• Title/Summary/Keyword: icmp flood

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A study on the outbound traffic controller for prevention of ICMP attacks (ICMP 공격 방지를 위한 outbound traffic controller에 관한 연구)

  • Yoo, Kwon-joeong;Kim, Eun-gi
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2016.10a
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    • pp.759-761
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    • 2016
  • ICMP(Internet Control Message Protocol) supports the processing of error in the communication network based TCP/IP. If a problem is occurred in a data transmission process, router or receiving host sends ICMP message containing the error cause to sending host. However, in this process an attacker sends a fake ICMP message to the host so that the communication between the hosts can be abnormally terminated. In this paper, we performed a study to prevent several attacks related to ICMP. To this, we have designed outbound traffic controller so that attack packet is not transmitted to network in operating system of host.

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A DDoS attack Mitigation in IoT Communications Using Machine Learning

  • Hailye Tekleselase
    • International Journal of Computer Science & Network Security
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    • v.24 no.4
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    • pp.170-178
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    • 2024
  • Through the growth of the fifth-generation networks and artificial intelligence technologies, new threats and challenges have appeared to wireless communication system, especially in cybersecurity. And IoT networks are gradually attractive stages for introduction of DDoS attacks due to integral frailer security and resource-constrained nature of IoT devices. This paper emphases on detecting DDoS attack in wireless networks by categorizing inward network packets on the transport layer as either "abnormal" or "normal" using the integration of machine learning algorithms knowledge-based system. In this paper, deep learning algorithms and CNN were autonomously trained for mitigating DDoS attacks. This paper lays importance on misuse based DDOS attacks which comprise TCP SYN-Flood and ICMP flood. The researcher uses CICIDS2017 and NSL-KDD dataset in training and testing the algorithms (model) while the experimentation phase. accuracy score is used to measure the classification performance of the four algorithms. the results display that the 99.93 performance is recorded.