2013. Anomaly detection in the cloud: Detecting security incidents via machine learning. In Trustworthy Eternal Systems via Evolving Software, Data and Knowledge, Moschitti, A. & Plank, B., eds, volume 379 of Communications in Computer and Information Science, 103-116. Springer Berlin Heidelberg....
Be that as it may, there are a plenty of security worries in cloud computing which still should be handled (e.g., confidentiality, auditability and Privileged User Access). To recognize and avoid such issues, the Intrusion Detection System (IDS) and Intrusion Prevention System (IPS) are ...
Anomaly Detection in Cloud Using Hexabullus Optimisation-Enabled Fuzzy Classifier with Smart Contract-Enabled Secure Communication Cloud computing forms a mainstream in the emerging field of Internet of Things (IoT) networks, which provides high storage and access to data whenever need... F Sammy,SMC...
Anomaly detection on large-scale, complex and dynamic data is an essential service that is vital to enable smart functionality in most systems. Increased reliance on cloud computing infrastructures to process such data pose critical challenges with regard to security and privacy. This paper introduces...
Cloud computing is a completely internet dependent technology where client data are stored and maintained in the data center of a cloud provider like Google, Amazon, Apple Inc., Microsoft etc. The Anomaly Detection System is one of the Intrusion Detection techniques. It's an area in the cloud...
Based on the system analysis of the whole process of log processing including log analysis, feature extraction, anomaly detection, prediction and evaluation and real-time reliability, the ensemble learning model is applied to analyzing the massive system logs in this paper. The anomaly detection for...
Our scheme would serve as a novel anomaly detection tool to improve security framework in VM management for cloud computing. 展开 关键词: Anomaly detection Security Virtualization DOI: 10.1016/j.future.2015.06.005 被引量: 17 年份: 2016
This paper proposes a framework for time series generation built to investigate anomaly detection in cloud microservices. In the field of cloud computing, ensuring the reliability of microservices is of paramount concern and yet a remarkably challenging task. Despite the large amount of research in th...
Continuous cost monitoring and anomaly detection is especially important in the dynamic environment of cloud computing. Anomaly detection for cloud cost management works by analyzing historical data for a specific metric and identifies patterns and trends in order to build models of predictable outcomes....
Anomaly detection in the CERN OpenStack cloud is a challenging task due to the large scale of the computing infrastructure and, consequently, the large volume of monitoring data to analyse. The current solution to spot anomalous servers in the cloud infrastructure relies on a threshold-based alarmi...