Fhtm Updates

I am sure many of you have noticed a huge change in the attitude that is here on Fortune Social in the past few weeks. It appears as if all of the NSM's and Paul Orberson are trying diligently to hide the real truth from everyone about the real structure of the business as well as how and who really makes money.

When Fortune Social was originally conceived it was to be an umbrella for everything positive about FHTM. God only knows there was enough negativity in Google and the other search engines. Our primary objective was to help everyone build a profitable FHTM business. There is so much negativity in the search engines from the latest state actions that it will take years and a team of 1000's to combat this. We refuse to expend the resources, as we are 100% unappreciated by FHTM owners.

The attitude of the administrators of Fortune Social changed when the Montana Securities Commission issued a cease a desist order not only against FHTM, Paul Orberson and Thomas Mills – but also all of the reps and managers in Montana and specifically Mike Misenheimer. When this happened, FHTM feverishly tried to sweep it under the carpet and merely asked all Montana reps to temporarily stop doing business there. We could not! I personally don't intend to make Paul any wealthier at the expense of my family. I am also sick in tired of hearing that we are pissed because we FAILED. That is so far from the truth as you can get.

What happened to the dreams and financial freedom of all of those 1,600 somewhat reps that counted on Misenheimer and Orberson to eliminate their jobs and become debt free?  Seems to me like all of those dreams have been crushed and all of those reps are forbidden from engaging in any FHTM business. Do they still get their residuals or have they been hung out to dry?

Our staff immediately began an in depth investigation into FHTM and discovered so many irregularities from what they tell you to what is reality. I know this is going to piss off so many of the cult like believers in FHTM and Orberson but if you are going to hang your family's future and financial freedom on this entity – shouldn't you all know the REAL truth?

First – they DO not have a single direct relationship with any of the products they represent (except the companies Paul owns or controls) *see attached analysis ~

Secondly – NONE of the CEO's of any of the companies that FHTM represents ever went to Lexington to visit Paul or cut a deal. S0 many times prospects hear the phrase, "If GE, Verizon and DuPont can align with us – we must not be a pyramid scheme – we must be real". THIS IS SO BOGUS! Those companies are not DIRECTLY aligned with Fortune Hi-Tech Marketing.

Thirdly – Paul did not come out of retirement to help anyone other than himself. The pay plan is top heavy and if you read below you might understand why so many Stat Attorney Generals are going after FHTM with both barrels loaded for bear. Our research indicates that Montana was a cease and desist for not only FHTM but its officers and managers. What happens when they decide to issue a financial penalty against all of the ESM's or NSM's who purported this Fraud against Montanans'? Who pays this? I guarantee it won't be Orberson!

Additionally another dozen states have FHTM in their radar and are investigating them for the same things.  Friends in California sent us a copy of a suit filed towards the end of last month in CA which not only names FHTM but most of the President's pool and seeks $25Million in damages. Where does that leave all of the folks in California and the west coast of the USA?  Unfortunately, like addicts, most of the NSM's are in total denial. They have to be or their business would disintegrate tomorrow. Have they created a huge nest egg from all of the revenues, or spent it on their new found lavish lifestyle?

There is a fine line between illegal scam and a real network marketing company. All of the administrators of Fortune Social are very pro legal network marketing – but we cannot seem to find any real data that supports the fact that Fortune Hi-Tech Marketing is NOT a scam and illegal!

Open your eyes folks. So many of you around the US and Canada got into the FHTM business to build a future for your families and get away from the JOB. The administrators of Fortune Social understand that more than most as they have been entrepreneurs and self sufficient for over 30 years. We hate to see so many hang their hats on a system that benefits 100 or so people and 99% of the rest invest, suffer, quit or get shut down.

As regulators in the telecommunications field for over 20 years we understand the need to be legal, forthright and above board. Paul Orberson and the Presidential Ambassadors tell a great story, except 90% of it is BS designed to enhance themselves and their pocketbooks.

Fortune Social will be adding some new tools over the summer and will try and keep all of its users fully informed as to the latest legal woes of the company so many refuse to quit. Just remember – when you get named in a state cease and desist or lawsuit – YOU ARE OUT OF BUSINESS IMMEDIATELY AND ALL REVENUES STOP! Additionally it may cost you more to defend the fines than you ever made.

Fortune Hi-Tech Marketing (FHTM) Analysis of Product and Business Model

Howard Wagler @ 2:16 PM

FHTM is a multi level marketing company that purports to allow you to work directly with well known companies and make lots of money by taking a percentage back from purchases made through your FHTM representative site. In reality, if a representative stops signing people up under them, they will make very little money, as little as .5% on products sold through the site (unless you have eight levels of representatives sign up under you, and you also get a small cut of those under you who sell services or products). The get rich quick portion of the presentation relies on signing up people under you for $299 a person, and getting them to sign others up, as well as pay for training at $250 a person. Note that you also must pay a $199 renewal fee each year, and if you pay for the trainer course, an additional $100 trainer renewal fee. This is a text book example of a pyramid scheme, with a token product line on the side to try and make the business legitimate.

I will analyze some of the products that a FHTM representative can get a percentage back on (.5%), which is supposedly the primary focus of the business (if it is not, it is possibly illegal, so they have to pretend that this is the focus). From research and hearing actual representatives say it, the way to make money is to sign people up under you. One representative I heard from only made $17 in a month through the products, but made much more by convincing others to sign up too.

The whole point of this analysis is to show that the sale of products and services through FHTM is not a way to make large amounts of money, and in fact is offered to try and mask the true source of most earnings, which are derived from the sign up fees of new people joining. Thus the primary purpose of the company is to sign up new representatives, making it an illegal pyramid scheme.

MyTelTag
This is a product only available to Representatives and costs $19.99 a month. So clearly buying this won't make you money as a representative, and in fact will cost you $19.99 a month.

