A neural network component for an intrusion detection system

By Hervé Debar, M. Becker, D. Siboni. 1992

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Citations in the corpus

Neural Cleanse: Identifying and Mitigating Backdoor Attacks in Neural Networks (2019, methodology): “In the security space, DNNs are used for everything from malware classification [1], [2], to binary reverseengineering [3], [4] and network intrusion detection [5].”
Intrusion detection using neural networks and support vector machines (2002, methodology): “Using neural networks for intrusion detection has been done within the security community [1, 7 ,8,10,11].”
Modeling intrusion detection system using hybrid intelligent systems (2007, background): “They designed the detector analogous to the T and B-lymphocytes that are found in the human immunological system.”
The use of computational intelligence in intrusion detection systems: A review (2010, methodology): “[70, 72] modified the traditional Elman recurrent model by giving input at both time t-1 and time t.”
The base-rate fallacy and the difficulty of intrusion detection (2000, background): “More “sophisticated” detectors, such as neural network-based detectors (such as Debar et al. [1992]), that take time series behavior of the subject into account, are unfortunately not covered.”
Immune system approaches to intrusion detection – a review (2004, background): “Many experimental anomaly detection systems exist including [34, 69, 108] and a commercial system also adopts the anomaly detection approach [4].”
Intrusion Detection with Neural Networks (1997, methodology): “Several IDSs that employ neural networks for on-line intrusion detection have been proposed (Debar et al. 1992: Fox et al. 1990).”
Anomaly-based network intrusion detection: Techniques, systems and challenges (2009, methodology): “This detection approach has been employed to create user profiles (Fox et al., 1990), to predict the next command from a sequence of previous ones (Debar et al., 1992), to identify the intrusive behaviour of traffic patterns (Cansian et al., 1997), etc.”
Intrusion Detection Systems: A Survey and Taxonomy (2002, background): “Hyperview [ DBS92 ] is a system with two major components.”
Deep Learning for Unsupervised Insider Threat Detection in Structured Cybersecurity Data Streams (2017, unknown): “Early work on modeling normal user activity on a network using RNNs was performed by Debar et al. (1992).”
Carat: collaborative energy diagnosis for mobile devices (2013, background): “In the field of security, anomaly-based intrusion detection has a long history [8, 34, 35].”