Blockchain and AI to improve cybersecurity – new research

by | Jun 22, 2024 | AI, Artificial Intelligence, Signal, Technology

Main Findings:

Enhanced Security and Privacy:

    • Blockchain technology (BT) and decentralised AI significantly enhance cybersecurity measures by providing a secure, transparent, and tamper-proof system for data transactions and storage.
    • Federated learning (FL), combined with blockchain, ensures data privacy while allowing decentralised training of AI models, mitigating risks associated with centralised data storage and processing​

Increased Resilience and Efficiency:

      • Decentralised AI models improve the resilience of cybersecurity systems by distributing threat detection and response mechanisms across multiple nodes, reducing the risk of single points of failure.
      • Blockchain-based smart contracts and peer-to-peer energy trading enhance the resilience and security of smart grids by eliminating the need for third-party intermediaries

Improved Collaboration and Trust:

        • Blockchain facilitates secure, real-time data sharing and automation in disaster management and other collaborative environments, enhancing transparency and trust among stakeholders.
        • The technology’s immutable ledger and consensus mechanisms ensure the authenticity and accuracy of transactions, fostering better collaboration in multi-stakeholder settings​

Challenges in Implementation:

Recommendations:

Research and Development:

    • Further empirical research is necessary to test and validate the proposed blockchain and AI models in real-world scenarios, particularly concerning smart contracts and peer-to-peer energy trading​
    • Development of incentive-based blockchain frameworks to improve federated learning methods, focusing on performance and security aspects​

Standardisation and Regulation:

      • Early standardisation efforts in blockchain technology can significantly benefit its adoption by ensuring interoperability and compliance with existing regulations.
      • A structured taxonomy categorising the key components and concepts related to blockchain and decentralised AI for cybersecurity should be developed and widely disseminated​

Privacy and Security Enhancements:

        • Adoption of advanced cryptographic methods and privacy-enhancing technologies to bolster the security and privacy of blockchain and AI solutions.
        • Implementation of decentralised identity management protocols to improve the security and scalability of identity verification processes

Collaboration and Interoperability:

          • Strategies to enhance the interoperability of various blockchain platforms and decentralised AI models should be a priority to facilitate better collaboration and data sharing across different systems and organisations.
          • Encouraging multi-stakeholder collaboration in the development and deployment of blockchain-enabled cybersecurity solutions​

By addressing these recommendations, integrating blockchain and decentralised AI can revolutionise cybersecurity, offering robust, secure, and efficient systems capable of countering evolving cyber threats.

Full research here
A.M. Shamsan Saleh, Blockchain for secure and decentralized artificial intelligence in cybersecurity: A comprehensive review, Blockchain: Research and Applications (2024), doi: https://doi.org/10.1016/j.bcra.2024.100193.