CSIT375 AI for Cybersecurity Overview

Introduction to CSIT375 AI for Cybersecurity

• Course conducted by Dr. Manoj Kumar and Dr. Chen Chen at SOCS, University of Wollongong in Dubai.
• Presentation materials derived from multiple sources.

What is AI?

• Artificial Intelligence (AI) refers to machine-driven decision-making that mimics human reasoning.
• AI has progressed rapidly, impacting numerous sectors like finance, workplace compliance, and security.
• Key applications include stock price prediction, anomaly detection, risk assessment, and self-driving technology.

AI Characteristics

• AI systems process input and generate outputs based on learned behavior.
• Examples include:
  • Computer Vision: Translates visual input (pixels) into actions or descriptions.
  • Speech Recognition: Interprets audio clips and generates responses.
  • Machine Translation: Converts text from one language to another.
• Neural networks, a subfield of AI, emulate human brain processes, aiding in data interpretation and learning.

Definitions in AI

• Artificial Intelligence (AI): Creation of intelligent machines.
• Machine Learning (ML): A branch of AI utilizing data to enhance applications.
• Deep Learning (DL): A subset of ML that employs deep neural networks for model training with large datasets.

What is Cybersecurity?

• Cybersecurity encompasses technologies and practices to safeguard networks, systems, and data from unauthorized access and attacks.
• Major goals include:
  • Confidentiality: Preventing unauthorized information disclosure.
  • Integrity: Avoiding unauthorized information modification.
  • Availability: Ensuring information and systems are accessibly secure.

Cybersecurity Components

• Effective cybersecurity requires integration of people, processes, and technology.
• Users must adhere to data security principles, while processes establish response frameworks for cyber incidents.
• Technological tools include firewalls, antivirus software, and malware protections.

Common Cybersecurity Threats

• Phishing: Deceptive emails that act as trusted sources to harvest personal data.
• Ransomware: Locks files until a ransom is paid.
• Malware: Malicious software that damages or gains unchecked access to systems.
• Social Engineering: Manipulating individuals into revealing confidential information.

Role of AI in Cybersecurity

• AI and ML are increasingly employed in cybersecurity for automated threat detection and prevention.
• AI can analyze data patterns, predict attacks, and implement proactive measures.
• Continuously learns by processing large datasets to identify emerging threats and behaviors.

Applications of AI in Cybersecurity

• Threat Detection: Monitors network activity for anomalies, flagging insider threats and malicious behavior.
• Endpoint Protection: Identifies previously unknown malware through behavioral analysis.
• Cloud Security: Analyzes risky login activities and assesses potential threats in cloud environments.

Monitoring and Data Analysis

• AI systems offer automated, continuous monitoring, improving data analysis efficiency.
• Log data can be represented as a graph to enhance analysis and speed up threat detection queries.

Example Applications

• Malware Classification: AI models classify executables as malware based on past indicators, aiding in incident response and prioritization.
• Projection into a low-dimensional embedding space makes complex data analysis more tractable and meaningful for cybersecurity tasks.
• Use cases include comparing malware samples and identifying threats based on proximity in embedding space.

This quiz provides an introduction to the concepts of artificial intelligence and its relevance to cybersecurity. It covers foundational terms and explores how AI can enhance security measures in digital environments. Suitable for students enrolled in CSIT375 at the University of Wollongong in Dubai.