Special Session on on Machine Learning for
                                 Computer Security

The demand for networked consumer systems and devices is large and growing rapidly. As computers have become more 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.

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.

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
♦Analyzing recently detected attacks
♦Responding to attacks
♦Predicting attacker actions and goals
♦Performing forensic analysis of compromised systems
♦Analyzing activities

Submission Instructions

Authors are invited to submit regular technical papers or position papers. The position papers should present novel technologies at an early stage of development or share future vision. All submissions should describe original, previously unpublished research, not currently under review by another conference or journal. Manuscripts should not exceed five (5) pages in double-column IEEE format. Please submit the paper through   EDAS.  Formatting details can be found under   Author Information on the CCNC web site.

Session Organizers

Dr. Afrand Agah  aagah@wcupa.edu, Computer Science department at West Chester University of Pennsylvania

Dr. Mehran Asadi  masadi@wcupa.edu, Computer Science department at West Chester University of Pennsylvania