TY - GEN
T1 - Building Cyber Resilience
T2 - 1st International Conference on Data Processing and Networking, ICDPN 2024
AU - Rasheed, Awais
AU - Nasir, Hifsah
AU - Hussain, Nazar
AU - Khan, Maqbool
AU - Li, Wei
AU - Ahmad, Faizan
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.
PY - 2025/9/1
Y1 - 2025/9/1
N2 - Artificial intelligence has revolutionized threat detection and risk management in the evolving cybersecurity landscape. By combining machine learning and deep learning techniques, proactive cybersecurity strategies can be developed. AI models can predict cyber threats early by analyzing various data sources like network logs and system activity records. Integration of ML algorithms with advanced data analysis techniques such as clustering provides a comprehensive view of security incidents. Hybrid models like convolutional neural networks and recurrent neural networks, along with transfer learning and explainable AI, enhance anomaly detection capabilities. These AI-driven approaches improve cyber resilience by detecting threats early on and offering adaptive responses to protect critical assets and maintain operational continuity.
AB - Artificial intelligence has revolutionized threat detection and risk management in the evolving cybersecurity landscape. By combining machine learning and deep learning techniques, proactive cybersecurity strategies can be developed. AI models can predict cyber threats early by analyzing various data sources like network logs and system activity records. Integration of ML algorithms with advanced data analysis techniques such as clustering provides a comprehensive view of security incidents. Hybrid models like convolutional neural networks and recurrent neural networks, along with transfer learning and explainable AI, enhance anomaly detection capabilities. These AI-driven approaches improve cyber resilience by detecting threats early on and offering adaptive responses to protect critical assets and maintain operational continuity.
KW - Anomaly detection
KW - Convolution neural network (CNN)
KW - Cyber resilience
KW - Explainable AI (XAI)
KW - Machine learning (ML)
KW - Predictive analytics
KW - Recurrent neural network (RNN)
KW - Threat detection
KW - Threats prediction
UR - https://www.scopus.com/pages/publications/105016005074
U2 - 10.1007/978-981-96-5535-9_10
DO - 10.1007/978-981-96-5535-9_10
M3 - Conference contribution
AN - SCOPUS:105016005074
SN - 9789819655342
T3 - Lecture Notes in Networks and Systems
SP - 139
EP - 154
BT - Data Processing and Networking - Proceedings of ICDPN 2024
A2 - Swaroop, Abhishek
A2 - Virdee, Bal
A2 - Correia, Sérgio Duarte
A2 - Valicek, Jan
PB - Springer Science and Business Media Deutschland GmbH
Y2 - 25 October 2024 through 26 October 2024
ER -