In this work, we describe an automated ML-based measurement data anomaly mitigation technique that uses regression, clustering, deep learning techniques as a ...

This paper discusses the multiple ML algorithms for data anomaly detection, the basis of software design considerations, open-source software components, and ...

Oct 8, 2024 · In this paper, we introduce an integrated solution to conceal the rate information of wireless transmissions while simultaneously boosting the ...

This paper discusses the multiple ML algorithms for data anomaly detection, the basis of software design considerations, open-source software components, and ...

In this study, we address the prevalent issue of data integrity in network traffic datasets, which are instrumental in developing machine learning (ML) models ...

Machine-learning (ML) based tools can provide a reliable interpretation of the deluge of data obtained from the field. For the decision-makers to ensure ...

This investigation examines the role of machine learning (ML) in improving the safety of digital infrastructure by examining network anomaly detection and ...

Oct 4, 2024 · This study focuses on energy systems (ES), critical infrastructures vulnerable to disruptions from natural disasters, cyber attacks, equipment failures, or ...

Jan 25, 2023 · State and local agencies can identify cyberthreats through anomaly detection. Machine learning can enhance the identification of malicious activity on ...

detection of anomalies in Cyber-Physical Systems (CPS) [14]. ML-based algorithms help in the detection of cyber-attacks as well as in differentiating ...