Discovery of Malicious Attacks to Improve Mobile Collaborative Learning (MCL)
Abdul Razaque, Khaled Elleithy

TL;DR
This paper presents a novel intrusion detection system that detects and blocks rogue DHCP attacks in mobile collaborative learning environments, enhancing security and user privacy.
Contribution
It introduces a multi-frame signature-cum anomaly-based IDS with new algorithms and rules specifically designed to counter rogue DHCP attacks in MCL networks.
Findings
Effective detection of rogue DHCP attacks demonstrated
Improved network security and user privacy confirmed
Performance surpasses existing intrusion detection methods
Abstract
Mobile collaborative learning (MCL) is highly acknowledged and focusing paradigm in eductional institutions and several organizations across the world. It exhibits intellectual synergy of various combined minds to handle the problem and stimulate the social activity of mutual understanding. To improve and foster the baseline of MCL, several supporting architectures, frameworks including number of the mobile applications have been introduced. Limited research was reported that particularly focuses to enhance the security of those pardigms and provide secure MCL to users. The paper handles the issue of rogue DHCP server that affects and disrupts the network resources during the MCL. The rogue DHCP is unauthorized server that releases the incorrect IP address to users and sniffs the traffic illegally. The contribution specially provides the privacy to users and enhances the security…
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Taxonomy
TopicsNetwork Security and Intrusion Detection · Advanced Malware Detection Techniques · Spam and Phishing Detection
