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Yanping Shen, Kangfeng Zheng, Yanqing Yang, Shuai Liu and Meng Huang
Various machine-learning methods have been applied to anomaly intrusion detection. However, the Intrusion Detection System still faces challenges in improving Detection Rate and reducing False Positive Rate. In this paper, a Class-Level Soft-Voting Ensem...
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Nathan Martindale, Muhammad Ismail and Douglas A. Talbert
As new cyberattacks are launched against systems and networks on a daily basis, the ability for network intrusion detection systems to operate efficiently in the big data era has become critically important, particularly as more low-power Internet-of-Thi...
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Hongyu Liu and Bo Lang
Networks play important roles in modern life, and cyber security has become a vital research area. An intrusion detection system (IDS) which is an important cyber security technique, monitors the state of software and hardware running in the network. Des...
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Iwan Syarif
Pág. 277 - 290
This paper describes the advantages of using Evolutionary Algorithms (EA) for feature selection on network intrusion dataset. Most current Network Intrusion Detection Systems (NIDS) are unable to detect intrusions in real time because of high dimensional...
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Kegong Diao, Chris Sweetapple, Raziyeh Farmani, Guangtao Fu, ... David Butler
Pág. 383 - 393
Evaluating and enhancing resilience in water infrastructure is a crucial step towards more sustainable urban water management. As a prerequisite to enhancing resilience, a detailed understanding is required of the inherent resilience of the underlying sy...
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