Peter Lamas has a direct affiliate program paying 20% that is free to sign up for. So going through FHTM pays you .5%, and signing up for a free affiliate account pays 20%.

Choice Plans RX
This is a FHTM company that they pay Ocenture to set up and run for them. When you go to the website, it has copyright FHTM, but when you look who owns the domain name, all contact emails are to ocenture.com email addresses. If you use this product, remember you are actually buying from FHTM, and be sure to check prices you are paying against a site such as drugstore.com. A spot check of the price list shows the drug Pegasys for 180MCG/0.5 for $1,482.23. It appears to be available from drugstore.com as a 1ml vial for $651.98. If the 0.5 in the ChoicePlanRX price refers to half a ML, then you pay $2,964.46 for 1ml, while at drugstore.com you can get it for $651.98. I suggest you look at the prices yourself.

Health Card
This product is yet another product that FHTM paid Ocenture to run, and Ocenture uses VantageAmerica Solutions, Inc. to run the card discounts. It looks like FHTM paid Ocenture to rebrand their pre packaged product called MedAffordable.

Travel FHTM
This is another service where FHTM paid Ocenture to rebrand and rename their existing product called TrotHop, and to set up an affiliate site through Travelocity, to book tickets through an airline. If you buy from TravelFHTM, you are going through three middlemen to reach the airline (FHTM, Ocenture, & Travelocity). Basically this service uses Travelocity, rebranded to look like TravelFHTM, adding on a fee to each ticket. Tickets tend to be $5 – $10 dollars more on TravelFHTM than buying straight from Travelocity, you can test this by checking the price for an identical flight through Travelocity and TravelFHTM. Also, in order to offer this product, the representative must pay $49.99

Roadside AutoClub
This is simply a service set up by Ocenture to provide roadside assistance.  to look at all the services Ocenture can set up for your organization. It looks like this is what FHTM did.

Ingrid Home Security
The link to this service did not work, so I was unable to assess what this service was. If the link is not working, it's safe to say you can't use this service.

Protect America
This appears to be a GE security product that FHTM markets, by going through an authorized dealer, greatalarms.com. So you have 2 middle men, (FHTM and greatalarms.com) As of 2.26.10, the FHTM's site had free* sign up options, but the asterisk beside the FREE does not have an explanation. It should include this: * "Standard monitoring agreement required with approved credit. ", FHTM is misleading if they don't show the disclaimer. It is not free.

FortuneTV.info
This is a product only available to Fortune Representatives, and so is not a way for FHTM reps to make money.

EZnet Tools
This is a Quick Website Creation Company that welcomes Multi Level Marketing Companies as affiliates. Information about joining EZnet Tools as an affiliate is available. If you want to set up a simple website, I suggest you use a reputable company like wordpress.com, who can have you online on your own domain name for $15 a year

Dish Network
Anyone can become an affiliate of Dish Network, and be paid $120 per installation, you can become an affiliate here. Compare that to .5% through FHTM, and the best choice is clear.

Magazines.com
You can sign up for free to be an affiliate of Magazines.com, and earn a 35% commission on subscriptions sold. Compare that to .5% through FHTM.

The Wireless Shop
One of the most talked about services at FHTM is the wireless shop. This is a website that FHTM uses Simplexity to run. You can buy cell phones and cell phone contracts through this service. Simplexity uses linkshare.com to purchase these services. By going through FHTM Wireless Shop you appear to be using three middlemen (FHTM, Simplexity, and Linkshare). Linkshare can be joined for free by going to simplexity's site which can be joined for free  and clicking on "Join Our Wireless Program Today" Alternately, you can go straight to LinkShare.com and create a free affiliate account, and start earning the full commission instead of the .5% FHTM gives back to their representatives. With this free account, you can earn affiliate money from many companies, a list of which can be found here. So FHTM does not really have a direct relationship with Verizon and AT&T, contrary to the impression given by the company.

The money that is implied to be available to be made to Representatives (as much as $80,000 a month is shown) is derived almost entirely from spreadsheets showing what would happen if you signed up three people at $299 a person, and they each signed up three people, and so on, down to eight levels. The problem with this type of business model, besides possibly being illegal, is that in order for people to make the money they were told they could, they have to continue signing up people. Whenever people no longer sign up, then all of the people at the bottom of the pyramid will lose their money. So even if you can get into a pyramid scheme like this before it collapses, and make money off of signing people up under you, when it does fail, most of the money that you made would have been taken from those under you, and they would lose it. For ethical and moral reasons, I would not want to take other people's money, knowing that sooner or later the money I make will be lost by someone down the line.

If you are still not convinced that this is not a legitimate business, the North Dakota attorney general issued a cease and desist order against FHTM in December (it has since been lifted).

Update 2: You can read the Temporary Cease and Desist Order here. It is lengthy, but has a lot of very relevant information.

How to Identify a Product-Based Pyramid Scheme ("Recruiting MLM")

© 2003, Jon M. Taylor, PhD

Multilevel companies that are based on profits from recruiting rather than retailing should be regarded as pyramid schemes or "recruiting MLMs." This article describes five ways to distinguish them from "retail MLMs" in which the company pays generously for retailing products without recruiting a large downline. "Recruiting MLMs" typically display five features:

1. Recruiting of participants is unlimited in an endless chain of recruiters recruiting recruiters.

Ask whether unlimited recruiting is allowed. When a given market is saturated, and the program must move on to another location or introduce new products or divisions to continue, the opportunity for each new person to make money becomes less and less as the programs expands.

2. Advancement in a hierarchy of multiple levels of "distributors" is achieved by recruitment, rather than by appointment.

Ask whether participating "distributors" advance their position (and potential income) in a hierarchy of multiple levels of "distributors" by recruiting other "distributors" who in turn advance by recruiting distributors under them, etc.? If so, the result is self-appointment through recruitment to ascending payout levels in the distributor hierarchy. If the only way a person can profit significantly in the scheme is through recruiting to advance to higher payout levels (or to buy another's downline), this strongly indicates a pyramid scheme.

