Intrusion detection technique based on flow aggregation and latent semantic analysis

Author:

Wu JunruiORCID,Wang WenyongORCID,Huang LishengORCID,Zhang Fengjun

Funder

Ministry of Science and Technology of the People's Republic of China

National Key Research and Development Program of China

Publisher

Elsevier BV

Subject

Software

Reference44 articles.

1. Internet of Things for Sustainability: Perspectives in Privacy, Cybersecurity, and Future Trends;Salam,2020

2. Got phished? Internet security and human vulnerability;Goel;J. Assoc. Inf. Syst.,2017

3. The use of ensemble models for multiple class and binary class classification for improving intrusion detection systems;Iwendi;Sensors,2020

4. An intelligent intrusion detection system (IDS) for anomaly and misuse detection in computer networks;Depren;Expert Syst. Appl.,2005

5. James Cannady, James Mahaffey, The application of artificial neural networks to misuse detection: initial results, in: Proceedings of the 1st International Workshop on Recent Advances in Intrusion Detection, Citeseer.

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1. Research on Deep Learning-based Network Intrusion Detection Model;2023 4th International Conference on Computer, Big Data and Artificial Intelligence (ICCBD+AI);2023-12-15

2. DDoS2Vec: Flow-Level Characterisation of Volumetric DDoS Attacks at Scale;Proceedings of the ACM on Networking;2023-11-27

3. Intrusion Detection Behavioral Model by Using ANN;Proceedings of International Conference on Data Analytics and Insights, ICDAI 2023;2023

4. NTFA: Network Flow Aggregator;Proceedings of the International Conference on Applied Cybersecurity (ACS) 2023;2023

5. A Malicious Code Detection Method Based on FF-MICNN in the Internet of Things;Sensors;2022-11-12

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