Search results for "Intrusion"

showing 10 items of 159 documents

Machine Learning Techniques for Intrusion Detection: A Comparative Analysis

2016

International audience; With the growth of internet world has transformed into a global market with all monetary and business exercises being carried online. Being the most imperative resource of the developing scene, it is the vulnerable object and hence needs to be secured from the users with dangerous personality set. Since the Internet does not have focal surveillance component, assailants once in a while, utilizing varied and advancing hacking topologies discover a path to bypass framework " s security and one such collection of assaults is Intrusion. An intrusion is a movement of breaking into the framework by compromising the security arrangements of the framework set up. The techniq…

Computer scienceAnomaly-based intrusion detection system02 engineering and technologyIntrusion detection systemIDSMachine learningcomputer.software_genre[ INFO.INFO-CV ] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV][INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]Machine LearningResource (project management)Component (UML)0202 electrical engineering electronic engineering information engineeringROCSet (psychology)[ INFO.INFO-AI ] Computer Science [cs]/Artificial Intelligence [cs.AI]False Positivebusiness.industryACM[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]020206 networking & telecommunicationsPrecisionObject (computer science)True PositiveOutlier020201 artificial intelligence & image processingThe InternetArtificial intelligenceData miningbusinesscomputer
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Combining conjunctive rule extraction with diffusion maps for network intrusion detection

2013

Network security and intrusion detection are important in the modern world where communication happens via information networks. Traditional signature-based intrusion detection methods cannot find previously unknown attacks. On the other hand, algorithms used for anomaly detection often have black box qualities that are difficult to understand for people who are not algorithm experts. Rule extraction methods create interpretable rule sets that act as classifiers. They have mostly been combined with already labeled data sets. This paper aims to combine unsupervised anomaly detection with rule extraction techniques to create an online anomaly detection framework. Unsupervised anomaly detectio…

Computer scienceAnomaly-based intrusion detection systemNetwork securityintrusion detectiontunkeutumisen havaitseminenFeature extractionDiffusion mapdiffusion mapIntrusion detection systemMachine learningcomputer.software_genrepoikkeavuuden havaitseminenBlack boxtiedon louhintan-grammiCluster analysista113Training setrule extractionbusiness.industryn-gramanomaly detectiondiffuusiokarttakoneoppiminensääntöjen erottaminenAnomaly detectionArtificial intelligenceData miningtiedonlouhintabusinesscomputer2013 IEEE Symposium on Computers and Communications (ISCC)
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Estimating Accuracy of Mobile-Masquerader Detection Using Worst-Case and Best-Case Scenario

2006

In order to resist an unauthorized use of the resources accessible through mobile terminals, masquerader detection means can be employed. In this paper, the problem of mobile-masquerader detection is approached as a classification problem, and the detection is performed by an ensemble of one-class classifiers. Each classifier compares a measure describing user behavior or environment with the profile accumulating the information about past behavior and environment. The accuracy of classification is empirically estimated by experimenting with a dataset describing the behavior and environment of two groups of mobile users, where the users within groups are affiliated with each other. It is as…

Computer scienceMobile computingAnomaly detectionIntrusion detection systemData miningFalse rejectioncomputer.software_genrecomputerClassifier (UML)Similitude
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Evaluation of Ensemble Machine Learning Methods in Mobile Threat Detection

2017

The rapid growing trend of mobile devices continues to soar causing massive increase in cyber security threats. Most pervasive threats include ransom-ware, banking malware, premium SMS fraud. The solitary hackers use tailored techniques to avoid detection by the traditional antivirus. The emerging need is to detect these threats by any flow-based network solution. Therefore, we propose and evaluate a network based model which uses ensemble Machine Learning (ML) methods in order to identify the mobile threats, by analyzing the network flows of the malware communication. The ensemble ML methods not only protect over-fitting of the model but also cope with the issues related to the changing be…

Computer scienceintrusion detection0211 other engineering and technologiesDecision tree02 engineering and technologycomputer.software_genreComputer securitymobiililaitteet0202 electrical engineering electronic engineering information engineeringsupervised machine learningSoarAndroid (operating system)tietoturvata113021110 strategic defence & security studiesta213business.industrymobile threatsensemble methods020206 networking & telecommunicationsFlow networkEnsemble learninganomaly detectionmachine learningkoneoppiminenMalwareThe InternetbusinesscomputerMobile device
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Assessment of Deep Learning Methodology for Self-Organizing 5G Networks

2019

In this paper, we present an auto-encoder-based machine learning framework for self organizing networks (SON). Traditional machine learning approaches, for example, K Nearest Neighbor, lack the ability to be precisely predictive. Therefore, they can not be extended for sequential data in the true sense because they require a batch of data to be trained on. In this work, we explore artificial neural network-based approaches like the autoencoders (AE) and propose a framework. The proposed framework provides an advantage over traditional machine learning approaches in terms of accuracy and the capability to be extended with other methods. The paper provides an assessment of the application of …

Computer scienceintrusion detection5G-tekniikka02 engineering and technologyIntrusion detection systemself-organizing networks (SON)Machine learningcomputer.software_genrelcsh:Technologyk-nearest neighbors algorithmself-organizing networkslcsh:Chemistryautoencoder (AE)deep learning (DL)mobility load balancing0202 electrical engineering electronic engineering information engineeringGeneral Materials ScienceInstrumentationlcsh:QH301-705.5Fluid Flow and Transfer ProcessesautoencoderArtificial neural networkbusiness.industrylcsh:Tmobility load balancing (MLB)Process Chemistry and TechnologyDeep learningGeneral Engineeringdeep learning020206 networking & telecommunicationsSelf-organizing networkLoad balancing (computing)021001 nanoscience & nanotechnologyAutoencoderlcsh:QC1-999Computer Science Applicationscell outage detectionlcsh:Biology (General)lcsh:QD1-999lcsh:TA1-2040Cellular networkArtificial intelligence0210 nano-technologybusinesslcsh:Engineering (General). Civil engineering (General)computerlcsh:Physics5G
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On the Robust Synthesis of Logical Consensus Algorithms for Distributed Intrusion Detection

