Course Gaps at Kaduna State University

Introduction to biometrics and digital image processing. Matlab in biometric image/signal processing. Biometric algorithms and systems with emphasis on face, fingerprint, eyes (iris), speech (voice). Automated biometric identification multimodal biometrics. Biometric data: raw data, template data, and data methods. Biometric matching basics: biometric authentication, enrolment, correct user, and incorrect user. Match threshold and matching performance. Setting a threshold. Biometric authentication: matching data, ground truth, calculating errors rates and graphs. Biometric data: Storage of biometric data elements, transactions, errors and quality upgrades. Data security and integrity. Privacy issues and other aspects of biometrics. Applications of biometrics and future trends. Challenging issues: security strength and recognition rates. Alternatives of passwords and smart cards. Lab work: Practical exercise on biometric capture, image processing, matching threshold and performance. Learn the practical aspect of automated biometric identification of multimodal, authentication and calculation of error rates. Work on biometric algorithms, privacy and security of stored biometric data.

Introduction to cloud computing, cloud computing vendors, cloud computing threats, cloud reference model. Cloud-enabling technologies. Services, Service-Oriented Architectures. Cloud service models. Cloud deployment models. Introduction to data centres: servers, data storage, networking and virtualisation. Data centre networking. Introduction to server virtualisation software: VMware VSphere. Virtual machine management: configuration, placement and resource allocation. Power efficiency in virtual data centres. Fault tolerance in virtual data centres. The cloud cube model and security for cloud computing. Security in the cloud. Cloud threats, threat mitigation and security risks. Real world issues with cloud computing. Cloud security alliance. National Institute of Standards and Technology, Information Assurance Framework. Cloud audit. Cloud management audit/assurance programme, Cloud business continuity planning. Building a cloud. Architectural best practices: Designing for the cloud. Economics of the cloud. Cloud strategy. Cloud standards and the future. Security of the cloud.

Techniques for detecting, responding to and defeating organised cybercrimes and cyberwar activities. Analysing successful and unsuccessful advanced persistent threats and malware campaigns. Analyse divergent national and international policies for combating cyber terrorism and terrorist tactics worldwide. Understanding Cyber threat intelligence - defining threats, Understanding risk, Cyber threat intelligence and its rule, Expectations of organisations and analysts, and indicators of compromise. Tactical threat intelligence. Role of a tactical threat intelligence analyst, expected skills and tradecraft. The Kill Chain and Intrusion Analysis. Indicator lifecycle. Introduction to operational threat intelligence - Role of an operational threat intelligence analyst, Need for information sharing and peers. Models and methods for managing intelligence, campaigns and threat actors. Introduction to strategic threat Intelligence - role of a strategic threat intelligence analyst. Threat modelling, Organisational change and security posturing. Event recording and incident sharing. Evolution of counterterrorism and cyber conflict.

Introduction to digital forensics, digital evidence, and increasing awareness of digital evidence. Challenging aspects of digital evidence. Best practices in securing, processing, acquiring, examining and reporting on digital evidence. Cyber trail and challenging aspects of the cyber trail. Brief history of computer crime and cybercrime investigation. Cyber auditing. Evolution of investigative tools. Language of computer crime investigation. The role of computers in crime, technology and law, jurisdiction, pornography and obscenity, child pornography, privacy, copyrights and the “theft” of digital intellectual property. The investigative process and investigative reconstruction, with digital evidence. Examine techniques and tools used by computer forensics investigations such as acquisition, preservation, recovery, and analysis of evidence obtained from portable and stationary computer storage devices, personal digital assistants (PDAs), and cell phones. Current technologies and methods as well as leading edge techniques with practical based exercises/projects and research opportunities. Lab work: Practical exercises on how to make use of various techniques and tools for computer forensics investigations and cyber trail during cybercrime investigations. Practice cyber auditing skills. Work on applying the best practices in securing, processing, acquiring, examining and reporting on digital evidence with current technologies and methods in forensics investigation.