AI Assisted Decision Making of Security Review Needs for New Features

Overview

Explore AI-assisted decision-making for identifying security review needs in new features, addressing challenges in modern SDLC and improving security oversight in fast-paced development environments.

Syllabus

• Introduction to AI in Software Development
Overview of AI applications in the SDLC
Importance of AI in security reviews
• Fundamentals of Security in Software Development
Basic principles of software security
Common security vulnerabilities and their impact
• AI Algorithms and Models for Decision Making
Overview of machine learning models
Decision trees, neural networks, and ensemble methods
• Identifying Security Review Needs
Criteria for determining security review necessity
Risk assessment and prioritization
• Designing AI Systems for Security Analysis
Integrating AI tools in the SDLC
Data collection and preparation for AI models
• AI-Assisted Security Review Process
Workflow of AI-assisted security decision-making
Continuous monitoring and feedback loops
• Case Studies and Practical Applications
Real-world examples of AI in security reviews
Lessons learned from industry applications
• Challenges and Limitations of AI in Security
Common pitfalls in AI-assisted decision-making
Addressing bias and ensuring fairness in models
• Future Trends in AI for Security and Development
Emerging technologies and their potential impact
Evolving standards and best practices
• Capstone Project
Apply learned concepts to a mock feature release
Conduct AI-assisted security review and present findings

Subjects

Conference Talks