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Learning to detect abnormal semantic web data

Yang Yu, Xingjian Zhang, Jeff Heflin
2011 Proceedings of the sixth international conference on Knowledge capture - K-CAP '11  
To detect incorrect data, ideally we can directly learn characteristics of them. But incorrect data have too many forms.  ...  Recently some works [1, 2, 3, 4] began to focus on the quality of Semantic Web data.  ... 
doi:10.1145/1999676.1999713 dblp:conf/kcap/YuZH11 fatcat:7znnduqkvjhkbfrjppuaaj6ahy

Prediction and Visual Intelligence Platform for Detection of Irregularities and Abnormal Behaviour (short paper)

Konstantinos P. Demestichas, Theodoros Alexakis, Nikolaos Peppes, Konstantina Remoundou, Ioannis V. Loumiotis, Wilmuth Müller, Konstantinos Avgerinakis
2020 Machine Learning for Trend and Weak Signal Detection in Social Networks and Social Media  
Nowadays, (cyber)criminals demonstrate an ever more increasing resolve to exploit new technology so to achieve their unlawful purposes.  ...  In this light, the authors introduce an innovative platform that provides near real-time advanced social behavior analytics using irregularities detection based on historical patterns.  ...  Thus, the module can extract useful patterns and hidden relationships among different datasets that can lead to trends discovery and abnormal behaviour detection.  ... 
dblp:conf/twsdetection/DemestichasAPRL20 fatcat:raefp27rqjayvcqj7pvjgvlslm

An Improved Feature Extraction Approach for Web Anomaly Detection Based on Semantic Structure

Zishuai Cheng, Baojiang Cui, Tao Qi, Wenchuan Yang, Junsong Fu, Zhe-Li Liu
2021 Security and Communication Networks  
In recent years, various machine learning, deep learning, and transfer learning-based anomaly detection approaches have been developed to protect against Web attacks.  ...  Anomaly-based Web application firewalls (WAFs) are vital for providing early reactions to novel Web attacks.  ...  In the detection step, the method that classifies new HTTP request as normal or abnormal based on the semantic structure and learned model is proposed.  ... 
doi:10.1155/2021/6661124 fatcat:fe5zuqvxqvgujeqkxpfbdromrm

Towards a Data Semantics Management System for Internet Traffic

Bassem Mokhtar, Mohamed Eltoweissy
2014 2014 6th International Conference on New Technologies, Mobility and Security (NTMS)  
In this paper, we propose a Data Semantics Management System (DSMS) for learning Internet traffic data semantics to enable smarter semantics-driven networking operations.  ...  Our preliminary evaluation using real Internet traffic shows the efficacy of DSMS for learning behavior of normal and abnormal traffic data and for accurately detecting anomalies at low cost.  ...  Fig. 4 illustrates the processing time overhead of the DSMS's semantics reasoning model, using LDA, to recognize semantics of normal/abnormal flows and to detect running malicious flows and attacks accordingly  ... 
doi:10.1109/ntms.2014.6814054 dblp:conf/ntms/MokhtarE14 fatcat:kel5edhy2jhtpcjmosbxder7li

A Review Analysis on Anomaly Detection Using Data Mining Techniques in Social Networking

Samiksha Nehra
2017 International Journal for Research in Applied Science and Engineering Technology  
The paper displays an audit of number of data mining approaches used to recognize anomalies. I.  ...  INTRODUCTION Anomaly detection alludes to recognizing designs in a given informational collection that don't fit in with a set up typical conduct.  ...  Finding the evolvement of Semantic Web (SW) upgrades the learning of the noticeable quality of Semantic Web Community and imagines the blend of the Semantic Web.  ... 
doi:10.22214/ijraset.2017.10054 fatcat:77ywm6dnfjap7aazirtv3wrcoy

Connecting Web Event Forecasting with Anomaly Detection: A Case Study on Enterprise Web Applications Using Self-Supervised Neural Networks [article]

Xiaoyong Yuan, Lei Ding, Malek Ben Salem, Xiaolin Li, Dapeng Wu
2020 arXiv   pre-print
data, and sequence embedding techniques to integrate contextual events and capture dependencies among web events.  ...  DeepEvent includes three key features: web-specific neural networks to take into account the characteristics of sequential web events, self-supervised learning techniques to overcome the scarcity of labeled  ...  Many supervised machine learning provides have been used to detect anomaly for web applications by providing a binary prediction of normal or abnormal web requests learning from the historical data.  ... 
arXiv:2008.13707v2 fatcat:dkfqyqgxonethnrrhaojqfz2qi

