Introduction to National Security and Information Security

  • Professor Wong Kam Fei’s Background

    • Faculty of Engineering, specializes in artificial intelligence.

    • Engages in industry collaboration, community work, and practical applications of technology.

    • Emphasizes the importance of understanding diverse perspectives for better problem-solving.

Structure of Presentation

  • The lecture is divided into six parts:

    1. Definition of national security, with a focus on information security.

    2. Examples illustrating national security concepts.

    3. The impact of digitization and the role of artificial intelligence.

    4. Challenges associated with handling data and security issues.

    5. Discussion on machine learning's role in data utilization.

    6. Conclusion.

Definitions of Security in Various Contexts

  • National Security Overview

    • Broader than just military defense; includes various types of security:

    • Military Security: Protection against external threats; e.g., conflicts like Russia and Ukraine.

    • Political Security: Safeguarding political ideologies and positions against dissent.

    • Homeland Security: Preventing incidents like bomb attacks, especially in public places.

    • Economic Security: Protection from threats impacting economic stability, e.g., tensions between China and the U.S. over trade.

    • Societal Security: Maintaining social order; ensuring public safety amidst demonstrations.

    • Technology Security: Safeguarding against information breaches, e.g., tapping incidents involving political figures.

    • Environmental Security: Addressing pollution and environmental degradation affecting national integrity.

    • Food Security: Ensuring sufficient food availability; examples include impacts of wars on supply chains.

    • Resource Security: Managing natural resources like gas supply during geopolitical conflicts.

    • Nuclear Security: Protecting nuclear facilities from potential attacks and environmental hazards.

Importance of Information Security

  • Definition of Information Security:

    • A set of practices to safeguard data from unauthorized access or alterations.

    • Core Components:

    • Confidentiality: Protecting private information (e.g., Hong Kong ID, personal data) from unauthorized access.

    • Integrity: Ensuring data is accurate and unaltered; keeping misinformation at bay. Examples include political misinformation impacting electoral outcomes.

    • Availability: Guaranteeing access to information; issues arising when services become inaccessible (e.g., DDoS attacks).

Current Trends and Challenges in Information Security

  • Ransomware Incidents:

    • Example: Attack on Nvidia by LAPSUS$ group demanding ransom for decryption, representing a widespread cybersecurity issue.

    • Notable cases include disruptions to government services in Costa Rica and Gmail server failures affecting user accessibility.

The Big Data Context

  • Characteristics of Big Data:

    • Described through five Vs:

    1. Volume: Amount of data; large data sets pose comprehension challenges.

    2. Variety: Different forms of data (text, images, audio), complicating consistency and analysis.

    3. Velocity: Speed of data generation and dissemination; e.g., real-time messaging on platforms like Twitter.

    4. Veracity: Truthfulness of the information; importance of distinguishing between fact and misinformation.

    5. Value: Assessing the relevance of information from a business or user perspective.

Application of Machine Learning in Data Analysis

  • Machine Learning Overview:

    • Relies on data input for analysis, often functioning as a 'black box' with unclear decision-making processes.

    • Importance of understanding inputs and potential biases in machine learning applications.

    • Example of the "blind men and the elephant" showcasing varied interpretations of data.

Ethical and Practical Implications in Information Security

  • Privacy Concerns:

    • Legislation like GDPR regulating personal data protection, emphasizing the principle of mutual respect in data handling.

    • Case examples of data misuse and persistence of unauthorized marketing solicitations.

  • Public Responsibility and Awareness:

    • Encouragement for individuals to report incidents of data misuse to relevant authorities (e.g., Hong Kong's PCPD).

Conclusion and Future Directions

  • Security as a Foundation for Development:

    • Reference to President Xi's statement highlighting the interdependence of security and economic development.

    • Acknowledging the increasing importance of ethical data treatment and information security in a digital age.

Further Points for Discussion

  • AI and its Security Vulnerabilities:

    • The computability of AI technologies has potential risks; necessity for proactive measures in cybersecurity.

  • Future of Information Security:

    • As digital connectivity increases, the vulnerabilities and ethical implications of information access will grow more critical.

  • Ongoing Research Areas:

    • Rumor detection and the role of AI in improving understanding of misinformation dynamics.