Search results for "Server"

showing 10 items of 586 documents

Simulation-Based Performance Study of e-Commerce Web Server System – Results for FIFO Scheduling

2013

The chapter concerns the issue of overloaded Web server performance evaluation using a simulation-based approach. We focus on a Business-to-Consumer (B2C) environment and consider server performance both from the perspective of computer system efficiency and e-business profitability. Results of simulation experiments for the Web server system under First-In-First-Out (FIFO) scheduling are discussed. Much attention has been paid to the analysis of the impact of a limited server system capacity on business-related performance metrics.

Web serverComputer sciencebusiness.industryE-commercecomputer.software_genreFair-share schedulingScheduling (computing)Operating systemProfitability indexbusinessServer systemWeb server performancecomputerSimulation based
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Analysis of Aggregated Bot and Human Traffic on E-Commerce Site

2014

A significant volume of Web traffic nowadays can be attributed to robots. Although some of them, e.g., search-engine crawlers, perform useful tasks on a website, others may be malicious and should be banned. Consequently, there is a growing need to identify bots and to characterize their behavior. This paper investigates the share of bot-generated traffic on an e-commerce site and studies differences in bots' and humans' session-based traffic by analyzing data recorded in Web server log files. Results show that both kinds of sessions reveal different characteristics, including the session duration, the number of pages visited in session, the number of requests, the volume of data transferre…

Web serverComputer sciencebusiness.industryVolume (computing)Static web pageE-commercecomputer.software_genreWorld Wide WebWeb trafficWeb pageSession (computer science)businessSite mapcomputer
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Anomaly Detection from Network Logs Using Diffusion Maps

2011

The goal of this study is to detect anomalous queries from network logs using a dimensionality reduction framework. The fequencies of 2-grams in queries are extracted to a feature matrix. Dimensionality reduction is done by applying diffusion maps. The method is adaptive and thus does not need training before analysis. We tested the method with data that includes normal and intrusive traffic to a web server. This approach finds all intrusions in the dataset. peerReviewed

Web serverComputer scienceintrusion detectionDimensionality reductionFeature matrixDiffusion mapdiffusion maphyökkäyksen havaitseminenIntrusion detection systemcomputer.software_genreanomaly detectionpoikkeavuuden havaitseminendiffuusiokarttakoneoppiminenAnomaly detectionData miningtiedonlouhintan-grammitcomputern-grams
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HTTP-level e-commerce data based on server access logs for an online store

2020

Abstract Web server logs have been extensively used as a source of data on the characteristics of Web traffic and users’ navigational patterns. In particular, Web bot detection and online purchase prediction using methods from artificial intelligence (AI) are currently key areas of research. However, in reality, it is hard to obtain logs from actual online stores and there is no common dataset that can be used across different studies. Moreover, there is a lack of studies exploring Web traffic over a longer period of time, due to the unavailability of long-term data from server logs. The need to develop reliable models of Web traffic, Web user navigation, and e-customer behaviour calls for …

Web serverDatabaseaccess logComputer Networks and CommunicationsComputer sciencebusiness.industry020206 networking & telecommunicationselectronic commerce02 engineering and technologyE-commerceWeb trafficcomputer.software_genreWeb trafficWeb serveronline store0202 electrical engineering electronic engineering information engineeringKey (cryptography)020201 artificial intelligence & image processingHTTP trafficUnavailabilitybusinesscomputerData ArticleComputer Networks
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The Myths of and Solutions for Android OS Controlled and Secure Environment

2015

<p class="R-AbstractKeywords"><span lang="EN-US">Android is the most popular mobile operating system nowadays both for smartphones and tablets. This fact creates many not fully recognized risks. Often even advanced users naive think that using antivirus software, firewall, encryption, updates, as well as avoiding potentially risky sites and applications are enough for security. This list is not full, but nevertheless each its item in most cases only conceals an illusion of reaching the security. Authors have summarized and pointed out several actual Android security issues and have proposed a number of possible solutions.</span></p><p class="R-AbstractKeywords"&gt…

Web serverEngineeringbusiness.industryMobile computingBring your own devicecomputer.software_genreComputer securityEncryptionWorld Wide WebServerMalwareWeb contentAndroid (operating system)businesscomputerAndroid; mobile computing; security; BYOD; smartphones; ICTEnvironment. Technology. Resources.
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Web Monitoring System and Gateway for Serial Communication PLC

2012

Abstract An industrial process requires interacting with the rest of the plant, being able to exchange data with other devices and monitoring systems in order to optimize production, reporting information and providing control capabilities to distant users. Internet, and, especially web browsers are an excellent tool to provide information for remote users, allowing not only monitoring but also controlling the industrial process as an SCADA software or HMI system. The proposed system does not need specific proprietary software and its associated license costs. In this work, a webserver system is implemented under a Freescale microcontroller, acting as a gateway for a simple PLC with single …

