Secure Implementation with AI

Learning Objective – The goal of this module is to use AI for secure implementation of an application, which the engineers can use for secure application development and speeding up the operation in various stages of Software development lifecycle.

Audience – Any intermediate level professional in cybersecurity/software development/solutions architecture/devsecops.

Pre-Requisite: Prerequisites for understanding AI in cybersecurity encompass fundamental knowledge in Artificial Intelligence (AI), including Machine Learning (ML), Deep Learning (DL), Natural Language Processing (NLP), and Computer Vision. Additionally, familiarity with Large Language Models (LLMs), covering their definition, significance, evolution, and applications across various domains like Natural Language Understanding, Text Generation, Conversational Agents, and Information Retrieval, is essential. Understanding the synergy between Cybersecurity and AI involves leveraging AI for automating security policies, reporting, and detecting common security flaws such as anomalies in user behavior, unauthorized access attempts, cryptographic key management, and weaknesses in cryptographic implementations. Furthermore, integrating AI into the Secure Software Development Lifecycle (SDLC) for automated security testing, code review, and vulnerability management is crucial. Finally, to apply LLMs effectively in cybersecurity, one needs to grasp their utility in enhancing security knowledge through common prompts and leveraging automation tools like GenAI.

Understanding AI for building secure design (4 hours)

· Gathering security requirements

· Determining organization’s assets

· Building a secure design with help of AI

Using AI for Secure implementation (8 hours)

· Learn about common insecure code practices.

· AI for securing the written code.

· Use AI for using secure technologies.

User Authentication and Authorization (4 hours)

· Implementing strong authentication and authorization mechanisms safeguards AI systems from unauthorized access.

· Techniques such as multi-factor authentication,

· Role-based access control, and

· least privilege principle help enforce access control policies and prevent unauthorized usage.

Using AI for Secure testing (8 hours)

· Learn about common insecure code practices.

· AI for securing the written code.

· Use AI for using secure technologies.

Using AI for Dev-Sec-ops (8 hours)

· Automated code analysis

· Secure pipeline and repositories

· Access management

Using AI Powered security solutions (8 hours)

· AI-powered web application firewalls

· Monitoring cloud environments

· AI-powered endpoint protection solutions