3."Pay to play" requirements are satisfied by ongoing "incentivized purchases."

These are purchases of goods and services that are required to participate in commissions or to ascend in the distributor hierarchy. If they are required to participate in the "business opportunity," then whether they are used, sold, given away, or stored is irrelevant. They should be considered a cost of doing business.

Ask whether prospective "distributors" are encouraged to make sizable investments ("front loading") in "incentivized purchases" in order to take advantage of the "business opportunity" and later to continue qualifying for advancement or higher payout in overrides (commissions and bonuses). This practice, can result in large losses if the products cannot be resold.Also be wary of plans that require minimum periodic purchases ("pay to play") to qualify for commissions or advancement. Do not sign up for continuing product purchases on auto-ship through an automatic bank draft or credit card, rather than making occasional purchases as needed. Such purchase requirements may be disguised investments in a product-based pyramid scheme or a clever attempt to disguise pyramid investments as product purchases.

4. The company offers commissions and/or bonuses to more than five levels of "distributors."

Ask whether the company pay overrides to distributors in a hierarchy of more levels than are functionally justifiable. Even in major corporations, the entire world marketplace can be covered in five levels of sales management ­- branch, district, regional, national, and international sales managers. Paying commissions and bonuses on more than five levels in an MLM program primarily enriches those at the top at the expense of those at the bottom. You would be wise to avoid any program that pays overrides on more than five levels. Breakaway compensation systems are particularly exploitive, as payments are on a hierarchy of "breakaway" organizations of whole groups of participants, not just individuals -- creating an extraordinarily high loss rate, except for those at the top of a "mega-pyramid of pyramids."

5. Company payout per sale for each upline participant equals or exceeds that for the person selling the product, creating inadequate incentive to retail and excessive incentive to recruit -- and an extreme concentration of income at the top.

Ask whether a "distributor" purchasing products "for resale" would receive about the same total payout (in commissions, bonuses, etc.) from the MLM company as participants several levels above who had nothing to do with the sale. If so, the company's payments to the person retailing the product would be pitifully small, while those at the top of the upline can compound the small commission per sale by the sales of hundreds or even thousands of downline distributors. This is great for the upline leaders but lousy for those attempting retail sales. Avoid any MLM company that pays less than half of all distributor payout to the person actually selling the products to outside customers.

Never accept income projections of retail sales at full retail prices, especially for products that are overpriced and not competitive in the marketplace. Also be wary if you are asked to choose between two options or "tracks" -- one for those who want to "retail" the products and another track for those who are serious about "building the business." This sales pitch usually indicates that the incentives are heavily weighted towards recruiting

Where valid data are available, recent research has demonstrated that when all five of these red flags are found in an MLM, the percentage of participants who lose money is 99.9% -- even worse than the loss rates for typical no-product pyramid schemes and for games of chance in Las Vegas.

BEST OF LUCK TO ALL OF YOU HERE ON FORTUNE SOCIAL. WE HOPE ALL OF YOUR DREAMS COME TRUE, ALTHOUGH IT PROBABLY WONT BE IN FORTUNE HI-TECH.

http://www.fortunesocial.com/fortune-hi-tech-blogs/fhtm-updates.html

About the Author

A Survey on Botnets with Cryptography

Abstract.

 As technology has been developed, the network of bot, botnet, has been huge matter in computer science society. Most botnet causes network security threats and they are based on C&C server such as IRC, HTTP common protocol [1] and recently botnet also constructs P2P connection and the bot’s characteristics and activities are all different according to the structure of  botnet. That is why the existed research is numerous, too, and it is beneficial to categorize and to classify defense mechanism of bot. The bot activities result in a lot of negative effects such as DDoS (Distributed Denial of Service) and  Spamming. The mechanisms for bot detection and defenses can be categorized into C&C based bot detection and P2P based bot detection. A vital aspect of botnet administration is the authenticity and integrity of commands. Asymmetric cryptography offers a simple, yet effective way to do this and the methodology is discussed here.

Keywords: botnet, bot detection, P2P bot, C&C bot ,cryptography

 1. INTRODUCTION

The untraceable feature of coordinated attacks is just what hackers/attackers demand to compromise a computer or a network for their illegal purposes. Once a group of hosts with different locations are controlled by a malicious individual or organization to initiate an attack, one can hardly trace back the origins due to the complexity of the Internet. For this reason, the increase of events and threat against legitimate Internet activities such as information leakage, click fraud, denial of service (DoS) attack, and E-mail spam, etc., have become very serious problems nowadays[1]. Those victims controlled by coordinated attackers are called zombies, or bots which derives from the word “robotâ€. The term of bots is commonly referred to software applications running automated tasks over the Internet [2]. Under such a command and control (C2, or C&C) infrastructure, a group of bots are able to form a self-propagating, self-organizing, and autonomous framework, named botnet [3]. Generally, to compromise a series of systems, the botnet’s master (also called as herder or perpetrator) will remotely control bots to install worms, Trojan horses, or backdoors on them [3]. The majority of those victims are running Microsoft Windows operating system [3]. The process of stealing hosts resources to consist a botnet is so called “scrumping†[3].

Botnets  can be classified into two major categories based on their topologies [4]. One typical and the most common type is Internet Relay Chat (IRC) based botnets. Because of its centralized architecture, researchers have designed some feasible countermeasures to detect and destroy such botnets [5, 6]. Hence, newer and more sophisticated hackers/attackers start to use Peer to Peer (P2P) technologies in botnets [4,7]. P2P botnets are distributed and do not have central point of failure. Comparing to IRC-based botnets, they are more difficult to detect and take down [4]. Besides, most of its existing studies are still in the analysis phase [4, 7].

