A survey of intrusion detection in Internet of Things

https://romisatriawahono.net/lecture/rm/survey/network%20security/Patel%20-%20Intrution%20Detection%20System%20in%20Cloud%20-%202013.pdf

Review: An intrusion detection and prevention system in cloud computing: A systematic review

This paper presents a novel feature learning model for cyber security tasks. We propose to use Auto-encoders (AEs), as a generative model, to learn latent representation of different feature sets. We show how well the AE is capable of automatically learning a reasonable notion of semantic similarity among input features. Specifically, the AE accepts a feature vector, obtained from cyber security phenomena, and extracts a code vector that captures the semantic similarity between the feature vectors. This similarity is embedded in an abstract latent representation. Because the AE is trained in an unsupervised fashion, the main part of this success comes from appropriate original feature set that is used in this paper. It can also provide more discriminative features in contrast to other feature engineering approaches. Furthermore, the scheme can reduce the dimensionality of the features thereby signicantly minimising the memory requirements. We selected two different cyber security tasks: networkbased anomaly intrusion detection and Malware classication. We have analysed the proposed scheme with various classifiers using publicly available datasets for network anomaly intrusion detection and malware classifications. Several appropriate evaluation metrics show improvement compared to prior results.

Autoencoder-based feature learning for cyber security applications

This paper completely introduces an exhaustive and a comprehensive review of the so-called salp swarm algorithm (SSA) and discussions its main characteristics. SSA is one of the efficient recent meta-heuristic optimization algorithms, where it has been successfully utilized in a wide range of optimization problems in different fields, such as machine learning, engineering design, wireless networking, image processing, and power energy. This review shows the available literature on SSA, including its variants, like binary, modifications and multi-objective. Followed by its applications, assessment and evaluation, and finally the conclusions, which focus on the current works on SSA, suggest possible future research directions.

Salp swarm algorithm: a comprehensive survey

Anomaly network-based intrusion detection system using a reliable hybrid artificial bee colony and AdaBoost algorithms

Finding information through search engines from large data repositories becomes more complicated due to three things; the growth and the size of the Web, insufficient relevancy of most of the search results, and the need to sort out the more relevant results from less relevant results. For more than a decade, many great methods and tools for visualization in faceted search engines have been developed and literature about them published in conference proceedings and journals. However, there are still rooms for improvement. To take up this, we have reviewed many visualizations based faceted search and performed our research especially on information exploration on the Web with the purpose of finding a better way to address visualization in faceted search. In this research, we discuss some issues among many, such as pre-processing and acquisition of search results that need to be taken into consideration in the development of a visualization based faceted search. The main contribution of this paper is a report of the review of past information on visualization-based faceted search tools and the mechanisms for enhancing filters to reduce down the results of the search process.

Visualization in Faceted Search Engine - A Review

The increasing interaction of modern industrial control systems (ICS) to the outside Internet world influences making these systems vulnerable to a wide range of cyber-attacks. Moreover, the utilisation of Commercial-off-the-Shelf (COTS) products, as well as open communication protocols, made them attractive targets to various threat agents including cyber-criminals, national-state, and cyber-terrorists. Given that, today's ICSs are deriving the most critical national infrastructures. Therefore, this raises tremendous needs to secure these systems against cyber-attacks. Intrusion detection technology has been considered as one of the most essential security precautions for ICS networks. It can effectively detect potential cyber-attacks and malicious activities and prevent catastrophic consequences. This paper puts forward a new method to detect malicious activities at the ICS net-works.

An Anomaly Detection Technique for Deception Attacks in Industrial Control Systems

Machine learning-based telemedicine framework to prioritize remote patients with multi-chronic diseases for emergency healthcare services

Supervisory Control and Data Acquisition (SCADA) system is the underlying control system of most national critical infrastructures such as power, energy, water, transportation and telecommunication. In order to understand the potential threats to these infrastructures and the mechanisms to protect them, different types of cyber-attacks applicable to these infrastructures need to be identified. Therefore, there is a significant need to have a comprehensive understanding of various types of cyber-attacks and its classification associated with both Opera-tion Technology (OT) and Information Technology (IT). This paper presents a comprehensive review of existing cyberattack taxonomies available in the literature and evaluates these taxonomies based on defined criteria.

/pdf/a-review-towards-practical-attack-taxonomy-for-industrial-58yqy0bd53.pdf

Qais Saif Qassim

Papers

Visualization in Faceted Search Engine - A Review

An Anomaly Detection Technique for Deception Attacks in Industrial Control Systems

Machine learning-based telemedicine framework to prioritize remote patients with multi-chronic diseases for emergency healthcare services

A review: Towards practical attack taxonomy for industrial control systems

A Study on security vulnerabilities assessment and quantification in SCADA systems