[PDF] Top 20 detecting outliers in web based network traffic
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detecting outliers in web based network traffic
... of detecting input validation related attacks, they also note that there are a large number of techniques available to handle these kinds of ...of detecting workflow violation attacks called ...techniques ... See full document
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Outlier Detection in Secure Shell Honeypot using Particle Swarm Optimization Technique
... deployments, network communication has become vital and inevitable with human ...a network communication without security is ...through network. Parallel to this, network threats and attacks ... See full document
8
Machine learning approach for detection of nonTor traffic
... neural network (ANN) and Support vector machines (SVM) in terms of overall accuracy in detecting nonTor traffic in a Tor network traffic dataset data from the University of New ... See full document
6
Detecting Terror- Related Activities on the Web Using Neural Network
... The detection module performs on line monitoring of all traffic between the users being monitored and the web. The content of the pages they access is analyzed, transformed to a form of a vector. And added ... See full document
6
Machine learning approach for detection of non-Tor Traffic
... overlay network designed to provide privacy and anonymity over the internet for TCP based applications like ...the web firstly by sending a request anonymously to Tor routers from one of the ... See full document
24
Design and Optimization of Mobile Aggregation Networks.
... is based on data ...networking traffic generated by these devices. We focus on traffic protocols in which smartphones and lap- tops have distinct ...DHCP traffic behavior, and the implications ... See full document
142
Detecting Distributed Network Traffic Anomaly with Network-Wide Correlation Analysis
... existing network-wide detection methods are based on ...in detecting distributed network traffic ...in detecting relatively small distributed anomalous traffic from normal ... See full document
11
Security Issues on Composite Web Services
... for network intrusion detection ...signature based (NIDS) that sits behind the anomaly detection system, IDS preventing web-based attacks when implanted as web-application ...of ... See full document
5
Mobile Malware Detection through Analysis of Web Application Network Behavior
... for detecting meaningful deviations in a mobile application’s network traffic patterns that can be used for detecting an emerging type of malware with self- updating capabilities that allow ... See full document
5
Defending inimitable attacking Hostin web proxy based traffic
... traditional network security devices because attack traffic often mimic regular traffic and cannot be identified by network layer ...a Web application with legitimate requests in an ... See full document
7
DETECTING ANOMALOUS NETWORK TRAFFIC BASED ON CLASSIFYING FREQUENT TRAFFIC PATTERNS METHOD AND TOOLS
... 2.1 Change-Point Detection: Change-point detection is the difficulty of discovering time points at which properties of time-series data change. This includes a broad range of real world problems and has been vigorously ... See full document
8
A novel intrusion detection method based on OCSVM and K-means recursive clustering
... of detecting malicious network traffic in a SCADA (Supervisory Control and Data Acquisition) system, based on the combination of One-Class Support Vector Machine (OCSVM) with RBF kernel and ... See full document
10
A note on detecting statistical outliers in psychophysical data
... Abstract: This paper considers how best to identify statistical outliers when the underlying sampling distribution is unknown. Eight methods are described, and each is evaluated using Monte Carlo simulations of a ... See full document
7
A note on detecting statistical outliers in psychophysical data
... importance to positive and negative deviations from the cen- ter), whereas psychometric data are often skewed—since, for example, the process that lead to outlying data may lead to sensory abilities being ... See full document
9
Detecting and Revamping of X Outliers in Time Series Database
... ii Detection of X-Outliers using LCSSLongest Common Subsequence according to the known periodicity iii Revamping of X-Outliers iv The proposed method was tested with three different time[r] ... See full document
6
Constraint based Cluster Ensemble to Detect Outliers in Medical Datasets
... constraint based cluster ensemble framework to detect soft-outliers in combination with fuzzy approach ...constraint based cluster ensemble approach incorporates the prior domain knowledge of the ... See full document
7
Detecting global outliers from large distributed databases
... As the co-chairs of the FSKD 2012, we would like to thank all the committee members and reviewers for their timely help. We greatly appreciate the authors, speakers, invited session organizers, session chairs, and others ... See full document
8
DETECTION AND REMOVAL OF REDUNDANT WEB CONTENT THROUGH RECTANGULAR AND SIGNED APPROACH
... elements of 4- tuples from the above documents are indexed and similarity computation is performed using string comparison. If they are similar, then positive count is incremented else negative count is incremented. ... See full document
7
Loss Functions for Detecting Outliers in Panel Data: An Introduction
... Geographic information systems can be used with loss functions to find outliers. GIS is particularly helpful for finding geographic patterns in outliers. Map 1 at the end of this paper shows the q = – 1/2 ... See full document
9
NETWORK TRAFFIC ANALYSIS USING CLUSTERING
... ∈ Ant clustering needs some parameter values to be adjusted for good performance. The values α=0.5, k1=0.1 and k2=0.15 were adopted from an earlier work, where their use is also explained more carefully [1]. The value ... See full document
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