Neural Network (NN) has emerged over the years and has made remarkable contribution to the advancement of various fields of endeavor. The purpose of this work is to examine neural networks and their emerging applications in the field of engineering, focusing more on Controls. In this work, we have examined the various architectures of NN and the learning process. The needs for neural networks, training of neural networks, and important algorithms used in realizing neural networks have also been briefly discussed. Neural network application in control engineering has been extensively discussed, whereas its applications in electrical, civil and agricultural engineering were also examined. We concluded by identifying limitations, recent advances and promising future research directions.

Botnets have carved a niche in contemporary networking and cybersecurity due to the impact of their operations. The botnet threat continues to evolve and adapt to countermeasures as the security landscape continues to shift. As research efforts attempt to seek a deeper and robust understanding of the nature of the threat for more effective solutions, it becomes necessary to again traverse the threat landscape, and consolidate what is known so far about botnets, that future research directions could be more easily visualised. This research uses the general exploratory approach of the qualitative methodology to survey the current botnet threat landscape: Covering the typology of botnets and their owners, the structure and lifecycle of botnets, botnet attack modes and control architectures, existing countermeasure solutions and limitations, as well as the prospects of a botnet threat. The product is a consolidation of knowledge pertaining the nature of the botnet threat; which also informs future research directions into aspects of the threat landscape where work still needs to be done.

An international association advancing the multidisciplinary study of informing systems. Founded in 1998, the Informing Science Institute (ISI) is a global community of academics shaping the future of informing science.

Cloud computing, the technology that makes it possible for computing resources to be provisioned to clients / subscribers over long distances, as well as its component technology – virtualization, which makes it possible for multiple guest systems to co-reside on a single host machine and share the computing resources of the host, have both become very popular technologies that have witnessed giant improvements in the 21^st century. This is a review paper that presents an overview of the technologies of virtualization and cloud computing, tracing their history and evolution down a timeline to what they have today, and providing pointers to prospects of future advancements to virtualization and cloud computing.

Advancements in information technology have significantly enhanced productivity and efficiency through the adoption of cloud computing, yet this adoption has also introduced a spectrum of security threats. Effective cybersecurity mitigation strategies are imperative to minimize the impact on cloud infrastructure and ensure reliability. This study seeks to categorize and assess the risk levels of cybersecurity threats in cloud computing environments, providing a comprehensive characterization based on eleven major causes, including natural disasters, loss of encryption keys, unauthorized login access, and others. Using fuzzy set theory to analyze uncertainties and model threats, threats were identified, prioritized, and categorized according to their impact on cloud infrastructure. A high level of data loss was revealed in five key features, such as encryption key compromise and unauthorized login access, while a lower impact was observed in unknown cloud storage and exposure to sensitive data. Seven threat features, including encryption key loss and operating system failure, were found to significantly contribute to data breaches. In contrast, others like virtual machine sharing and impersonation, exhibited lower risk levels. A comparative analysis of threat mitigation techniques determined Spoofing, Tampering, Repudiation, Information Disclosure, Denial of Service and Elevation of Privilege (STRIDE) as the most effective methodology with a score of 59, followed by Quality Threat Modeling Methodology (QTMM) (57), Common Vulnerability Scoring System (CVSS) (51), Process for Attack Simulation and Threat Analysis (PASTA) (50), and Persona non-Grata (PnG) (47). Attack Tree and Hierarchical Threat Modeling Methodology (HTMM) each achieved 46, while Linkability, Identifiablility, Nonrepudiation, Detectability, Disclosure of Information, Unawareness and Noncompliance (LINDDUN) scored 45. These findings underscore the value of fuzzy set theory in tandem with threat modeling to categorize and assess cybersecurity risks in cloud computing. STRIDE is recommended as an effective modeling technique for cloud environments. This comprehensive analysis provides critical insights for organizations and security experts, empowering them to proactively address recurring threats and minimize disruptions to daily operations.

Cyber security is generally an extension of the traditional information technology (IT) security that is aimed at protecting systems, applications and data that exposed to a variety of forms of attack via the internet, ranging from data theft and espionage to corruption of data and denial of service attacks. There is a need for an increase in cyber security research due to losses from sabotage being experienced by nations, businesses and individuals from various cybercrime attacks. This paper takes a look at the applications digital watermarking to the process of protection in cyber space called cyber watermarking particularly focusing on theft of information (identity & credit card theft).The methodology of the research is through literature search and case study. The rest of the paper presents a brief overview of the digital watermarking and issues in cyber security.