2013

We introduce a novel consensus mechanism by which the agents of a network can reach an agreement on the value of a shared logical vector function depending on binary input events. Based on results on the convergence of finite--state iteration systems, we provide a technique to design logical consensus systems that minimize the number of messages to be exchanged and the number of steps before consensus is reached, and that can tolerate a bounded number of failed or malicious agents. We provide sufficient joint conditions on the input visibility and the communication topology for the method's applicability. We describe the application of our method to two distributed network intrusion detecti…

Consensus algorithmTheoretical computer scienceComputer scienceDistributed computingVisibility (geometry)Binary numberValue (computer science)Topology (electrical circuits)Computer Science::Multiagent SystemsSettore ING-INF/04 - AutomaticaControl and Systems EngineeringConsensus distributed algorithms intrusion detection security.Bounded functionConvergence (routing)Electrical and Electronic EngineeringVector-valued function
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One dimensional consolidation of Opalinus Clay from shallow depth

2017

First experimental results on Opalinus Clay from shallow depth (< 30 m depth) are presented and compared to results on cores from Mont Terri Underground Rock Laboratory (~ 300 m depth). Samples were tested in one dimensional condition using an advanced experimental technique. The samples from the two sites show similar properties in terms of geotechnical characterization and one dimensional compressibility/swelling indexes, despite the different source depths.

Consolidation (soil)MineralogyOverburden pressureVoid ratioPore water pressureSoilParticle-size distributionSoil waterCompressibilityShalesLaboratory TestingMercury intrusion porosimetryOpalinus ClayGeology
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Consequências mal adaptativas de invasões mentais com conteúdos relacionados a transtornos obsessivos, dismórficos, hipocondríacos e alimentares: dif…

2021

Unwanted mental intrusions (UMIs) with contents related to Obsessive-Compulsive Disorder (OCD), Body Dysmorphic Disorder (BDD), Illness Anxiety Disorder (IAD), and Eating Disorders (EDs) are highly prevalent, independently of the cultural and/or social context. Cognitive-behavioral explanations for these disorders postulates that the escalation from common UMIs to clinically relevant symptoms depends on the maladaptive consequences (i.e., emotions, appraisals, and control strategies) of experiencing UMIs. This study examines, from a cross-cultural perspective, the cognitive-behavioral postulates of the maladaptive consequences of having UMIs.Non-clinical 1,473 participants from Europe, the …

Cross-cultural study; Cross-sectional study; Eating disorders; Illness anxiety; Obsessive-Compulsive spectrum disorders; Unwanted mental intrusionsUnwanted mentalCross-sectional studyIntrusionsUnwanted mental intrusionsIllness anxiety disorderObsessive-Compulsivemental disordersmedicineCross-culturalCross-cultural studyEstudio transculturalCross-sectional studyTrastornos del espectro obsesivo-compulsivoIllness anxietyPerspective (graphical)Social environmentmedicine.diseaseEstudio transversalClinical PsychologyEating disordersAnsiedad por enfermedadTrastornos alimentariosObsessive-Compulsive spectrum disordersSpectrum disordersBody dysmorphic disorderEating disordersIntrusiones mentales no deseadasOriginal ArticlePsychologyClinical psychology
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Homework practices: role conflicts concerning parental involvement

2016

ABSTRACTThis article on hand discusses results of an ethnographic study which aims to perform a detailed description of practices of doing homework in a domestic environment. Based on the international state of research, first the question and the methodical approach will be explained, subsequently the role conflicts and stress ratios developed while doing homework in a family environment will be presented on the basis of two contrasting cases. To conclude, the homework-linked intrusion of school into familiar surroundings, regarding the parental involvement in contradictory requirements, will be analysed.

Cultural Studies05 social sciences050301 educationRole conflictEducationGender StudiesIntrusionDomestic environmentPedagogy0501 psychology and cognitive sciencesVideo technologySociology0503 educationSocial psychology050104 developmental & child psychologyEthnography and Education
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Tooth-Implant connection: A bibliographic review

2008

The aim of this study was to carry out a bibliographic review of all available literature addressing the issue of whether or not the connection of teeth to implants by means of a prosthesis is a viable treatment alternative. Twenty articles from a variety of sources were analyzed and classified in order to draw conclusions. Articles were classified by type and an analysis was made of the different variables considered in each study, obtaining percentages of implant survival ranging from 84.4% to 100%, prosthetic complications ranging from 80% to 90%, and the incidence of dental intrusion ranging from 0 to 5.6%. Biomechanical studies: Some articles studied models in order to assess different…

Dental Implantsmedicine.medical_specialtybusiness.industrymedicine.medical_treatmentDentistry:CIENCIAS MÉDICAS [UNESCO]ProsthesisConnection (mathematics)SurgeryDental ImplantationIntrusionOtorhinolaryngologyOsseointegrationUNESCO::CIENCIAS MÉDICASmedicineIncreased stressHumansPeriodontal fiberSurgeryPrimary treatmentImplantNatural toothbusinessToothGeneral DentistryMedicina Oral Patología Oral y Cirugia Bucal
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