Computational intelligence-enabled cybersecurity for the Internet of Things

The computational intelligence (CI) based technologies play key roles in campaigning cybersecurity challenges in complex systems such as the Internet of Things (IoT), cyber-physical-systems (CPS), etc. The current IoT is facing increasingly security issues, such as vulnerabilities of IoT systems, malware detection, data security concerns, personal and public physical safety risk, privacy issues, data storage management following the exponential growth of IoT devices. This work aims at investigating the applicability of computational intelligence techniques in cybersecurity for IoT, including CI-enabled cybersecurity and privacy solutions, cyber defense technologies, intrusion detection techniques, and data security in IoT. This paper also attempts to provide new research directions and trends for the increasingly IoT security issues using computational intelligence technologies

Cognitive modelling of language acquisition with complex networks

ABSTRACT Cognitive modelling is a well-established computational intelligence tool, which is very useful for studying cognitive phenomena, such as young children's first language acquisition. Specifically, linguistic modelling has recently benefited greatly from complex network theory by modelling large sets of empirical linguistic data as complex networks, thereby illuminating interesting new patterns and trends. In this chapter, we show how simple network analysis techniques can be applied to the study of language acquisition, and we argue that they reveal otherwise hidden information. We also note that a key network parameter -the ranked frequency distribution of the links -provides useful knowledge about the data, even though it had been previously neglected in this domain

The Need for Concerted Efforts for COVID-19 Intelligence Gathering: Medical Espionage and Cyber Crime Trends Analysis to Strengthen the UK's Pandemic Response

An important knowledge gap that needs bridging is the extent to which current natural language processing (NLP) tools, models and resources can be successfully applied to exploring a specific aspect of dark-web data such as COVID-19-related communication. It is imperative to support law enforcement in gathering intelligence on the new COVID-19-related cybercrime strategies in the DW. The research gap around the DW search and textual analysis consists in the lack of robust mechanisms for querying, processing and monitoring trends on the DW. The critical data sets and computational solutions need to be made available for immediate exploitation and further research to strengthen the UK’s pandemic response