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8/24/2012
08:56 PM
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Application Detects Social Network Spam, Malware

Using the social context of posts, researchers from UC Riverside create prototype Facebook app that detects social malware with 97 percent accuracy

Social networks are both a boon and bane for online criminals: People using the networks tend to trust messages sent by "friends" and other users to whom they are connected, making social engineering that much more effective. On the other hand, the networks are gated communities, where security policies and technologies can radically change the attack landscape.

MyPageKeeper, a project designed and created by computer scientists at the University of California, Riverside, does just that. Created as a Facebook application, the program searches the news feeds of its subscribers every two hours looking for suspected social malware and scams, collectively referred to as "socware" by the researchers. When it finds a suspect post, it leaves a comment indicating that the item is likely a scam or malware.

The group was able to correlate posts that were duplicated across MyPageKeeper's user base -- on sign of spamminess -- and posts that contained links to suspect Internet addresses, accurately identifying socware in 97% of cases.

"The core technology underlying this app is how to efficiently see what posts are pointing to malicious Web pages," says Harsha V. Madhyastha, an assistant professor in computer science and engineering at UC Riverside and a co-author of a paper on the project presented at the USENIX Security Conference earlier this month. "We identify what is suspicious without crawling every link in every post. To minimize our costs, we identify what is bad and what is good just based on what we call the social context -- the information included in the post and the URLs."

Socware is prevalent on social networks. Almost half of all users had encountered a scam or malware on Facebook in the prior four months, according to the researchers. In addition, socware is tailored to take advantage of the way each service works. For example, likejacking -- referred to by the researchers as "like as a service" -- is a method for fooling users into inadvertently raising the reputation of Facebook applications or posts.

"Typically per day, we find 50 unique URLs, and those are spread across hundreds of users," Madhyastha says. "And this is from our subset of Facebook users that are out there."

[ Recent widespread spam runs posing as convincing-looking email messages from LinkedIn, Facebook, ADP, American Express, US Airways, the U.S. Postal Service, UPS, and several other high-profile organizations are all part of a single, orchestrated attack campaign. See Series Of Convincing Spam Runs Part Of One Massive Advanced Attack Campaign.]

The project suggests ways of curtailing the pollution of spam, malicious apps, and fraudulent links on social networking sites, such as Facebook and Twitter. Earlier this month, Facebook estimated that 8.7 percent of the accounts on its site are fake in some way.

The techniques could also help companies protect their employees on social networks, identifying potentially fraudulent posts. The researchers are also investigating ways of rolling back posts and tweets that a person may regret posting or that violate company policy.

Other technologies have struggled with solving the problem of malicious activities on social networks, says Michael Sutton, vice president of security research at Web security firm Zscaler. Attackers have already adapted to defensive techniques, such as URL filtering and antivirus.

"The old ways of doing security are really struggling with things such as social networks," he says.

The problem with the UC Riverside approach, however, is that it is specific to each social network. The provider would have to create an app for each provider's application programming interface.

Yet, socware exists almost entirely in the social networking world, and so it makes most sense to solve the problem there, says Adam Wosotowsky, messaging data architect with McAfee.

"This is a good technique -- a version 1.0 to be able to sure, but the direction, I think, is the right direction," he says. "If you want to protect in the realm of the social networking service, you have to be in the realm of the social networking service."

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Candace
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Candace,
User Rank: Apprentice
8/25/2012 | 6:01:59 AM
re: Application Detects Social Network Spam, Malware
Kudos to the UC Riverside team for taking on social spam. Their findings underscore how the spam problem is growing and why site owners should consider defensive technologies against it. Unfortunately, social spam creates real costs in-various forms including lost users, tarnished reputation, skewed analytics, and decreased ad revenue. Automated moderation, leveraging analysis of context, URLs, and other features, is definitely the way to go.
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