Packet header anomaly detection using statistical analysis by Yassin, Warusia, Udzir, Nur Izura, Abdullah, Azizol, Abdullah @ Selimun, Mohd Taufik, Muda, Zaiton, Zulzalil, Hazura

“…The disclosure of network packets to recurrent cyber intrusion has upraised the essential for modelling various statistical-based anomaly detection methods lately. Theoretically, the statistical-based anomaly detection method fascinates researcher’s attentiveness, but technologically, the fewer intrusion detection rates persist as vulnerable disputes. …”

A refined filter for UHAD to improve anomaly detection by Hajamydeen, Asif Iqbal, Udzir, Nur Izura

“…Therefore, this paper proposes a refined filterer for unsupervised heterogeneous anomaly detection that retains most anomalous events irrespective of its volume in the logs and also discusses the impact of the refined filterer in supporting the detection. …”
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A comparison of different technique in flow based anomaly detection by Salah, Mohammad

Subjects: “…Anomaly detection (Computer security)…”
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Host-based packet header anomaly detection using statistical analysis by Yassin, Warusia, Udzir, Nur Izura, Abdullah, Azizol, Abdullah @ Selimun, Mohd Taufik, Muda, Zaiton, Zulzalil, Hazura

“…The exposure of network packets to frequent cyber attacks has increased the need for designing statistical-based anomaly detection recently. Conceptually, the statistical based anomaly detection attracts researcher's attention, but technically, the low attack detection rates remains an open challenges. …”
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Effective dimensionality reduction of payload-based anomaly detection in TMAD model for HTTP payload by Kakavand, Mohsen, Mustapha, Norwati, Mustapha, Aida, Abdullah @ Selimun, Mohd Taufik

“…Our proposed anomaly detection also achieved comparable performance in terms of computational complexity when compared to three state-of-the-art anomaly detection systems.…”
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A survey of anomaly detection using data mining methods for hypertext transfer protocol web services by Kakavand, Mohsen, Mustapha, Norwati, Mustapha, Aida, Abdullah, Mohd Taufik, Riahi, Hamed

“…Data mining is widely recognized as popular and important intelligent and automatic tools to assist humans in big data security analysis and anomaly detection over IDSs. In this study we discuss our review in data mining anomaly detection methods for HTTP web services. …”
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Improving intrusion detection for better anomaly detection based on x-means clustering and multi-layer perceptron classification by Abbas, Borkan Ahmed

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Improved TLS protocol for platform integrity assurance using mutual attestation by Abd Aziz, Norazah

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Permission extraction framework for android malware detection by Ghasempour, Ali

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An efficient anomaly intrusion detection method with evolutionary neural network by Sarvari, Samira

“…Despite all the strengths of the anomaly detection systems, there are still drawbacks that reduce the performance of the system. …”
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An integrated anomaly intrusion detection scheme using statistical, hybridized classifiers and signature approach by Mohamed Yassin, Warusia

“…In recent years, data mining based anomaly detection (DMAD), particularly classification methods, have been incessantly enhanced in differentiating normal and attack behaviour. …”
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Intrusion detection based on K-means clustering and Naïve Bayes classification by Muda, Zaiton, Mohamed Yassin, Warusia, Sulaiman, Md. Nasir, Udzir, Nur Izura

“…Intrusion Detection System (IDS) plays an effective way to achieve higher security in detecting malicious activities for a couple of years. Anomaly detection is one of intrusion detection system. …”
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Signature-based anomaly intrusion detection using integrated data mining classifiers by Yassin, Warusia, Udzir, Nur Izura, Abdullah, Azizol, Abdullah @ Selimun, Mohd Taufik, Zulzalil, Hazura, Muda, Zaiton

“…In this work, a novel Signature-Based Anomaly Detection Scheme (SADS) which could be applied to scrutinize packet headers' behaviour patterns more precisely and promptly is proposed. …”
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An overview of neural networks use in anomaly intrusion detection systems by Sani, Yusuf, Mohamedou, Ahmed, Ali, Khalid Abdullahi, Farjamfar, Anahita, Azman, Mohamed, Shamsuddin, Solahuddin

“…But the main problem of anomaly detection IDS is that; it is very difficult to build, because of the difficulty in defining what is normal and what is abnormal. …”
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An efficient anomaly intrusion detection method with evolutionary kernel neural network random weights by Sarvari, Samira, Mohd Sani, Nor Fazlida, Mohd Hanapi, Zurina, Abdullah @ Selimun, Mohd Taufik

“…Considering that using a combination of ANN and EA can produce an advanced technique to develop an efficient anomaly detection approach for IDS, several types of research have used ENN algorithms to detect the attacks. …”
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A proposed approach for diabetes diagnosis using neuro-fuzzy technique by Alasaady, Maher Talal, Mohd Aris, Teh Noranis, Mohd Sharef, Nurfadhlina, Hamdan, Hazlina

“…Normalization, imputation, and anomaly detection are part of the pre-processing stage. …”

Improving intrusion detection using genetic algorithm by Hashemi, V. Moraveji, Muda, Zaiton, Yassin, Warusia

“…A great deal of attention has been recently paid to anomaly detection to accomplish intrusion detection. However, a major problem with this approach is maximizing detection rate and accuracy, as well as minimizing false alarm i.e., inability to correctly discover particular types of attacks. …”
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A systematic literature review on outlier detection in wireless sensor networks by Safaei, Mahmood, Asadi, Shahla, Driss, Maha, Boulila, Wadii, Alsaeedi, Abdullah, Chizari, Hassan, Abdullah, Rusli, Safaei, Mitra

“…The purpose of this paper is to conduct a systematic literature review to report the available works on outlier and anomaly detection in WSNs. The paper highlights works conducted from January 2004 to October 2018. …”
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Anomaly behavior detection using flexible packet filtering and support vector machine algorithms by Abdul Wahid, Mohammed N.

“…The main method is related to processing and filtering data packets using different types of packet filtering on network system and, more specifically, capturing and filtering data packets transmitted on high speed communications links for errors and attackers’ detection and signal integrity analysis. Many anomaly detection experiments have been conducted in order to investigate the performance of network traffics filtering methods that analyzing bandwidth, speed, errors and attackers. …”
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Statistical global investigation of pre-earthquake anomalous geomagnetic diurnal variation using superposed epoch analysis by Yusof, Khairul Adib, Abdullah, Mardina, Abdul Hamid, Nurul Shazana, Ahadi, Suaidi, Ghamry, Essam

“…However, the statistical significance of such anomalies detected using the diurnal variation range ratio (DVRR) method still requires verification as only a limited number of EQs occurring in certain seismoactive zones were included. …”