Search results for "Sequential classification"

showing 2 items of 2 documents

A Quantum-Inspired Classifier for Early Web Bot Detection

2022

This paper introduces a novel approach, inspired by the principles of Quantum Computing, to address web bot detection in terms of real-time classification of an incoming data stream of HTTP request headers, in order to ensure the shortest decision time with the highest accuracy. The proposed approach exploits the analogy between the intrinsic correlation of two or more particles and the dependence of each HTTP request on the preceding ones. Starting from the a-posteriori probability of each request to belong to a particular class, it is possible to assign a Qubit state representing a combination of the aforementioned probabilities for all available observations of the time series. By levera…

Settore INF/01 - InformaticaComputer Networks and Communicationsbot detectionData modelsTime series analysisearly decisionquantum-inspired computingTime measurementCorrelationCostsmultinomial classificationPredictive modelsbot detection; Correlation; Costs; Data models; early decision; multinomial classification; multivariate sequence classification; Predictive models; quantum-inspired computing; sequential classification; Task analysis; Time measurement; Time series analysis;multivariate sequence classificationTask analysisSafety Risk Reliability and Qualitybot detection; Correlation; Costs; Data models; early decision; multinomial classification; multivariate sequence classification; Predictive models; quantum-inspired computing; sequential classification; Task analysis; Time measurement; Time series analysissequential classification
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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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