REMINDER [Nrg-l] NRG on Monday November 1st MCS135@4:00pm

Niky Riga inki at cs.bu.edu
Mon Nov 1 09:12:03 EST 2004


Hi evryone,
Just a reminder that NRG is today at 4:00pm at MCS135.


Niky
Niky Riga wrote:

> 
> Hi,
> Next week, NRG will be hosting Jaeyeon Jung. She is a Ph.D. student at 
> MIT, working at the Computer Science and Artificial Intellegence 
> Laboratory. She is working on Network Security issues. The title and 
> abstract of the talk follow. If someone wants to meet with her (either 
> 1-on-1 or in a group), please let me know.
> 
> Regards,
> Niky
> 
> ====================================================================
> 
> Title: Threshold Random Walk: its theory and applications to portscan
> detection and fast detection of scanning worm infections.
> 
> Papers are linked at http://nms.lcs.mit.edu/~jyjung/
> 
> Speaker: Jaeyeon Jung (Ph.D. student at MIT Computer Science and
> Artificial Intelligence Laboratory)
> 
> Abstract:
> Attackers routinely perform random "portscans" of IP addresses to find
> vulnerable servers to compromise. Network Intrusion Detection Systems 
> (NIDS)
> attempt to detect such behavior and flag these portscanners as 
> malicious. An
> important need in such systems is  prompt response: the sooner a NIDS 
> detects malice,
> the lower the resulting damage. At the same time, a NIDS should not 
> falsely implicate
> benign remote hosts as malicious. Balancing the goals of promptness and 
> accuracy
> in detecting malicious scanners is a delicate and difficult task. We 
> develop a
> connection between this problem and the theory of sequential hypothesis 
> testing
> and show that one can model accesses to local IP addresses as a random 
> walk on
> one of two stochastic processes, corresponding respectively to the 
> access patterns
> of benign remote hosts and malicious ones. The detection problem then 
> becomes one
> of observing a particular trajectory and inferring from it the most likely
> classification for the remote host. We use this insight to develop TRW
> (Threshold Random Walk), an on-line detection algorithm that identifies 
> malicious
> remote hosts. Using an analysis of traces from two qualitatively 
> different sites,
> we show that TRW requires a much smaller number of connection attempts
> (4 or 5 in practice) to detect malicious activity compared to previous
> schemes, while also providing theoretical bounds on the low (and 
> configurable)
> probabilities of missed detection and false alarms. In summary, TRW 
> performs
> significantly faster and also more accurately than other current solutions.

-- 
Use a smile as your shield. It will protect u better than cruelty in 
return will.


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