TY - GEN
T1 - Data-Aided Intrusion Detection Systems: Leveraging AI, Blockchain and Digital Twin Technology
AU - Alharbi, Ohood
AU - Shaikh, Riaz Ahmed
AU - Asif, Rameez
PY - 2025/1/16
Y1 - 2025/1/16
N2 - Intrusion Detection Systems (IDS) are the key for securing the rapidly evolving Internet-of-Things (IoT), where data security and privacy will become increasingly important in the forthcoming era. This research presents an innovative method for improving IDS performance through the integration of Artificial Intelligence (AI), Blockchain, and Digital Twin (DT) technologies. AI is utilized for real-time anomaly detection, whereas DT replicate device behavior for predicting threats and Blockchain ensures secure, decentralized data transmission. Energy-efficient zero-knowledge proofs are employed to meet the energy requirements of Blockchain, enhancing both security and resource efficiency. The performance of the suggested system will be assessed based on detection accuracy, latency, scalability, energy efficiency, and privacy preservation. This distinctive integration of advanced technologies delivers a multi-faceted security system, providing a thorough respond to for strengthening security in IoT networks.
AB - Intrusion Detection Systems (IDS) are the key for securing the rapidly evolving Internet-of-Things (IoT), where data security and privacy will become increasingly important in the forthcoming era. This research presents an innovative method for improving IDS performance through the integration of Artificial Intelligence (AI), Blockchain, and Digital Twin (DT) technologies. AI is utilized for real-time anomaly detection, whereas DT replicate device behavior for predicting threats and Blockchain ensures secure, decentralized data transmission. Energy-efficient zero-knowledge proofs are employed to meet the energy requirements of Blockchain, enhancing both security and resource efficiency. The performance of the suggested system will be assessed based on detection accuracy, latency, scalability, energy efficiency, and privacy preservation. This distinctive integration of advanced technologies delivers a multi-faceted security system, providing a thorough respond to for strengthening security in IoT networks.
UR - http://www.scopus.com/inward/record.url?scp=85218023189&partnerID=8YFLogxK
U2 - 10.1109/BigData62323.2024.10825899
DO - 10.1109/BigData62323.2024.10825899
M3 - Conference contribution
T3 - Proceedings - 2024 IEEE International Conference on Big Data, BigData 2024
SP - 8214
EP - 8215
BT - 2024 IEEE International Conference on Big Data (BigData)
PB - The Institute of Electrical and Electronics Engineers (IEEE)
CY - Washington, DC, USA
ER -