Unit 4640: Advanced Topics in Computing and Security

1. Cryptography and Network Security

1.1 Introduction to Cryptography

• Symmetric vs Asymmetric encryption
• Historical context and evolution

1.2 Encryption Algorithms

• Advanced Encryption Standard (AES)
• RSA algorithm
• Elliptic Curve Cryptography (ECC)

1.3 Digital Signatures and Hash Functions

• Purpose and implementation
• Common hash algorithms (SHA family)

1.4 Public Key Infrastructure (PKI)

• Certificates and certificate authorities
• Trust models

1.5 Secure Communication Protocols

• SSL/TLS
• IPsec
• Secure Shell (SSH)

2. Cloud Computing and Virtualization

2.1 Fundamentals of Cloud Computing

• Definition and characteristics
• Deployment models: public, private, hybrid

2.2 Virtualization Technologies

• Hypervisors: Type 1 and Type 2
• Containerization (Docker, Kubernetes basics)

2.3 Cloud Service Models

• Infrastructure as a Service (IaaS)
• Platform as a Service (PaaS)
• Software as a Service (SaaS)

2.4 Benefits and Challenges

• Scalability, cost-effectiveness
• Security and compliance concerns

3. Big Data Analytics

3.1 Overview of Big Data

• Characteristics: Volume, Velocity, Variety, Veracity

3.2 Tools and Technologies

• Hadoop ecosystem
• Apache Spark

3.3 Data Mining and Machine Learning

• Supervised vs unsupervised learning
• Common algorithms

3.4 Predictive Analytics

• Techniques and applications

3.5 Data Visualization

• Principles and tools (Tableau, Power BI)

4. Internet of Things (IoT) and Cyber-Physical Systems

4.1 IoT Architectures

• Layered IoT architecture
• Sensor networks and communication protocols

4.2 Integration with Cyber-Physical Systems

• Definition and components
• Real-time control and monitoring

4.3 IoT Security Challenges

• Threat vectors
• Security frameworks and best practices

4.4 Applications

• Smart cities
• Industrial IoT (IIoT)

5. Artificial Intelligence and Machine Learning

5.1 Introduction to AI

• Definition and history

5.2 Neural Networks and Deep Learning

• Architecture and training
• Convolutional Neural Networks (CNNs)

5.3 Natural Language Processing (NLP)

• Text processing and sentiment analysis

5.4 Computer Vision

• Image recognition and applications

5.5 AI Ethics

• Bias, privacy, and societal impact

6. Blockchain Technology

6.1 Fundamentals of Blockchain

• Decentralized ledger concept
• Consensus mechanisms (Proof of Work, Proof of Stake)

6.2 Smart Contracts

• Definition and operational principles

6.3 Cryptocurrencies

• Bitcoin, Ethereum overview

6.4 Applications Beyond Finance

• Healthcare
• Supply chain management

7. Ethical Hacking and Penetration Testing

7.1 Ethical Hacking Fundamentals

• Roles and responsibilities
• Legal and ethical considerations

7.2 Penetration Testing Methodologies

• Reconnaissance
• Scanning and enumeration
• Exploitation

7.3 Vulnerability Assessment

• Tools and techniques

7.4 Social Engineering

• Techniques and defense strategies

7.5 Securing Systems

• Best practices and mitigation strategies