 The organization of the paper is as follows. In Section 2, botnet  classification is given.Section 3 describes the relevant attacks. Section 4 elaborates the detection and tracing mechanisms. Preventive measures are given in Section 5. The conclusion and future challenges are shown in Section 6.

 2. CLASSIFICATION

Botnets are emerging threats with billions’ hosts worldwide infected. Bots can spread over thousands of computers at a very high speed like worms do. Unlike worms, bots in a botnet are able to cooperate towards a common malicious purpose. For that reason, botnets nowadays play a very important role in the Internet malware epidemic [16]. In [19] the W. T. Strayer et al. presented some metrics by flow analysis on detecting botnets. After filtering IRC session out of the traffic, flow based methods were applied to discriminate malicious from benign IRC channels. The methods proposed by [20] and [21] combined both application and network layer analysis. E. Cooke et al. [22] dealt with IRC activities at the application layer, using information coming from the monitoring of network activities. Some authors had introduced machine learning techniques into botnet detection [23], since they led a better way to characterize botnets. Currently, honeynets and Intrusion Detection System (IDS) are two major techniques to prevent their attacks. Honeynets can be deployed in both distributed and local context [9]. They are capable of providing botnet attacking information, but can not tell the details like whether the victim has a certain worm [9]. The IDS uses the signatures or behavior of existing botnet for references to detect potential attack. Thus, to summarize the characteristics of botnet is significant for a secure network. To the best of our knowledge, we have not found any other work about anomaly-based detection for botnet.

 2.1 Formation and Exploitation

To illustrate the formation and exploitation, we take spamming botnet as an example. A typical formation of botnet can be described as following steps [3],

1) The perpetrator of botnet sends out worms or viruses to infect victims' machines, whose payload are bots.

2) The bots on the infected hosts log into an IRC server or other communications medium, forming a botnet.

3) Spammer makes payment to the owner of this botnet to gain the access right.

4) Spammer sends commands to this botnet to order the bots to send out spam.

5) The infected hosts send the spam messages to various mail servers in the Internet.

 2.2  IRC-based Bot

IRC is a protocol for text based instant messaging among people connected with the Internet. It is based on Client/Server (C/S) model but suited for distributed environment as well [18]. Typical IRC severs are interconnected and pass messages from one to another [18]. One can connect with hundreds of clients via multiple servers. It is so called multiple IRC (mIRC), in which communications among clients and server are pushed to those who are connected to the channel. The functions of IRC based bots include managing access lists, moving files, sharing clients, sharing channel information, and so on [18].

• Bot: is typically an executable file triggered by a specific command from the IRC sever. Once a bot is installed on a victim host, it will make a copy into a configurable directory and let the malicious program to start with operating system. Generally, bots are just the payload of worms or the way to open a backdoor [18].

• Control channel: is a secured IRC channel set up by the attacker to manage all the bots.

• IRC Server: may be a compromised machine or even a legitimate provider for public service.

• Attacker: is the one who control the IRC bot attack.

The attacker’s operations have four stages [16]:

1) Creation Stage, where the attacker may add malicious code or just modify an existing one out of numerous highly configurable bots over the Internet [16].

2) Configuration Stage, where the IRC server and channel information can be collected [16]. As long as the bot is installed on the victim, it will automatically connect to the selected host [16]. Then, the attacker may restrict the access and secure the channel to the bots for business or some other purpose [16]. For example, the attacker is able to provide a list of bots for authorized users who want to further customize and use them for their own purpose.

3) Infection Stage, where bots are propagated by various direct and indirect means [16]. As the name implies, direct techniques exploit vulnerabilities of the services or operating systems, and are usually associated with the use of viruses [16]. While the vulnerable systems are compromised, they continue the infection process such that saving the time of  attacker to add other victims [16]. The most vulnerable systems are Windows 2000 and XP SP1, where the attacker can easily find unpatched or unsecured (e.g., without firewall) hosts[16]. By contrary, indirect approaches use other programs as a proxy to spread bots, e.g., using distributed malware through DCC (Direct Client-to-Client) file exchange on IRC or P2P networks to exploit the vulnerabilities of target machines [16].

4) Control Stage, where the attacker can send the instructions to a group of bots via IRC channel to do some malicious tasks.

 2.3  P2P-based Bot

Few papers focus on P2P-based bot so far [4, 24-29, 46]. It is still a challenging issue. In fact, using P2P adhoc network to control victim hosts is not a novel technique [26].P2P communication system is much harder to disrupt. This means that the compromise of a single bot does not necessarily mean the loss of the entire botnet. However, the design of P2P systems are more complex and there are typically no guarantees on messages delivery or latency. A worm with a P2P fashion, named Slapper [27], infected Linux system by DoS attack in 2002. It used hypothetical clients to send commands to compromised hosts and receive responses from them [27]. Thereby, its network location could be anonymous and hardly be monitored [27]. One year after, another P2P-based bot appeared, called Dubbed Sinit [28]. It used public key cryptography for update authentication. Later, in 2004, Phatbot [29] was created to send commands to other compromised hosts using a P2P system. Currently, Storm Worm [24] may be the most wide-spread P2P bot over the Internet. T. Holz et al. have analyzed it using binary and network tracing [24]. Besides, they also proposed some techniques to disrupt the communication of P2P-based botnet, such as eclipsing content and polluting the file.

Nevertheless, the above P2P-based bots are not mature and have many weaknesses. Many P2P networks have a central server or a seed list of peers who can be contacted for adding a new peer. This process named bootstrap has a single point of failure for aP2P-based botnet [25]. For this reason, authors in [25] presented a specific hybrid P2P botnet to overcome this problem.

 2.4  Types of Bots

Many types of bots in the network have already been discovered and studied [9, 16, 17]. Table I will present several widespread and well-known bots, together with their basic features.

