Unit 1 Access Control Knowledge Assessment скачать в хорошем качестве

Unit 1 Access Control Knowledge Assessment

🔐 Level 3 Networking & Cybersecurity — Unit 001 Access Control | Learning Session This session introduces Access Control, a core component of cybersecurity designed to protect systems, data, and organisational assets from unauthorised access. Learners will explore how identity, authentication, and authorisation work together to maintain secure and productive environments across modern organisations. This lesson supports the development of technical knowledge, analytical thinking, and practical implementation skills aligned with industry expectations within networking and cybersecurity roles. 🎯 What You Will Learn ✅ The purpose of access control within organisations and how it protects confidentiality, integrity, and availability (CIA Triad). ✅ Primary security control categories including preventative, detective, corrective, deterrent, recovery, and compensating controls. ✅ Understanding Defence in Depth strategies and layered cybersecurity protection approaches supported by guidance from organisations such as Fortinet. ✅ Methods used to limit access to systems and sensitive data to reduce insider threats and cyberattacks. ⏱ Suggested Chapters 00:00 Introduction to Access Control 04:30 CIA Triad Explained 09:00 Primary Security Control Categories 15:00 Physical, Logical & Administrative Controls 22:00 Access Control Techniques & Case Studies 30:00 Identity Management & Authentication 36:00 Restricting vs Enabling Access 42:00 Threats & Vulnerabilities 50:00 Practical Authentication Implementation 56:00 Assessment Guidance & Progress Tracking #CyberSecurity #NetworkingCourse #AccessControl #Level3IT #CyberSecurityTraining #DigitalSkills #EthicalHacking #NetworkSecurity #AdultLearning #UKEducation #CiscoNetworking #cyberawareness Level 3 Networking and Cybersecurity, Access Control Unit 001, CIA Triad, Defence in Depth Strategy, Identity Management, Authentication Methods, Cybersecurity Threat Awareness, Network Simulation Learning