List of Papers Under Consideration

See course homepage for papers selected to date.

Intrusion Detection

For a quick background on intrusion detection, see: Stefan Axelsson, Intrusion Detection Systems: A Taxomomy and Survey, Technical Report No 99-15, Dept. of Computer Engineering, Chalmers University of Technology, Sweden, March 2000.

    Papers:
  1. http://www.zurich.ibm.com/pub/Other/RAID/Prog_RAID98/Table_of_content.html
  2. A Intrusion Detection in Real-Time Database Systems via Time Signatures Victor C. S. Lee, City University of Hong Kong John A. Stankovic and Sang H. Son , University of Virginia Proceedings of the Sixth IEEE Real Time Technology and Applications Symposium (RTAS 200
  3. http://www.mitre.org/support/papers/tech_papers_01/bloedorn_datamining/index.shtml
  • Clustering
    2. Intrusion detection with unlabeled data using clustering Leonid Portnoy, Elezar Eskin, Sal Stolfo Workshop on Data Mining for Security ApplicationsIntrusion detection with unlabeled data using clustering Leonid Portnoy, Elezar Eskin, Sal Stolfo Workshop on Data Mining for Security Applications
  • Analysis
    1. "Data Mining Methods for Detection of New Malicious Executables" http://www.cs.columbia.edu/ids/publications/binaryeval-ieeesp01.pdf
    2. Christoph Michael, Anup K. Ghosh: Using Finite Automata to Mine Execution Data for Intrusion Detection: A Preliminary Report. 66-79 http://link.springer.de/link/service/series/0558/bibs/1907/19070066.htm
    3. Anup K. Ghosh, Aaron Schwartzbard: Analyzing the Performance of Program Behavior Profiling for Intrusion Detection. 19-32
    4. DBSec'99
      Ravi Mukkamala, Jason Gagnon, Sushil Jajodia: Integrating Data Mining Techniques with Intrusion Detection Methods. 33-46

    • Suggestion from Murat Kantarcioglu:
    Finding Interesting Associations without Support Pruning Cohen, Datar, Fujiwara, Gionis, Indyk, Motwani, Ullman, Yang

    Preventing Inference

    2. Chris Clifton and Don Marks, ``Security and Privacy Implications of Data Mining'', ACM SIGMOD Workshop on Data Mining and Knowledge Discovery, Montreal, Canada, June 2, 1996.
    3. T. D. Johnsten and V. V. Raghavan. Impact of decision-region based classification mining algorithms on database security. In V. Atluri and J. Hale, editors, Research Advances in Database and Information Systems Security, pages 171--191. Kluwer Academic, Norwell, MA, 2000.
      DBSec'01: Security Procedures for Classification Mining Algorithms Tom Johnsten, Vijay V. Raghavan
    4. Clifton, JCS

    Other

    1. Incremental Clustering and Dynamic Information Retrieval Moses Charikar, Chandra Chekuri, Tomas Feder, Rajeev Motwani
    2. Incremental Document Clustering for Web Page Classification. Wai-chiu Wong Adsa Wai-chee Fu
    3. Multi-Topic E-mail Authorship Attribution Forensics O. de Vel, A. Anderson, M. Corney, G. Mohay Workshop on Data Mining for Security Applications
    4. Brodley/Lane profiling users based on command histories.
    5. Hale's papers: http://www.mcs.utulsa.edu/~hale/papers.html