Published Papers: http://jmlr.csail.mit.edu/papers/topic/ml_sec.html
Call For Papers
As computers have become more ubiquitous and connected, their security
has become a major concern. Of interest to this special issue is
research that demonstrates how machine learning (or data mining)
techniques can be used to improve computer security. This includes
efforts directed at improving security of networks, hosts, and
individual applications or computer programs. Research can have many
goals including, but not limited to, authenticating users,
characterizing the system being protected, detecting known or unknown
vulnerabilities that could be exploited, using software repositories
as training data to find software bugs, preventing attacks, detecting
known and novel attacks when they occur, analyzing recently detected
attacks, responding to attacks, predicting attacker actions and goals,
performing forensic analysis of compromised systems, and analyzing
activities seen in honey pots and network "telescopes" or "black
Of special interest are studies that use machine learning techniques,
carefully describe their approach, evaluate performance in a realistic
environment, and compare performance to existing accepted
approaches. Studies that use machine learning techniques or extend
current techniques to address difficult security-related problems are
of most interest.
It is expected that studies will have to address many classic machine
learning issues including feature selection, feature construction,
incremental/online learning, noise in the data, skewed data
distributions, distributed learning, correlating multiple models, and
efficient processing of large amounts of data.
Important Dates: (expired)
- Philip Chan, Florida Tech [pkc AT cs DOT fit DOT edu]
- Richard Lippmann, MIT Lincoln Lab [lippmann AT ll DOT mit DOT edu]
- Philip Chan, Florida Tech
- Wei Fan, IBM Watson Research Center
- Anup Ghosh, DARPA
- Tom Goldring, NSA
- Sushil Jajodia, George Mason Univ.
- Chris Kruegel, Technical University Vienna
- Vipin Kumar, Univ. of Minnesota
- Terran Lane, Univ. of New Mexico
- Wenke Lee, Georgia Tech
- Richard Lippmann, MIT Lincoln Lab
- Matthew Mahoney, Florida Tech
- Roy Maxion, Carnegie Mellon Univ.
- Chris Michael, Cigital
- Srinivasan Parthasarathy, Ohio State Univ.
- R. Sekar, Stony Brook Univ.
- Jude Shavlik, Univ. of Wisconsin
- Marius Silaghi, Florida Tech
- Salvatore Stolfo, Columbia Univ.
- Alfonso Valdes, SRI