Types

Features

Agobot

Phatbot

Forbot

Xtrembot

1. They are so prevalent that over 500 variants exist in the Internet today. Agobot is the only bot that can use other                 control protocols besides IRC [9]. It offers various approaches to hide bots on the compromised hosts,including NTFS Alternate Data Stream, Polymorphic

Encryptor Engine and Antivirus Killer [16].

SDBot

RBot

UrBot

UrXBot

SDBot is the basis of the other three bots and probably many more [9]. Different from Agobot, its code is unclear and only has limited functions. Even so, this group of bots is still widely used in the Internet [16].

SpyBot

NetBIOS

Kuang

Netdevil

KaZaa

There are hundreds of variants of SpyBot nowadays [17]. Most of their C2 frameworks appear to be shared with or evolved from SDBot [17]. But it doesn’t provide accountability or conceal their malicious purpose in codebase [17].

mIRC-based

GT-Bots

GT (Global Threat) bot is mIRC-based bot. It enables a mIRC chat-client based on a set of binaries (mainly DLLs) and scripts [16]. It often hides the application window in

compromised hosts to make mIRC invisible to the user [9].

DSNX Bots

The DSNX (Data Spy Network X) bot has a convenient plug-in interface for adding a new function [16]. Albeit the default version does not meet the requirement of spreaders, plugins can help to address this problem [9].

Q8 Bots

It is designed for Unix/Linux OS with the common features of a bot, such as dynamic HTTP updating, various DDoS-attacks, execution of arbitrary commands etc. [9].

Kaiten

It is quite similar to Q8 Bots due to the same runtime environment and lacking of spreader as well. Kaiten has an easy remote shell, thus it is convenient to check further

vulnerabilities via IRC [9].

Perl-Based Bots

Many variants written on Perl nowadays [9]. They are so small that only have a few hundred lines of the bots code [9]. Thus, limited fundamental commands are available for attacks, especially for DDoS-attacks in Unix-based systems [9].

 

3. BOTNET ATTACKS

Botnets can serve both legitimate and illegitimate purposes [6]. One legitimate purpose is to support the operations of IRC channels using administrative privileges on specific individuals. Nevertheless, such goals do not meet the vast number of bots that we have seen. Based on the wealth of data logged in Honeypots [9], the possibilities to use botnets for criminally motivated or for destructive goals are able to be categorized as follows.

 3.1 DDoS Attacks

Botnets are often used for DDoS attacks [9], which can disable the network services of victim system by consuming its bandwidth. For instance, a perpetrator may order the botnet to connect a victim’s IRC channel at first, and then this target can be flooded by thousands of service requests from the botnet. In this kind of DDoS attack, the victim IRC network is taken down. Evidence reveals that most commonly implemented by botnets are TCP SYN and UDP flooding attacks [30].

General countermeasure against DDoS attacks requires: (1) controlling a large number of compromised machines; (2) disabling the remote control mechanism [30]. However, we still need more efficient ways to avoid this kind of attack. F. C. Freiling et al. [30] have presented an approach to prevent DDoS attack via exploring the hiding bots in Honeypots.

3.2 Spamming and Spreading Malware

About 70% to 90% of the world’s spam is caused by botnets nowadays, which has most experienced in the Internet security industry concerned [47, 49]. Study report indicates that, once the SOCKS v4/v5 proxy (TCP/IP RFC 1928) on compromised hosts is opened by some bots, those machines may be used for nefarious tasks, e.g., spamming. Besides, some bots are able to gather email addresses by some particular functions [9]. Therefore, attackers can use such a botnet to send massive amounts of spam [31]. Researchers in [32] have proposed a distributed content independent spam classification system, called Trinity, against spamming from botnets. The designer assumes that the spamming bots will send a mass of e-mails within a short time. Hence, any letter from such address can be a spam.

In order to discover the aggregate behaviors of spamming botnet and benefit its detection in the future, Y. Xie et al. [33] have designed a spam signature generation framework named AutoRE. They also found several characteristics of spamming botnet: (1) spammer often appends some random and legitimate URLs into the letter to evade detection [33]; (2) botnet IP addresses are usually distributed over many ASes (Autonomous Systems), with only a few participating machines in each AS on average [33]; (3) despite the contents of spam are different, their recipients’ addresses may be similar [33]. How to use these features to capture the botnets and avoid spamming is worth to research in the future. Similarly, botnets can be used to spread malware too[9]. For instance, botnet can launch Witty worm to attack ICQ protocol since the victims’ system may have not activated Internet Security Systems (ISS) services [9].

3.3 Information Leakage

Because some bots may sniff not only the traffic passing by the compromised machines but also the command data within the victims, perpetrators can retrieve sensitive information like usernames and passwords from botnets easily[9]. Evidences indicate that, botnets are becoming more sophisticated at quickly scanning in the host for significant corporate and financial data [47]. Since the bots rarely affect the performance of the running infected systems, they are often out of the surveillance area and hard to be caught. Keylogging is the very solution to the inner attack [9,16]. Such kind of bot listens for keyboard activities and then reports to its master the useful information after filtering the meaningless inputs. This enables the attacker to steal thousands of private information and credential data [16].

3.4 Click Fraud

With the help of botnet, perpetrators are able to install advertisement add-ons and browser helper objects (BHOs) for business purpose[9]. Just like Google’s AdSense program, for the sake of obtaining higher click-through rate (CTR), perpetrators may usebotnets to periodically click on specific hyperlinks and thus promote the CTR artificially [9]. This is also effective to online polls or games [9]. Because each victim’s host owns a unique IP address scattered across the globe, every single click will be regarded as a valid action from a legitimate person.

3.5 Identity Fraud

Identity Fraud, also called as Identity Theft, is a fast growing crime on the Internet [9]. Phishing mail is a typical case. It usually includes legitimate-like URLs and asks the receiver to submit personal or confidential information. Such mails can be generated and sent by a botnet through spamming mechanisms [9]. In a further step, botnets also can set up several fake websites pretending to be an official business sites to harvest victims’ information. Once a fake site is closed by its owner, another one can pop up, until you shut down the computer.

