Nickson M. Karie

Ravi Chaudhary, Reza Ryan, Nasim Ferdosian et al.

Digital forensic investigations increasingly depend on preprocessing heterogeneous network evidence from intrusion detection systems, IoT devices, and enterprise traffic logs. Incompatible schemas and timestamp formats hinder evidence correlation and timeline reconstruction, while current ad hoc approaches offer no mechanism to verify consistency across runs or analysis, creating reproducibility gaps that challenge evidence admissibility. This paper introduces a deterministic forensic preprocessing framework that converts heterogeneous network datasets into a reproducible canonical form. The framework formalises three preprocessing transformations: schema normalisation, temporal normalisation, and provenance tracking. These transformations are specified using set-theoretic definitions and supported by four theorems establishing determinism, information preservation, and provenance completeness. A chunk-based architecture provides O(c) bounded memory. Empirical evaluation across UNSW-NB15, IoT-23, and TON_IoT demonstrates 100% output consistency across repeated runs, robust temporal normalisation completeness over heterogeneous timestamp formats, and scalable performance from millions to hundreds of millions of records.

Nickson M. Karie, Craig Valli

The continued evolution in computer network technologies has seen the introduction of new paradigms like Software Defined Networking (SDN) which has altered many traditional networking principles in todays business environments. SDN has brought about unprecedented change to the way organisations plan, develop, and enact their networking technology and infrastructure strategies. However, SDN does not only offer new opportunities and abilities for organisations to redesign their entire network infrastructure but also presents a different set of issues and challenges that need to be resolved. One such challenge is the implementation of Digital Forensic Readiness (DFR) in SDN environments. This paper, therefore, examines existing literature and highlights the different issues and challenges impacting the implementation of DFR in SDN. However, the paper also goes further to offer insights on the different countermeasures that organisations can embrace to enhance their ability to respond to cybersecurity incidents as well as help them in implementing DFR in SDN environments

Victor R. Kebande, Nickson M. Karie, Richard A. Ikuesan

The phenomenon of network vigilantism is autonomously attributed to how anomalies and obscure activities from adversaries can be tracked in realtime. Needless to say, in today dynamic, virtualized, and complex network environments, it has become undeniably necessary for network administrators, analysts as well as engineers to practice network vigilantism, on traffic as well as other network events in real-time. The reason is to understand the exact security posture of an organization network environment at any given time. This is driven by the fact that modern network environments do, not only present new opportunities to organizations but also a different set of new and complex cybersecurity challenges that need to be resolved daily. The growing size, scope, complexity, and volume of networked devices in our modern network environments also makes it hard even for the most experienced network administrators to independently provide the breadth and depth of knowledge needed to oversee or diagnose complex network problems. Besides, with the growing number of Cyber Security Threats in the world today, many organizations have been forced to change the way they plan, develop and implement cybersecurity strategies as a way to reinforce their ability to respond to cybersecurity incidents. This paper, therefore, examines the relevance of RealTime Monitoring (RTM) as a supplementary security component of vigilantism in modern network environments, more especially for proper planning, preparedness, and mitigation in case of a cybersecurity incident. Additionally, this paper also investigates some of the key issues and challenges surrounding the implementation of RTM for security vigilantism in our modern network environments.

Victor R. Kebande, Nickson M. Karie, Richard Adeyemi Ikuesan et al.

The threats posed by botnets in the cyberspace continue to grow each day and it has become very hard to detect or infiltrate the cynicism of bots. This, is owing to the fact, that, the botnet developers each day, keep changing the propagation and attack techniques. Currently, most of these attacks have been centered on stealing computing energy, theft of personal information and Distributed Denial of Service (DDoS) attacks. In this paper, the authors propose a novel technique that uses the Non-Deterministic Polynomial-Time Hardness (NP-Hard Problem) based on the Traveling Salesperson Person (TSP) that depicts that a given bot, bj, is able to visit each host on a network environment, NE, and then it returns to the botmaster, in form of instruction(command), through optimal minimization of the hosts that are (may) be attacked. Given that bj represents a piece of malicious code and TSP-NP Hard Problem, which forms part of combinatorial optimization, the authors present this as an effective approach for the detection of the botnet. It is worth noting that the concentration of this study is basically on the centralized botnet architecture. This holistic approach shows that botnet detection accuracy can be increased with a degree of certainty and potentially decrease the chances of false positives. Nevertheless, a discussion on the possible applicability and implementation has also been given in this paper.