Search Results - (( attack detection sensor algorithm ) OR ( using classification using algorithm ))

Refine Results
  1. 1

    Energy-efficient intrusion detection in wireless sensor network by Salehian, Solmaz, Masoumiyan, Farzaneh, Udzir, Nur Izura

    Published 2012
    “…There are several algorithms for building Intrusion Detection Systems (IDS) based on different WSN routing protocol classifications with respect to energy-efficient manner. …”
    Get full text
    Get full text
    Conference or Workshop Item
  2. 2

    Anomaly detection in ICS datasets with machine learning algorithms by Mubarak, Sinil, Habaebi, Mohamed Hadi, Islam, Md Rafiqul, Abdul Rahman, Farah Diyana, Tahir, Mohammad

    Published 2021
    “…The features of flow-based network traffic are extracted for behavior analysis with port-wise profiling based on the data baseline, and anomaly detection classification and prediction using machine learning algorithms are performed.…”
    Get full text
    Get full text
    Get full text
    Get full text
    Get full text
    Article
  3. 3

    Internet of Things (IoT) intrusion detection by Machine Learning (ML): a review by Dehkordi, Iman Farhadian, Manochehri, Kooroush, Aghazarian, Vahe

    Published 2023
    “…The goal of this study is to show the results of analyzing various classification algorithms in terms of confusion matrix, accuracy, precision, specificity, sensitivity, and f-score to Develop an Intrusion Detection System (IDS) model.…”
    Get full text
    Get full text
    Get full text
    Article
  4. 4
  5. 5
  6. 6
  7. 7

    Presentation attack detection for face recognition on smartphones: a comprehensive review by Abdul Ghaffar, Idris, Haji Mohd, Mohd Norzali

    Published 2017
    “…Face Presentation Attack Detection through the sensor level technique involved in using additional hardware or sensor to protect recognition system from spoofing while feature level techniques are purely software-based algorithms and analysis. …”
    Get full text
    Get full text
    Article
  8. 8

    Cooperative multi agents for intelligent intrusion detection and prevention systems / Shahaboddin Shamshirband by Shamshirband, Shahaboddin

    Published 2014
    “…This thesis evaluates the proposed solution using flooding attacks in wireless sensor networks (i.e. a type of DDoS attack). …”
    Get full text
    Get full text
    Thesis
  9. 9

    Algorithm enhancement for host-based intrusion detection system using discriminant analysis by Dahlan, Dahliyusmanto

    Published 2004
    “…Misuse detection algorithms model know attack behavior. They compare sensor data to attack patterns learned from the training data. …”
    Get full text
    Get full text
    Thesis
  10. 10

    A study on advanced statistical analysis for network anomaly detection by Ngadi, Md. Asri, Idris, Mohd. Yazid, Abdullah, Abd. Hanan

    Published 2005
    “…Misuse detection algorithms model know attack behavior. They compare sensor data to attack patterns learned from the training data. …”
    Get full text
    Monograph
  11. 11

    ETERS: A comprehensive energy aware trust-based efficient routing scheme for adversarial WSNs by Khan, T., Singh, K., Hasan, M.H., Ahmad, K., Reddy, G.T., Mohan, S., Ahmadian, A.

    Published 2021
    “…However, a trust-based attack detection algorithm (TADA) assesses the reliability of SNs to detect internal attacks. …”
    Get full text
    Get full text
    Article
  12. 12

    Cyber attacks analysis and mitigation with machine learning techniques in ICS SCADA systems by Mubarak, Sinil, Habaebi, Mohamed Hadi, Abdul Rahman, Farah Diyana, Khan, Sheroz, Islam, Md Rafiqul

    Published 2019
    “…Mitigation techniques such as honeypot simulation which helps in vulnerability assessment, along with machine learning algorithms, suitable for intrusion detection and prevention of cyber-attacks in SCADA systems has been detailed.…”
    Get full text
    Get full text
    Get full text
    Article
  13. 13
  14. 14

    Machine learning-based anomaly detection in NFV: a comprehensive survey by Sehar Zehra, Ummay Faseeha, Hassan Jamil Syed, Fahad Samad, Ashraf Osman Ibrahim Elsayed, Anas W. Abulfaraj, Wamda Nagmeldin

    Published 2023
    “…It proposes the utilization of anomaly detection techniques as a means to mitigate the potential risks of cyber attacks. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Article
  15. 15
  16. 16

    Deep learning in distributed denial-ofservice attacks detection method for Internet of Things networks by Mohammed Aswad, Firas, Saleh Ahmed,, Ali Mohammed, Ali Majeed Alhammadi, Nafea, Ahmad Khalaf, Bashar, A. Mostafa, Salama

    Published 2023
    “…The RNN, CNN, LSTM, and CNN-BiLSTM are implemented and tested to determine the most effective model against DDoS attacks that can accurately detect and distinguish DDoS from legitimate traffic. …”
    Get full text
    Get full text
    Get full text
    Article
  17. 17

    Deep learning in distributed denial-ofservice attacks detection method for Internet of Things networks by Mohammed Aswad, Firas, Ahmed, Ali Mohammed Saleh, Majeed Alhammadi, Nafea Ali, Ahmad Khalaf, Bashar, A. Mostafa, Salama

    Published 2023
    “…The RNN, CNN, LSTM, and CNN-BiLSTM are implemented and tested to determine the most effective model against DDoS attacks that can accurately detect and distinguish DDoS from legitimate traffic. …”
    Get full text
    Get full text
    Get full text
    Article
  18. 18

    Deep learning in distributed denial-ofservice attacks detection method for Internet of Things networks by Mohammed Aswad, Firas, Saleh Ahmed, Ali Mohammed, Ali Majeed Alhammadi, Nafea, Ahmad Khalaf, Bashar, A. Mostafa, Salama

    Published 2023
    “…The RNN, CNN, LSTM, and CNN-BiLSTM are implemented and tested to determine the most effective model against DDoS attacks that can accurately detect and distinguish DDoS from legitimate traffic. …”
    Get full text
    Get full text
    Get full text
    Article
  19. 19
  20. 20