G-NAS: A grid-based approach for negative authentication


Surveys show that more than 80% authentication systems are password based and these systems are increasingly under direct and indirect attacks. In an effort to protect the Positive Authentication System (PAS), the negative authentication concept was introduced [9]. Here, the representation space of password profile is called self-region; any element outside this self-region is defined as the non-self-region. Then anti-password detectors (clusters) are generated covering most of the non-self-region while leaving some space uncovered to reduce detector generation time and obfuscation. In this work, we investigate a Grid-based NAS approach, called G-NAS, where anti-password detectors are generated deterministically. This approach allows faster detector generation compared to previous NAS approaches. We reported some experimental results of G-NAS using different real-world password datasets. Results demonstrate the efficiency of the proposed approach and exhibited significant improvements compared to NAS approaches. It appears to be more robust and scalable with respect to the size of password profiles and able to update of detector sets on-the-fly.

Publication Title

IEEE SSCI 2014: 2014 IEEE Symposium Series on Computational Intelligence - CICS 2014: 2014 IEEE Symposium on Computational Intelligence in Cyber Security, Proceedings