 4. DETECTION AND TRACING

By now, several different approaches of identifying and tracing back botnets have been proposed or attempted. First and the most generally, the use of Honeypots, where a subnet pretends to be compromised by a Trojan, but actually observing the behavior of attackers, was enabling the controlling hosts to be identified[22]. In a relevant case, Freiling et al. [30] have introduced a feasible way to detect certain types of DDoS attacks lunched by the botnet. To begin with, use honeypot and active responders to collect bot binaries. Then, pretend to join the botnet as a compromised machine by running bots on the honeypot and allowing them to access the IRC server. At the end, the botnet is infiltrated by a “silent drone†for information collecting, which may be useful in botnet dismantling. Another and also commonly used method is that, using the information form insiders to track an IRC-based botnet [11]. The third but not the least prevalent approach to detect botnets is probing DNS caches on the network to resolve the IP addresses of the destination servers [11].

 4.1 Honeypot and Honeynet

Honeypots are well-known by their strong ability to detect security threats, collect malwares, and to understand the behaviors and motivations of perpetrators. Honeynet, for monitoring a large-scale diverse network, consists of more than one honeypot on a network. Most of researchers focus on Linux-based honeynet, due to the obvious reason that, compared to any other platform, more freely honeynet tools are available on Linux [6]. As a result, only few tools support the honeypots deployment on Windows and intruders start to proactively dismantle the honeypot.

Some scholars aim at the design of a reactive firewall or related means to prevent multiple compromises of honeypots [6]. While a compromised port is detected by such a firewall, the inbound attacks on it can be blocked [6]. This operation should be carried on covertly to avoid raising suspicions of the attacker. Evidence tells us, we need operate less covert on protection of honeypots against multiple compromises by worms, due to worms are used to detect its presence [6]. Because many intruders download toolkits in a victim immediate aftermath, we should block correspond traffic only selectively. Such toolkits are significant evidences for future analysis. Hence, to some extent, attackers’ access to honeypots should not be prevented very well [6].

As honeypots have become more and more popular in monitoring and in defense systems, intruders begin to seek a way to avoid  evade honeypot traps [34]. There are some feasible techniques to detect honeypots. For instance, to detect VMware or other emulated virtual machines [35,36], or, to detect the responses of program’s faulty in honeypot [37]. In [38], Bethencourt et al. have successfully identified honeypots using intelligent probing according to public report statistics. In addition, Krawetz [39] have presented a commercial spamming tool capable of anti-honeypot function, called “Send-Safe’s Honeypot Hunterâ€. By checking the reply from remote proxy, spammer is able to detect honeypot open proxies [39]. However, this tool cannot effectively detect others except open proxy honeypot. Recently, C.C. Zou et al. [34] have proposed another methodology for honeypot detection based on independent software and hardware. In their paper, they also have introduced an approach to effectively locate and remove infected honeypots using a P2P structured botnet [34]. All above evidences indicate that, in case that botnet becomes invisible to honeypot, the relevant research should be improved.

4.2 IRC-based Detection

IRC-based botnet is wildly studied and therefore several characteristics have been discovered for detection so far. One of the easy ways to detect this kind of botnets is to sniff traffic on common IRC ports (TCP port 6667), and then check whether the payloadsmarch the strings in our knowledge database [22]. Nevertheless, botnets can use random ports to communicate. Therefore, another approach looking for behavioral characteristics of bots comes up. S. Racine [40] found IRC-based bots were often idle and only responded upon receiving a specific instruction. Thus, the connections with such features can be marked as potential enemies. Nevertheless, it still has a high false positive rate in the result.

There are also other methodologies exist for IRC-based botnet detection. Barford et al. [17] proposed some approaches based on the source code analysis. Rajab et al. [11] introduced a modified IRC client called IRC tracker, which was able to connect the IRC sever and reply the queries automatically. Given a template and relevant fingerprint, the IRC tracker could instantiate a new IRC session to the IRC server [11]. In case the bot master could find the real identity of the tracker, it appeared as a powerful and responsive bot on the Internet and run every malicious command, including the responses to the attacker [11]. Following, we will introduce some detection methods against IRC-based botnet.

4.2.1 Detection Based on Traffic Analysis

Signature technology is often used in anomaly detection. The basic idea is to extract feature information on the packets from the traffic and march the patterns registered in the knowledge base of existing bots. Apparently, it is easy to carry on by simply comparing every byte in the packet, but it also goes with several drawbacks [45]. Firstly, it is unable to identify the undefined bots [45]. Second, it should always update the knowledge base with new signatures, which enhances the management cost and reducesthe performance [45]. Third, new bots may launch attacks before they are patched in the knowledge base [45].

Based on the features of IRC, some other techniques to detect botnet come up. Basically, two kinds of actions are involved in a normal IRC communication. One is interactive commands and another is messages exchanging [45]. If we can identify the IRC operation with a specified program, it is possible to detect a botnet attack [45]. For instance, the private information is copied to other place by some IRC commands, we claim the system is under an attack since a normal chatting behavior will never do that [45]. On the other hand, the traffic may be encrypted or be concealed by network noises [21]. Any situation will make the bots invisible.

In [45], authors observed the real traffic on IRC communication ports ranging from 6666 to 6669. They found some IRC clients repeated sending login information while the server refused its connection [45]. Based on the experiment result, they claimed that bots would repeat these actions at certain intervals after refused by the IRC server, and those time intervals are different [45]. However, they did not consider a real IRC-based botnet attack into their experiment. It is a possible future work to extend their achievements.

 In [49], P. Sroufe et al. proposed a different method for botnet detection. Their approach can efficiently and automatically identify spam or bots. The main idea is to extract the shape of the Email (lines and the character count of each line) by applying a Gaussian kernel density estimator [49]. Emails with similar shape are suspected. However, authors did not show the way to detect botnet by using this method. It may be another future work worth to study.

