Anomaly detection in this type of data constitutes a challenging problem yet with numerous applications in science and engineering because anomaly scores come from the simultaneous consideration of the temporal and variable relationships. In this paper, we propose a clustering-based approach to detect ...
Hodge and Austin (2004) conducted a comparative analysis of anomaly detection algorithms published at that time, where they identified the underlying assumptions of each algorithm and highlighted their respective advantages and disadvantages. They categorized anomaly detection into three fundamental approaches:...
This paper focuses on anomaly detection of inappropriate behaviors in the complex human computer interaction process. A method is proposed. to identify the unauthorized users by analyzing their command sequence using clustering techniques. After calculating the frequency vector of the command sequence for...
This paper presents an anomaly detection approach based on clustering and classification for intrusion detection (ID). We use connections obtained from raw packet data of the audit trail as basic elements, then map the network connection records into 8 f
Online Clustering and Detective Cost Based Anomaly Detection Scheme for MANET基于在线聚类和检测成本的移动自组网异常检测 WANG Lei-chun,MA Chuan-xiang,王雷春,马传香 Keywords: Mobile ad hoc networks,Online clustering,Detective cost,Anomaly detection移动自组网,在线聚类,检测成本,异常检测 Full-Text Cite ...
In recent years, there has been a concerted effort to improve anomaly detection techniques, particularly in the context of high-dimensional, distributed clinical data. Analysing patient data within clinical settings reveals a pronounced focus on refining diagnostic accuracy, personalising treatment plans, ...
It is an important issue for the security of network to detect new intrusion attack and also to increase the detection rates and reduce false positive rates in Intrusion Detection System (IDS). Anomaly intrusion detection focuses on modeling normal behaviors and identifying significant deviations, whic...
In recent years, there has been a concerted effort to improve anomaly detection techniques, particularly in the context of high-dimensional, distributed clinical data. Analysing patient data within clinical settings reveals a pronounced focus on refining diagnostic accuracy, personalising treatment plans, ...
Wang Lifang, Han Xie. Anomaly Intrusion Detection Based on Quotient Space Granularity Clustering. Computer Applications and Software, 2010, 27(5) : 1911-1913 ( in Chinese) (王丽芳,韩燮. 基于商空间粒度聚类的异常入侵检测. 计算 机应用与软件, 2010, 27(5) : 1911-1913)...
WU Ning唱ning,ZHANG Jing.Factor analysis based anomaly detection and clustering[ J] .Decision Support Systems,2006,42 ( 1 ) :375唱 389.Ningning Wu,and Jing Zhang.Factor-analysis based anomaly detection and clustering. Decision Support . 2006...