Web serverEngineeringbusiness.industrySerial communicationComputerApplications_COMPUTERSINOTHERSYSTEMSGeneral MedicineGateway (computer program)Modular designcomputer.software_genreSoftwareSCADAEmbedded systemWeb pageOperating systemThe InternetbusinesscomputerIFAC Proceedings Volumes
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Modeling a non-stationary bots’ arrival process at an e-commerce Web site

2017

Abstract The paper concerns the issue of modeling and generating a representative Web workload for Web server performance evaluation through simulation experiments. Web traffic analysis has been done from two decades, usually based on Web server log data. However, while the character of the overall Web traffic has been extensively studied and modeled, relatively few studies have been devoted to the analysis of Web traffic generated by Internet robots (Web bots). Moreover, the overwhelming majority of studies concern the traffic on non e-commerce websites. In this paper we address the problem of modeling a realistic arrival process of bots’ requests on an e-commerce Web server. Based on real…

Web serverGeneral Computer ScienceComputer scienceInternet robotReal-time computing02 engineering and technologyE-commercecomputer.software_genreSession (web analytics)Theoretical Computer ScienceWeb traffic characterizationWeb serverWeb traffic0202 electrical engineering electronic engineering information engineeringTraffic generation modelWeb traffic analysis and modelingbusiness.industryComputerSystemsOrganization_COMPUTER-COMMUNICATIONNETWORKS020206 networking & telecommunicationsWeb botHeavy-tailed distributionModeling and SimulationHeavy-tailed distribution020201 artificial intelligence & image processingThe InternetWeb log analysis softwareLog file analysisData miningbusinessRegression analysiscomputerJournal of Computational Science
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Online Web Bot Detection Using a Sequential Classification Approach

2019

A significant problem nowadays is detection of Web traffic generated by automatic software agents (Web bots). Some studies have dealt with this task by proposing various approaches to Web traffic classification in order to distinguish the traffic stemming from human users' visits from that generated by bots. Most of previous works addressed the problem of offline bot recognition, based on available information on user sessions completed on a Web server. Very few approaches, however, have been proposed to recognize bots online, before the session completes. This paper proposes a novel approach to binary classification of a multivariate data stream incoming on a Web server, in order to recogn…

Web serverHTTP request analysis; Internet security; Machine learning; Neural networks; Sequential classification; Web bot detectionSettore INF/01 - InformaticaWeb bot detectionComputer sciencebusiness.industrySequential classification020206 networking & telecommunications02 engineering and technologyMachine learningcomputer.software_genreInternet securitySession (web analytics)Task (computing)Web trafficMachine learning0202 electrical engineering electronic engineering information engineeringHTTP request analysis020201 artificial intelligence & image processingArtificial intelligencebusinesscomputerNeural networksInternet security2018 IEEE 20th International Conference on High Performance Computing and Communications; IEEE 16th International Conference on Smart City; IEEE 4th International Conference on Data Science and Systems (HPCC/SmartCity/DSS)
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Efficient on-the-fly Web bot detection

2021

Abstract A large fraction of traffic on present-day Web servers is generated by bots — intelligent agents able to traverse the Web and execute various advanced tasks. Since bots’ activity may raise concerns about server security and performance, many studies have investigated traffic features discriminating bots from human visitors and developed methods for automated traffic classification. Very few previous works, however, aim at identifying bots on-the-fly, trying to classify active sessions as early as possible. This paper proposes a novel method for binary classification of streams of Web server requests in order to label each active session as “bot” or “human”. A machine learning appro…

Web serverInformation Systems and ManagementComputer scienceInternet robot02 engineering and technologyMachine learningcomputer.software_genreUsage dataManagement Information SystemsIntelligent agentEarly decision; Internet robot; Machine learning; Neural network; Real-time bot detection; Sequential analysis; Web botArtificial IntelligenceReal-time bot detection020204 information systemsMachine learning0202 electrical engineering electronic engineering information engineeringFalse positive paradoxSequential analysisSession (computer science)business.industryWeb botNeural networkEarly decisionTraffic classificationBinary classification020201 artificial intelligence & image processingArtificial intelligencebusinesscomputerClassifier (UML)SoftwareKnowledge-Based Systems
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Feature selection: A multi-objective stochastic optimization approach

2020

The feature subset task can be cast as a multiobjective discrete optimization problem. In this work, we study the search algorithm component of a feature subset selection method. We propose an algorithm based on the threshold accepting method, extended to the multi-objective framework by an appropriate definition of the acceptance rule. The method is used in the task of identifying relevant subsets of features in a Web bot recognition problem, where automated software agents on the Web are identified by analyzing the stream of HTTP requests to a Web server.

Web serverLinear programmingthreshold acceptingComputer scienceFeature extractionFeature selectionstochastic optimizationcomputer.software_genreMulti-objective optimizationfeature selection; multiobjective optimization; stochastic optimization; subset selection; threshold acceptingfeature selectionsubset selectionFeature (computer vision)Search algorithmStochastic optimizationmultiobjective optimizationData miningcomputer
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