 

4.2.2 Detection Based on Anomaly Activities

In [21], authors proposed an algorithm for anomaly-based botnet detection. It combined IRC mesh features with TCP-based anomaly detection module. It first observed and recorded a large number of TCP packets with respect to IRC hosts. Based on the ratio computed by the total amount of TCP control packets (e.g., SYN, SYNACK, FIN, and RESETS) over total number of TCP packets, it is able to detect some anomaly activities [21]. They called this ratio as the TCP work weight and claimed that high value implied a potential attack by a scanner or worm [21]. However, this mechanism may not work if the IRC commands have been encoded, as the discussion in [21].

 4.3 DNS Tracking

Since bots usually send DNS queries in order to access the C2 servers, if we can intercept their domain names, the botnet traffic is able to be captured by blacklisting the domain names [41, 42]. Actually, it also provides an important secondary avenue to take down botnets by disabling their propagation capability [11]. H. Choi et al. [41] have discussed the features of botnet DNS. According to their analysis, botnets’ DNS queries can be easily distinguished from legitimate ones [41]. First of all, only bots will send DNS queries to the domain of C2 servers, legitimate one never do this [41]. Secondly, botnet’s members act and migrate together simultaneously, as well as their DNS queries [41]. Whereas the legitimate one occurs continuously, vary from botnet [41]. Third, legitimate hosts will not use DDNS very often while botnet usually use DDNS for C2 Server [41]. Based on the above features, they developed an algorithm to identify botnet DNS query [41]. Their main idea is to compute the similarity for group activities and then distinguish the botnet from them based on its value. The similarity value is defined as 0.5 (C/A+C/B), where A and B stand for the size of two requested IP lists which have somecommon IP addresses and the same domain name, and C stands for the size of duplicated IP addresses [41]. If the value approximated zero, such common domain will be suspected [41].

There are also some other approaches. Dagon et al. [42] presented a method by examining the query rates of DDNS domain. Abnormally high rates or temporally concentrated were suspected, since the attackers changed their C2 servers quite often [44]. They utilized both Mahalanobis distance and Chebyshev’s inequality to quantify how anomalous the rate is [44]. Schonewille et al. [43] found that when C2 servers had been taken down, DDNS would often response name error. Hosts who repeatedly did such queries could be infected and thus to be suspected [43]. In [44], authors evaluated the above two methods through experiments on real world. They claimed that, Dagon’s approach was not as effective since it misclassified some C2 server domains with short TTL, while Schonewille’s method was comparative effective due to the suspicious name came from independent individuals [44]. In [48], X. Hu et al. proposed a botnet detection system called RB-Seeker (Redirection Botnet Seeker). It is able to automatically detect botnets in any structure. RB-Seeker first gathers information about bots redirection activities (e.g., temporal and spatial features) from two subsystems. Then it utilizes the statistical methodology and DNS query probing technique to distinguish the malicious domain from legitimate ones. Experiment result shows that RB-Seeker is an efficient tool to detect both “aggressive†and “stealthy†botnets.

 

5. Strong Cryptography

5.1Tamper-proof command and update scheme

A vital aspect of botnet administration is the authenticity and integrity of commands. A bot should only accept commands issued by the botmaster. In current botnets, the botmasters commonly use only a very weak form of authenticity, eg., by using a simple password scheme before sending the actual command. Even if the botnets use stronger authentication schemes, these can typically be broken, eg., Storm Worm uses a 64 bit RSA implementation which can be defeated. In centralized IRC botnets, this lack of authenticity could for example be overcome by patching the IRC server used for command distribution in such a way that only the botmaster can send messages in the designated channel. However, when dealing with a decentralized network of equal peers, a botmaster needs to ensure that no hostile parties like defenders or other botnet groups can poison the botnet by injecting malicious commands.

Asymmetric cryptography offers a simple, yet effective way to do this: before releasing a bot in the wild, the botmaster creates a public/private pair of cryptographic keys of which the former one is hardcoded into the bot’s binary. Doing so enables the botmaster to securely sign any commands or  files  using his private key. All peers in the botnet are able to verify the commands employing the hardcoded public key, but given a reasonable key length(eg.2048 bits for RSA), no defender will manage to forge the signature.

5.2Rent a botnet

With the help of asymmetric cryptography, a botmaster  can take on the role of a trusted certificate authority, which provides an efficient way to rent the botnet to  others in parts or as a whole, for a variable amount of time, and for certain purposes.To protect against malicious lessees, it is advisable to  implement a blacklist containing all invalidated public keys.This blacklist is saved on each bot’s computer and only the botmaster may add or remove public keys using his private key to sign the order. Thus, all certificates which belong to an attacker can be revoked.

However, such a blacklist is of little use against attacks which require only a short timeframe to be carried out successfully. For example, a malicious lessee could buy a botnet certificate for spam distribution and misuse it by ordering all bots to send an e-mail to a specified address, thereby revealing their IP address or other sensitive data. In effect, an attacker could conveniently obtain valuable information about a botnet’s size as well as its overall structure. Therefore , renting a botnet should be considered as an option which has to be used with caution by a botmaster.

6. PREVENTIVE MEASURES

Only need a couple of hours for conventional worms to circle the globe since released from a single host. If worms using botnet appear from multiple hosts simultaneously, they are able to infect the majority of vulnerable hosts worldwide in minutes [7]. Some botnets have been discussed in previous sections. Nevertheless, there still plenty of them are unknown to us. How to minimize the risk caused by botnets in the future is the topic we discussed in this section.

