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In recent years, intrusion detection has become an important topic in data analytics for network protection and security measures. This paper presents a new diagnostic method for data recorded over a working computer network that can be used in information security applications such as intrusion detection and prevention. The recommended technique uses a generalised representation of correlation data (time delay and frequency delay), the Ambiguity Function. This technique has been evaluated, documented and presented through various tests of the recorded features of the network using the UNSW-NB15 dataset. The efficiency and robustness of the proposed method was experimentally demonstrated.

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Ambiguity Function as a Network Intrusion Detection Indicator

  • 会议论文

  • 发表日期：

    2025年

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  • Spiros Chountasis,
  • Dimitris Sklavounos,
  • Dimitris Pappas

摘要

In recent years, intrusion detection has become an important topic in data analytics for network protection and security measures. This paper presents a new diagnostic method for data recorded over a working computer network that can be used in information security applications such as intrusion detection and prevention. The recommended technique uses a generalised representation of correlation data (time delay and frequency delay), the Ambiguity Function. This technique has been evaluated, documented and presented through various tests of the recorded features of the network using the UNSW-NB15 dataset. The efficiency and robustness of the proposed method was experimentally demonstrated.