Statistical decision making for authentication and intrusion detection
Paper in proceedings, 2009

User authentication and intrusion detection differ from standard classification problems in that while we have data generated from legitimate users, impostor or intrusion data is scarce or non-existent. We review existing techniques for dealing with this problem and propose a novel alternative based on a principled statistical decision-making view point. We examine the technique on a toy problem and validate it on complex real-world data from an RFID based access control system. The results indicate that it can significantly outperform the classical world model approach. The method could be more generally useful in other decision-making scenarios where there is a lack of adversary data. © 2009 IEEE.

Author

Christos Dimitrakakis

Chalmers, Computer Science and Engineering (Chalmers), Computing Science (Chalmers)

Aikaterini Mitrokotsa

Chalmers, Computer Science and Engineering (Chalmers), Networks and Systems (Chalmers)

8th International Conference on Machine Learning and Applications, ICMLA 2009

409-414

Areas of Advance

Information and Communication Technology

Subject Categories

Mathematics

Computer and Information Science

DOI

10.1109/ICMLA.2009.46

More information

Created

10/6/2017