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. …”

Unsupervised Anomaly Detection with Unlabeled Data Using Clustering by Chimphlee, Witcha, Abdullah, Abdul Hanan, Md. Sap, Mohd. Noor

“…We present a clustering-based intrusion detection algorithm, unsupervised anomaly detection, which trains on unlabeled data in order to detect new intrusions. …”
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Integrating genetic algorithms and fuzzy c-means for anomaly detection by Chimphlee, Witcha, Abdullah, Abdul Hanan, Sap, Noor Md., Chimphlee, Siriporn, Srinoy, Surat

“…The amount of available network audit data instances is usually large; human labeling is tedious, time-consuming, and expensive. Traditional anomaly detection algorithms require a set of purely normal data from which they train their model. …”
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To identify suspicious activity in anomaly detection based on soft computing by Chimphlee, Witcha, Sap, M., Abdullah, Abdul Hanan, Chimphlee, Siriporn, Srinoy, Surat

“…Empirical studies using the network security data set from the DARPA 1998 offline intrusion detection project (KDD 1999 Cup) show the feasibility of misuse and anomaly detection results.…”

Anomaly detection through spatio-temporal context modeling in crowded scenes by Lu, T., Wu, L., Ma, X., Shivakumara, P., Tan, C.L.

“…The proposed framework essentially turns the anomaly detection process into two parts, namely, motion pattern representation and crowded context modeling. …”
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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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Real valued negative selection for anomaly detection in wireless ad hoc networks by Abdul Majid, Azri, Maarof, Mohd. Aizaini

“…To achieve our goal, we studied how the real-valued negative selection algorithm can be applied in wireless ad hoc network network and finally we proposed the enhancements to real-valued negative selection algorithm for anomaly detection in wireless ad hoc network.…”
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Improving the anomaly detection by combining PSO search methods and J48 algorithm by Kurniabudi, Kurniabudi, Abdul Harris, Abdul Harris, Mintaria, Albertus Edward, Darmawijoyo, Darmawijoyo, Stiawan, Deris, Idris, Mohd. Yazid, Budiarto, Rahmat

“…Compared with the previous study the proposed technique has better accuracy, TPR, and FPR.Anomaly Detection, CICIDS2017…”

A feature selection algorithm for anomaly detection in grid environment using k-fold cross validation technique by Dahliyusmanto, Dahliyusmanto, Herawan, Tutut, Syefrida Yulina, Syefrida Yulina, Abdullah, Abdul Hanan

Campus hybrid intrusion detection system using SNORT and C4.5 Algorithm by Slamet, ., Izzeldin, I. Mohd, Fahmi, Samsuri

“…In this paper, the authors built Hybrid Intrusion Detecting System combines misuse detection system with anomaly detection system. The basis of misused detection module is snort, and anomaly detection module is constructed by using Algorithm C4.5 detectors. …”
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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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An FPGA-based IP core subscription-oriented fog computing platform by Tan, Tze Hon, Ooi, Chia Yee, Marsono, M. N.

“…The throughput and latency of implemented FPGA-based time-series anomaly detection analytics are 3096 detections per second and 0.32 ms, respectively, which is more than 61 × speedup over the reference analytics implemented in software. …”

Anomaly intrusion detection model using data mining techniques by Abdullah, Abdul Hanan, Rusli, Rozana

“…Evaluations are done using unsupervised anomaly detection schemes on the DARPA’98 data sets and real network traffic. …”

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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Fast optimization method: an on-line hurst parameter estimator by Idris, Mohd. Yazid, Abdullah, Abdul Hanan, Maarof, Mohd. Aizaini

“…The on-line Hurst estimator is crucial to characterize self-similar feature on stochastic process and widely applied in various fields such as in network traffic analysis, bandwidth provisioning and anomaly detection. Recent on-line Hurst estimator based on fast wavelet transform known as real-time wavelet estimator (RWM) is proven can estimates faster than other methods in on-line fashion. …”

Stepping-stone detection technique for recognizing legitimate and attack connections by Daud, Ali Yusny, Ghazali, Osman, Omar, Mohd Nizam

“…However, not all stepping-stone connections are malicious.This paper proposes an enhanced stepping-stone detection (SSD) technique which is capable to identify legitimate connections from stepping-stone connections.Stepping-stone connections are identified from raw network traffics using timing-based SSD approach.Then, they go through an anomaly detection technique to differentiate between legitimate and attack connections.This technique has a promising solution to accurately detecting intrusions from stepping-stone connections.It will prevent incorrect responses that punish legitimate users.…”
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Review of firewall optimization techniques by Shakirah, Saidin, Mohamad Fadli, Zolkipli

“…This paper review firewall optimization techniques such as data mining, anomaly detection, and traffic awareness, that have been done throughout time. …”
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Thermal Condition Monitoring of Electrical Installations Based on Infrared Image Analysis by M. S., Jadin, Kamarul Hawari, Ghazali, Soib, Taib

“…Therefore, this paper proposed a fast thermal anomaly detection and classification based on qualitative infrared image analysis. …”
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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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Anomaly intrusion detection systems in IoT using deep learning techniques: a survey by Alsoufi, Muaadh. A., Razak, Shukor, Md. Siraj, Maheyzah, Ali, Abdulalem, Nasser, Maged, Abdo, Salah

“…Consequently, improving the performance of anomaly detection requires the use of advanced deep learning techniques instead of traditional shallow learning approaches. …”