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Security Data Analytics

(WU-SEC6050.AV1)
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1

Business Analytics and Emerging Cybersecurity Challenges

  • Traditional Learning Methods in Business Analytics
  • Emerging Learning Methods in Business Analytics
  • Case Studies and Practical Applications in Business Analytics Learning
  • Assessment and Evaluation of Learning Methods in Business Analytics
  • Technologies Adapted
  • Future Trends and Innovations in Learning Methods for Business Analytics
  • Results
  • The Evolving Impact of Cyber security
  • Regulatory and Compliance Issues
  • Cyber security for Small and Medium-Sized Enterprises
  • The Future of Cyber security
  • Literature Review
  • Research Methodology
  • Findings and Discussion
  • Recommendations
2

Business Models and Proactive Cybersecurity for Real-Time Protection

  • New Types of Cyber Threats Expected to Emerge in 6G
  • The Cost of Cyber Attacks
  • Theoretical Foundations in Cyber security for Future Business Models
  • Fundamentals of Knowledge Representation
  • Business Model Frameworks
  • Hybrid Model
  • Reactive versus Proactive
  • The Best Practices for Implementing Proactive Security Methodologies
  • Strengths and Weaknesses
3

Incident Management in Modern Organizations with a Focus on Issues and Challenges in E-Banking

  • The Concept of Incident Management
  • Incident Management Process
  • Benefits of Effective Incident Management
  • Challenges and Barriers to Successful Incident Management
  • Best Practices in Incident Management
  • Incident Management Tools and Technologies
  • Incident Management in Different Industry Sectors
  • Results
  • Security Concern
  • Technical Infrastructure and Reliability
  • Customer Service and User Experience
  • Regulatory Compliance and Legal Challenges
  • Fraudulent Activities
  • Adoption Barriers for Certain Demographics
  • Integration with Third-Party Services
  • Data Privacy and Protection
4

Cybersecurity and Privacy-Preserving Techniques for Machine Learning in Business Big Data

  • Overview of ML in Business
  • Types of Business Data Leveraging ML
  • Importance of Securing Business Data in ML Systems
  • Cyber security Challenges in ML
  • Data Privacy Concerns in Business ML Applications
  • Vulnerabilities in ML Pipelines
  • Adversarial Attacks (Poisoning, Evasion, and Inference Attacks)
  • Data Breaches in Business Context
  • Examples of Attacks and Defenses in Real-World Business Scenarios
  • Advancements in Secure ML Techniques
  • Importance of Data Privacy
  • Role of ML and DL
  • Privacy Concerns in Business Big Data
  • Privacy-Preserving Techniques in ML
  • DL Techniques for Privacy Preservation
  • Metrics for Privacy Preservation
  • Data Privacy Concerns in Business ML Applications
  • Vulnerabilities in ML Pipelines
  • Data Breaches in Business Context
5

Navigating Cyber Security Tools - A Comprehensive Guide from Entry to Expert Level

  • Tool Documentation
6

Cybersecurity in African E-Commerce and Smarter Personalization for User Engagement

  • Literature Review of Cyber Security in Africa
  • Cyber security Solutions Based on African Indigenous Technologies for E-Commerce
  • Importance of Business Analytics in Cyber security
  • Cyber security, Challenges, and Solutions
  • Solutions and Best Practices of Implementing Cyber security in E-commerce in Africa
  • Challenges and Future Directions
  • Literature Survey
  • Proposed System
  • Results and Discussion

1

Business Analytics and Emerging Cybersecurity Challenges

  • Creating a Data Visualization Dashboard with R Shiny
  • Simulating a DoS Attack
  • Performing SQL Injection
  • Encrypting Data Using AES and RSA
2

Business Models and Proactive Cybersecurity for Real-Time Protection

  • Implementing Reactive Cybersecurity Measures
3

Navigating Cyber Security Tools - A Comprehensive Guide from Entry to Expert Level

  • Identifying Open Ports and Services Using Metasploit
  • Performing Digital Forensics Using Autopsy
  • Performing a Phishing Attack Using the SET Tool
  • Capturing Packets Using Wireshark
  • Performing Data Mining Using Maltego
4

Cybersecurity in African E-Commerce and Smarter Personalization for User Engagement

  • Segmenting Customers Using Clustering Techniques

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