Multi-frame Signature-cum Anomaly-based Intrusion Detection Systems (MSAIDS) to Protect Privacy of Users over Mobile Collaborative Learning (MCL)

TL;DR

This paper proposes MSAIDS, a multi-frame signature and anomaly-based intrusion detection system, to detect rogue DHCP attacks, enhance user privacy, and improve security in mobile collaborative learning environments.

Contribution

It introduces novel algorithms and rules for IDS to specifically detect rogue DHCP servers, strengthening security and privacy in mobile collaborative frameworks.

Findings

Effective detection of rogue DHCP attacks

Enhanced user privacy and network security

Validated through simulation and comparison with existing methods

Abstract

The rogue DHCP is unauthorized server that releases the incorrect IP address to users and sniffs the traffic illegally. The contribution specially provides privacy to users and enhances the security aspects of mobile supported collaborative framework (MSCF) explained in [24].The paper introduces multi-frame signature-cum anomaly-based intrusion detection systems (MSAIDS) supported with novel algorithms and inclusion of new rules in existing IDS. The major target of contribution is to detect the malicious attacks and blocks the illegal activities of rogue DHCP server. This innovative security mechanism reinforces the confidence of users, protects network from illicit intervention and restore the privacy of users. Finally, the paper validates the idea through simulation and compares the findings with known existing techniques.