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The development of e-assessment systems that can meet acceptable standards in the education industry is a present focus of researchers in the distance learning area. Cheating and impersonation in online examinations are two common challenges that have spawned diverse solutions that are usually based on continuous authentication and monitoring principles and technologies. Most of the solutions are focused on centralized e-proctoring schemes that depend massively on state-of the-art internet connectivity. However, many users of these systems, especially in the developing countries, have limited internet services. This is a major barrier to effective remote e-assessment of learners as many of these solutions fail with failing internet services. To resolve this challenge, this paper describes a Secure Offline Continuous Authentication and Monitoring(SOCAM) model for remote e-assessment.

Intrusion Detection Systems (IDSs) are an integral part of an organization's infrastructure. Without an IDS facility in place to monitor network and host activities, attempted and successful intrusion attempts may go unnoticed. This study proposed a Collaborative Knowledge Repository Architecture for Intrusion Detection (CK-RAID). It is based on a distributed network of computer nodes, each with their individual IDS with a centralized knowledge repository system, and firewall acting as a defence. When an unfamiliar attack hits any node, the first step the intrusion monitor takes is to request from Knowledge Repository Server the most effective intrusion response. To improve performance, Intrusion Update module collaborates with IDSs sensor and log by updating their expert rule and intrusion information respectively and removing the old intrusion signature from the knowledge base with the aid of Intrusion Detector Pruning. To ensure security of information exchange, RSA encryption and Digital Signature were used to encode information during transit. The result showed that CK-RAID had a detection rate of 97.2%, compared with Medoid Clustering, Y-means, FCM and K-means that have an accuracy of 96.38%, 87.15%, 82.13% and 77.25% respectively. Therefore, CK-RAID can be deployed for efficient detection of all categories of intrusion detection and response. [ABSTRACT FROM AUTHOR]

Intrusion Detection Systems (IDS) is defined as a component that analyses system and user operations in computer and network systems in search of activities considered undesirable from security perspectives. Applying mobile agent (MA) to intrusion detection design is a recent development and it is aimed at effective intrusion detection in distributed environment. From the literature, it is clear that most MA-based IDS that are available are not quite effective because their time to detection is high and detect limited intrusions. This paper proposes a way of classifying a typical IDS and then strategically reviews the existing mobile agent-based IDSs focusing on each of the categories of the classification, for example architecture, mode of data collection, the techniques for analysis, and the security of these intelligent codes. Their strengths and problems are stated wherever applicable. Furthermore, suggested ways of improving on current MA-IDS designs are presented in order to achieve an efficient mobile agent-based IDS for future security of distributed network. [ABSTRACT FROM AUTHOR]