Anomaly Detection Techniques in Data Mining—A Review

Lakshmi, K. N. V. S. K. Vijaya; Neema, N.; Muddasir, N. Mohammed; Prashanth, M. V.

doi:10.1007/978-981-15-0146-3_76

Cited by 2 publications

(1 citation statement)

References 8 publications

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“…While, anomaly-based detection techniques, seek to identify abnormalities in network traffic or system behaviour that could indicate the existence of malicious activity [72]. The anomalies could be created due to many factors, such as noise or phenomena that has a certain probability of being happened by certain conditions, which threatens the confidentiality, availability, and integration of data for an organization [73,74]. Therefore, anomalies are unusual behaviours triggered by a person/object that leave footsteps in the computing environment [75].…”

Section: Cyber Securitymentioning

confidence: 99%

Complex event processing for physical and cyber security in datacentres - recent progress, challenges and recommendations

et al. 2022

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A datacentre stores information and manages data access in fast and reliable manner. Failure of datacentre operation is not an option and can be catastrophic. Internet of things (IoT) devices in datacentre can automate management tasks and reduce human intervention and error. IoT devices can be used to manage many datacentre routine tasks such as monitoring physical infrastructure, updating software and configuration, monitoring network traffic, and automating alerting reports to respective authorities. The physical and cyber security of the datacentre can be handled by IoT technology by intrusion detection methods. By 2025, more than 25 billion things will be connected to the internet network, therefore massive data will be generated by different heterogeneous sources, and powerful processing engines such as complex event processing (CEP) are needed to handle such a fast and continuous stream of big data. The integration of machine learning (ML) and deep learning (DL) can enhance CEP by introducing new features such as automated rule extraction and self-healing mechanism. This study aims to provide an overview of CEP, as well as its features and potential for integration with IoT applications and ML/DL techniques. We provide a review of recent research works to highlight the capability and applicability of CEP technology to monitor physical facilities and cyber security in detail. This review also highlights several issues and challenges, and provides suggestions for future research. The highlighted insights and recommendations in this paper could raise efforts toward the development of future datacentres based on CEP technology.

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Section: Cyber Securitymentioning

confidence: 99%

Complex event processing for physical and cyber security in datacentres - recent progress, challenges and recommendations

et al. 2022

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Application of Data Mining Combined With K-Means Clustering Algorithm in Enterprises' Risk Audit

Rana

2024

Advances in Logistics, Operations, and Management Science

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The financial risk management mechanism of enterprises can be more complete through exploration in the application effect of data mining technology combined with K-means clustering algorithm in enterprise risk audit. Hence, K-means clustering algorithm is introduced to study the paperless status of electronic payment in the trading process of e-commerce enterprises. Additionally, a risk audit model of e-commerce enterprises is implemented based on K-means algorithm combined with Random Forest Light Gradient Boosting Machine (RF-LightGBM). In this model, the actual operation process of data preparation, data preprocessing, model construction, model application and evaluation are the payment flow in the transaction process of e-commerce enterprises by using big data analysis technology. Eventually, the performance of the model is evaluated by simulation.

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Anomaly Detection Techniques in Data Mining—A Review

Cited by 2 publications

References 8 publications

Complex event processing for physical and cyber security in datacentres - recent progress, challenges and recommendations

Complex event processing for physical and cyber security in datacentres - recent progress, challenges and recommendations

Application of Data Mining Combined With K-Means Clustering Algorithm in Enterprises' Risk Audit

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