Attacks/Breaches
8/28/2009
03:52 PM
Connect Directly
Google+
Twitter
RSS
E-Mail
50%
50%

Filtering Network Attacks With A 'Netflix' Method

University of California at Irvine researchers devise new model for blacklisting network attackers

Researchers have come up with a new method of blacklisting spam, distributed denial-of-service (DDoS) attacks, worms, and other network attacks that, in part, was inspired by Netflix's movie ratings recommendation system.

The so-called predictive blacklisting method proposed by University of California-Irvine researchers employs a combination of factors to improve blacklisting, such as trends in the times of attacks, geographical locations and IP address blocks, and any "connections" between the attacker and the victim, such as if an attacker had hit a victim's network before.

The blacklisting method "formalizes the blacklisting problem" when it comes to predicting the sources of attacks, says Athina Markopoulou, an assistant professor at UC-Irvine and a member of the research team.

Markopoulou and her team found that their method improves predictive blacklisting, accurately predicting up to 70 percent of attacks. "The hit-count of our combined method improves the hit-count of the state of the art for every single day," she says. "The improvement, depending on the day, is up to 70 percent, and 57 percent on average."

The method draws from Netflix's prediction system for unknown movie ratings, which uses known movie ratings to draw conclusions. "Our prediction system predicts future attackers based on past security logs," Markopoulou says.

Security experts say this new blacklisting method is mainly theoretical at this point -- there's no code or prototype -- but it could ultimately provide a way to minimize spam and other network-borne malicious traffic.

It's unlikely a mathematical algorithm can consistently predict a hacker's activity, says Robert Graham, CEO of Errata Security.

"[The UC-Irvine researchers] are trying to figure out how to find desktops sending out spam and to blacklist them. This is a filtering technique to cut down the noise," Graham says. "The thing is, they're trying to solve, with math, an issue of how people decide to attack the Net...But, ultimately, hackers do weird stuff. They will constantly do things outside the powers of [a mathematical prediction]. It has value in that it could cut down the noise. But you could never eliminate the noise."

Carey Nachenberg, a Symantec fellow for the security technology and response group, says the method basically sends a subset of blacklists to the potential victim versus a universal blacklist. "This is more academic," he says. "We already have blacklists we distribute to customers...it's not a big problem to have a universal blacklist [for anti-spam or IPS]," he contends.

Markopoulou says the method could be applied to security logs gathered by firewalls and IDSes, for instance, and an enterprise could better defend against attacks using this method. "An accurate blacklist predicts the attack sources that will attack the enterprise in the future. The enterprise can use this blacklist to proactively block these sources or to inspect in more detail traffic coming from those sources," she says.

In their paper (PDF), the researchers provide details about their test methodology and the algorithms they deployed. They tested their algorithms using hundreds of millions of logs from hundreds of networks gathered from a one-month period.

Markopoulou says the next step is for the research team to improve the prediction rate of the blacklisting approach. "Second, we want to understand what an attacker could do to evade our prediction method," she says.

Have a comment on this story? Please click "Discuss" below. If you'd like to contact Dark Reading's editors directly, send us a message. Kelly Jackson Higgins is Executive Editor at DarkReading.com. She is an award-winning veteran technology and business journalist with more than two decades of experience in reporting and editing for various publications, including Network Computing, Secure Enterprise ... View Full Bio

Comment  | 
Print  | 
More Insights
Register for Dark Reading Newsletters
White Papers
Cartoon
Current Issue
Dark Reading December Tech Digest
Experts weigh in on the pros and cons of end-user security training.
Flash Poll
Video
Slideshows
Twitter Feed
Dark Reading - Bug Report
Bug Report
Enterprise Vulnerabilities
From DHS/US-CERT's National Vulnerability Database
CVE-2014-5395
Published: 2014-11-21
Multiple cross-site request forgery (CSRF) vulnerabilities in Huawei HiLink E3276 and E3236 TCPU before V200R002B470D13SP00C00 and WebUI before V100R007B100D03SP01C03, E5180s-22 before 21.270.21.00.00, and E586Bs-2 before 21.322.10.00.889 allow remote attackers to hijack the authentication of users ...

CVE-2014-7137
Published: 2014-11-21
Multiple SQL injection vulnerabilities in Dolibarr ERP/CRM before 3.6.1 allow remote authenticated users to execute arbitrary SQL commands via the (1) contactid parameter in an addcontact action, (2) ligne parameter in a swapstatut action, or (3) project_ref parameter to projet/tasks/contact.php; (4...

CVE-2014-7871
Published: 2014-11-21
SQL injection vulnerability in Open-Xchange (OX) AppSuite before 7.4.2-rev36 and 7.6.x before 7.6.0-rev23 allows remote authenticated users to execute arbitrary SQL commands via a crafted jslob API call.

CVE-2014-8090
Published: 2014-11-21
The REXML parser in Ruby 1.9.x before 1.9.3 patchlevel 551, 2.0.x before 2.0.0 patchlevel 598, and 2.1.x before 2.1.5 allows remote attackers to cause a denial of service (CPU and memory consumption) a crafted XML document containing an empty string in an entity that is used in a large number of nes...

CVE-2014-8469
Published: 2014-11-21
Cross-site scripting (XSS) vulnerability in Guests/Boots in AdminCP in Moxi9 PHPFox before 4 Beta allows remote attackers to inject arbitrary web script or HTML via the User-Agent header.

Best of the Web
Dark Reading Radio
Archived Dark Reading Radio
Now that the holiday season is about to begin both online and in stores, will this be yet another season of nonstop gifting to cybercriminals?