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[] Detecting Cyberattacks By Profiling "Normal" Computer Habits,

Detecting Cyberattacks By Profiling "Normal" Computer Habits

Anaheim - Oct 11, 2002

An early version of a new software system developed by University at
Buffalo researchers that detects cyberattacks while they are in
progress by drawing highly personalized profiles of users has proven
successful 94 percent of the time in simulated attacks.

The "user-level anomaly detection system" was described Oct. 10, 2002
at the military communications conference known as MILCOM 2002 in
Anaheim, CA.

"We have developed a new paradigm, proactively encapsulating user
intent where you basically generate a profile for every single user in
the system where security is a major concern," said Shambhu Upadhyaya,
Ph.D., associate professor of computer science and engineering at UB
and co-author of the paper.

In addition to the paper presentation, MILCOM invited Upadhyaya to
give a half-day tutorial on the new intrusion detection system at the

Upadhyaya directs UB's Center of Excellence in Information Systems
Assurance Research and Education, one of 36 in the U.S. chosen by the
National Security Agency to develop new programs to conduct research
and train students to protect the nation's information technology
systems from cyberterrorism.

The new UB intrusion detection system is being developed for
application in highly secure facilities, such as those in the

"Existing approaches look at a past record of computer activity
because those systems produce audits of activity for every user," he
explained. "Our methodology is a marriage of two known techniques:  
misuse and anomaly detection. We use an assertion/rule-based approach
to precisely capture the initial bracket of activity and then
fine-tune this profile to reflect ongoing activity, making highly
personalized and accurate profiles possible.

"Also, since users are being constantly monitored, this system can
detect intrusions or attacks on-the-fly."

The UB system generates a user profile according to data about
standard operations and commands that each user follows to carry out
specific tasks.

The system is designed to detect significant deviations from
procedures followed by normal users.

While some commercially available computer security packages already
feature user-profiling, Upadhyaya noted that they are based on
"low-level" methods -- meaning they seek out deviations on the basis
of huge amounts of data, so they end up creating many false alarms.

"User modeling is computationally hard," said Upadhyaya. "Since many
of these existing systems treat this problem purely statistically, any
deviation from the norm is signaled as an anomaly, but it is often the
case that an intrusion has not occurred.

"It's a nuisance because an alarm can go off as often as every five
minutes," he said.

By contrast, the system he developed with co-authors Rankumar
Chinchani, a doctoral candidate in the UB Department of Computer
Science and Engineering, and Kevin Kwiat of the Air Force Research
Laboratory in Rome, N.Y., is based on the idea that the computation
habits of normal users generally are well-defined and that he or she
will work within those bounds.

"The normal behavior of computer users has been very well
characterized," said Upadhyaya. "Normal users stick within
well-defined parameters. Intruders or hackers, on the other hand, will
not be able to carry out their intended operations within such
well-defined parameters, and so will make the scope of his or her
activities overly permissive," said Upadhyaya. "Our system is based on
detecting that kind of behavior."

The key to the UB system's success and its "scalable" feature is that
its monitoring system operates at a high level, examining commands
that users execute to perform certain operations. This is in contrast
to the low-level monitoring that many existing packages perform, which
examine commands as basic as the ones and zeroes of which email
messages are composed.

"Our system is looking for a sequence of operations that falls within
certain 'normal' parameters," he explained.

"For example, if you want to make a document, you do certain things in
a certain order, you create the document, you use a word processing
program, you may run Spellcheck. Our system knows what to look for in
the normal sequence that is necessary to accomplish this job. Any
deviations from that are assumed to be potential cyberattacks."

The work was funded by the Air Force Research Laboratory in Rome, N.Y.

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