Search Results - (( java implementation rsa algorithm ) OR ( attack detection sensor algorithm ))

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  1. 1
    RSA Encryption & Decryption using JAVA

    RSA Encryption & Decryption using JAVA by Ramli, Marliyana

    Published 2006
    “…References and theories to support the research of 'RSA Encryption/Decryption using Java' have been disclosed in Literature Review section. …”
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    Final Year Project
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  2. 2
    AUTOMATED MODEL GENERATION OF FSM AND NUSMV MODEL FROM RSA JAVA SOURCE CODE FOR MODEL CHECKING

    AUTOMATED MODEL GENERATION OF FSM AND NUSMV MODEL FROM RSA JAVA SOURCE CODE FOR MODEL CHECKING by SALLEH AL-HUMAIKANI, MOHAMMED ABDULQAWI

    Published 2021
    “…RSA is one of these encryption algorithms that have been implemented in security systems. …”
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    Thesis
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  3. 3
    An improved RSA cryptosystem based on thread and CRT / Saheed Yakub Kayode and Gbolagade Kazeem Alagbe

    An improved RSA cryptosystem based on thread and CRT / Saheed Yakub Kayode and Gbolagade Kazeem Alagbe by Yakub Kayode, Saheed, Kazeem Alagbe, Gbolagade

    Published 2017
    “…Java programming language is used to implement the algorithm. …”
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  4. 4
    Secure Image Steganography Using Encryption Algorithm

    Secure Image Steganography Using Encryption Algorithm by Siti Dhalila, Mohd Satar, Roslinda, Muda, Fatimah, Ghazali, Mustafa, Mamat, Nazirah, Abd Hamid, An, P.K

    Published 2016
    “…A system based on the proposed algorithm will be implemented using Java and it will be more secured due to double-layer of security mechanisms which are RSA and Diffie-Hellman.…”
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    Conference or Workshop Item
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  5. 5
    A new sinkhole attack detection algorithm for RPL in wireless sensor networks (WSN)

    A new sinkhole attack detection algorithm for RPL in wireless sensor networks (WSN) by Ali, Mohammed Qasim

    Published 2019
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  6. 6
    Detecting sybil attacks in clustered wireless sensor networks based on energy trust system (ETS)

    Detecting sybil attacks in clustered wireless sensor networks based on energy trust system (ETS) by Alsaedi, Noor, Hashim, Fazirulhisyam, Sali, Aduwati, Rokhani, Fakhrul Zaman

    Published 2017
    “…Then, a trust algorithm is applied based on the energy of each sensor node. …”
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  7. 7
    A novel energy-efficient sybil node detection algorithm for intrusion detection system in wireless sensor networks

    A novel energy-efficient sybil node detection algorithm for intrusion detection system in wireless sensor networks by Karuppiah, A. Babu, Dalfiah, J., Yuvashri, K., Rajaram, S., Pathan, Al-Sakib Khan

    Published 2014
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  8. 8
    Presentation attack detection for face recognition on smartphones: a comprehensive review

    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. …”
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  9. 9
    Cooperative multi agents for intelligent intrusion detection and prevention systems / Shahaboddin Shamshirband

    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). …”
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  10. 10
    Algorithm enhancement for host-based intrusion detection system using discriminant analysis

    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. …”
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  11. 11
    A study on advanced statistical analysis for network anomaly detection

    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. …”
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  12. 12
    Digitally signed electronic certificate for workshop / Azinuddin Baharum

    Digitally signed electronic certificate for workshop / Azinuddin Baharum by Baharum, Azinuddin

    Published 2017
    “…Digital Signature was encrypted by RSA Algorithm, a very powerful asymmetrical encryption. …”
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  13. 13
    Energy-efficient intrusion detection in wireless sensor network

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

    Published 2012
    “…Attacks can occur from any direction and any node in WSNs, so one crucial security challenge is to detect networks' intrusion. …”
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  14. 14
    ETERS: A comprehensive energy aware trust-based efficient routing scheme for adversarial WSNs

    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. …”
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  15. 15
    Cyber attacks analysis and mitigation with machine learning techniques in ICS SCADA systems

    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.…”
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  16. 16
    Secure and Energy-Efficient Data Aggregation Method Based on an Access Control Model

    Secure and Energy-Efficient Data Aggregation Method Based on an Access Control Model by Jasim, Ahmed Abdulhadi, Idris, Mohd Yamani Idna, Azzuhri, Saaidal Razalli, Issa, Noor Riyadh, Noor, Noorzaily Mohamed, Kakarla, Jagadeesh, Amiri, Iraj Sadegh

    Published 2019
    “…The secure node authentication algorithm prevents attacks from accessing the network. …”
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  17. 17
    Machine learning-based anomaly detection in NFV: a comprehensive survey

    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. …”
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  18. 18
    Modelling of intelligent intrusion detection system: making a case for snort

    Modelling of intelligent intrusion detection system: making a case for snort by Olanrewaju, Rashidah Funke, Ku zahir, Ku Nor Afiza, Asnawi, Ani Liza, Sanni, Mistura Laide, Ahmed, Abdulkadir Adekunle

    Published 2018
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  19. 19
    Deep learning in distributed denial-ofservice attacks detection method for Internet of Things networks

    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. …”
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  20. 20
    Deep learning in distributed denial-ofservice attacks detection method for Internet of Things networks

    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. …”
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