6.1 Countermeasures on Botnet Attacks

Unfortunately, few solutions exist for a host to against a botnet DoS attack so far [3]. Albeit it is hard to find the patterns of malicious hosts, network administrators can still identify botnet attacks based on passive operating system fingerprinting extracted from the latest firewall equipment [3]. The lifecycle of botnet tell us, bots often utilize free DNS hosting services to redirect a subdomain to an inaccessible IP address. Thus, removing those services may take down such a botnet [3]. At present, many security companies focus on offerings to stop botnets [3]. Some of them protect consumers, whereas most others are designed for ISPs or enterprises [3]. The individual products try to identify bot behavior by anti-virus software. The enterprise products have nothing better solutions than nullrouting DNS entries or shutting down the IRC and other main servers after a botnet attack  identified [3].

6.2 Countermeasures for Public

Personal or corporation security inevitably depends on the communication partners [7]. Building a good relationship with those partners is essential. Firstly, one should continuously request the service supplier for security packages, such as firewall, anti-virus tool-kit, intrusion detection utility etc. [7]. Once something goes wrong, there should be a corresponding contact number to call [7]. Secondly, one should also pay much attention on network traffic and report to ISP if attacked by DDoS attack. ISP can help blocking those malicious IP addresses [7]. Thirdly, one is better to establish accountability on its system, together with a law enforcement authority [7]. More specifically, scholars and industries have proposed some strategies for both home users and system administrators, to prevent, detect and respond botnet attacks [16, 18]. Here we summarize their suggestions.

6.2.1 Home Users

TABLE II: RULES OF PREVENTION BY HOME USERS [18]

Type

 

Strategies

Personal  Habits

 

Attention while downloading

Avoid to install useless things

Read carefully before you click

Routine

Use anti-virus/trojan utilities

Update system frequently

Shutdown PC when you leave

Optional Operations

Back-up all systems regularly

Keep all software up-to-date

Deploy personal firewall

 

6.2.2 System Administrator

In the same way, there are correspond rules for system administrator to prevent, detect, and respond botnet attacks [16, 18]. As the prevention methods, administrator should follow vendor guidelines for updating the system and applications [18]. Also, keep informed of latest vulnerabilities and use access control and log files to achieve accountability [18]. As illustrated in Table III, these can help the system administrator to minimize the possibilities of botnets attacking.

 TABLE III: RULES OF DETECTION BY SYSTEM ADMINISTRATORS [18]

Rules

 

Notes

Regular monitor logs

Analyze the internet traffic for anomalies

Use network packet sniffer

Identify the malicious traffic in intranet

Isolate the malicious subnet

Verify IRC activity on host

Scan individual machine

They may contain malware

Once an attack is detected, system administrator should isolate those compromised hosts and notice the home users [16]. Then preserve the data on those infected hosts including the log files [16]. Besides, identify the number of victims via sniffer tools [16]. Finally, report the infection to security consultant [16].

7. CONCLUSION AND FUTURE CHALLENGES

To better understand the botnet and stop its attack eventually, we provide a botnet survey on existing researches. The content of discussion involves botnet formation and exploitation, and two typical topologies.

According to the discussion in Section 2, we have several ideas on different topologies. For IRC-based botnet issues, the thorny problem is that we can not get the source code of most of bots. Hence, depth analysis at networking level and system level for bots’ behaviors are hardly carried on. For P2P-based botnet issues, following practical challenges should be further considered: (1) maintaining the rest of bots after some have been taken down by defenders; (2) hiding the botnet topology while some bots are captured by defenders; (3) managing the botnet more easily; (4) changing the traffic patterns more often and make it harder for detection.

 As we can see, detecting and tracking compromised host in botnet will continue to be a challenging task. Traffic fingerprinting is useful for identifying botnet. Nevertheless, just like previous signature technologies discussed in Section 3, its drawbacks are obvious. We need an up-to-date knowledge base for all released bots in the world, which seems to be an impossible mission. Anomaly detection is another feasible approach. However, when infected hosts do not behave as unusual, it may be unable to detect  such a potential threat. Since current detecting technology depends on the happened attacking event, no guarantee for us to find every possible compromised hosts. One interesting issue about anomaly detection is the time efficiency. If an attack is occurs and we can capture the anomaly at first place and fix the relevant problems before it is used for malicious purposes, we say this anomaly detection is time efficient. We need focus on its time efficiency in the future work.

 In wireless context, especially for ad hoc network, we still have not got related research on both attacking and defending so far. There are lots of open issues: (1) How to find the shortest routing to attack target; (2) How to prevent the compromised hosts fromdetecting in the wireless network; (3) How to propagate the bots in the wireless network, especially before some compromised hosts off line.

 There are also some other interesting open issues need to be considered. To the best of our knowledge, by now, we cannot avoid DDoS attack derived from botnets. Even the attacking has been detected, no effective way to trace back and fight against it. Instead, we just simply shut down the compromised hosts or disconnect with the network, waiting for further command such as scanning virus or formatting the operating system. As the matter of fact, what we need indeed is avoiding bots propagating in the first step. Perhaps the only effective approach to eliminate botnets is deploying new protocols on routers worldwide. It is really a huge and beyond reality project. Then, why not consider installing it on a local gateway? Imagining, if the gateway could block the communication of bots between several domains, the attacker would not easily manage the compromised hosts worldwide. At the meantime, the gateway might give our information as to where the malicious command came from. Based on the plenty of evidences over network, it would be possible tracing back the initial attack. Nevertheless, it is very difficult to implement such an idea due to the following reasons: (1) It is hard to distinguish the malicious packets from the traffic flow; (2) Cooperating among domains is not very easy, and should consider the situation that some gateways are compromised; (3) How to trace the potential attack and who should be noticed for further analysis need to be studied.

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About the Author

Authors
1.G. Satyavathy, Lecturer,Department of Computer Science, Sri Ramakrishna College Of Arts and Science For Women,Coimbatore-641 044.
2.Dr. M. Punithavalli, Director and Head, Department Of Computer Science, Sri Ramakrishna College Of Arts and Science For Women,Coimbatore-641 044.

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