Advanced Cybersecurity Applications: Solutions to Counteract Cyber Threats

The papers in this Reprint cover a number of topics related to cybersecurity threats. Academic researchers and policy makers will find the topics of interest because cybersecurity solutions involve intra-organizational and inter-organizational decision-making and human-technology interaction that is focused on enhancing cybersecurity. The topics covered include challenges confronting local government and the way local government representatives can view policy in relation to the cybersecurity challenges faced. Cybersecurity vulnerabilities in relation to IT infrastructure are considered, and attention is given to digital transformation and network expansion. A hybrid ensemble learning-based intrusion detection framework for integrating deep learning and ML algorithms vis-à-vis real-time cybersecurity applications is featured. Reference is made to traditional security techniques for lending systems and security in blockchain-based lending systems. Insight is provided into network theory in the context of power-physical cross-domain attack paths, and reference is made to a cascading failure analysis. The limitations of existing security frameworks are featured, and multi-level security models are given attention. An APT malware detection model is highlighted to enhance local semantic representations, and two models are referred to. A systematic investigation into vulnerabilities of event-based person Re-ID models is provided. There is also a paper that addresses threat hunting in relation to healthcare, and the design of a threat-hunting platform is referenced.