Detecting abnormal data for ontology based information integration

Yang Yu, Jeff Heflin
2011 2011 International Conference on Collaboration Technologies and Systems (CTS)  
To better support information integration on Semantic Web data with varying degrees of quality, this paper proposes an approach to detect triples which reflect some sort of error.  ...  We detect such "abnormal triples" by learning probabilistic rules from the reference data and checking to what extent these rules agree with the triples.  ...  A typical use case could be that the system attempts to integrate or query over some new Semantic Web data sources.  ... 
doi:10.1109/cts.2011.5928721 dblp:conf/cts/YuH11 fatcat:mqeooun7fnbafpj7i7pp3ac7tu

Automated Detection of Non-Relevant Posts on the Russian Imageboard "2ch": Importance of the Choice of Word Representations [chapter]

Amir Bakarov, Olga Gureenkova
2017 Lecture Notes in Computer Science  
This study considers the problem of automated detection of non-relevant posts on Web forums and discusses the approach of resolving this problem by approximation it with the task of detection of semantic  ...  To make the comparison, we propose a dataset of semantic relatedness with posts from one of the most popular Russian Web forums, imageboard "2ch", which has challenging lexical and grammatical features  ...  , typos and abnormal grammar.  ... 
doi:10.1007/978-3-319-73013-4_2 fatcat:ilwrgobmfra7bewou2yy5snpwq

Combined Machine Learning and Semantic Modelling for Situation Awareness and Healthcare Decision Support [chapter]

Amira Henaien, Hadda Ben Elhadj, Lamia Chaari Fourati
2020 Lecture Notes in Computer Science  
The reasoner engine is based on a scalable set of inference rules cohesively integrated with a ML (Machine Learning) algorithm to ensure predictive analytic and preventive personalized health services.  ...  (Semantic Sensors Network)/SOSA (Sensor, Observation, Sample and Actuator) and ICNP (International Classification Nursing Practices) ontologies.  ...  To resume any abnormal value for a vital sign, we define the following SWRL 2 rule (GM ): icnp : Learning and Prediction Reasoning ML Engine (MLE) learns from previous patient's detected alarms to produce  ... 
doi:10.1007/978-3-030-51517-1_16 fatcat:cikanbgyjrdwpottfremmpdsou

Variance analysis and handling of Clinical Pathway: An overview of the state of knowledge

Gang Du, Liyuan Huang, Mengwei Zhou
2020 IEEE Access  
Moreover, this paper conducts a bibliometric analysis to visualize the clinical pathway variance research.  ...  In variance analysis and handling, there are a lot of imprecise knowledge and fuzzy relations to be reasoned with knowledge of different domains.  ...  From 2016 to 2019, she has participated in the research of medical operation management.  ... 
doi:10.1109/access.2020.3020151 fatcat:pe54rtkionfopgz6awtkx7kuzu

Automating Penetration Testing Within Ambiguous Testing Environment

Lim Kah Seng, Norafida Ithnin, Syed Zainudeen Mohd Shaid
2018 International Journal of Innovative Computing  
Thus, in this paper, the state-of-the-art of black box web application security scanner is systematically reviewed, to investigate the approaches for detecting web application vulnerability in an ambiguous  ...  Web application security scanner is such kind of program that is designed to assess web application security automatically with penetration testing technique.  ...  Moreover, designing a sophisticated algorithm to input each data entry point with appropriate data is challenging due to the ambiguity of semantic of data entry points.  ... 
doi:10.11113/ijic.v8n3.180 fatcat:alfz4ftlnzau3d2czw7p625ika

A Rule-Based Approach to Address Semantic Accuracy Problems on Linked Data

Leandro Mendoza
2014 International Semantic Web Conference  
"Dependency rules" concept is inspired in "data dependency" concept (well-known in relational databases domain and already used in [18] to detect abnormal data in RDF Graphs).  ...  [2] defined the Semantic Web (SW) as an extension of the current Web in which information is given well-defined meaning through the use of common standards and technologies to facilitate the sharing  ... 
dblp:conf/semweb/Mendoza14 fatcat:gu2u34vkwrcqlnsm6rnjogy4ie

Enhanced Host-Based Intrusion Detection Using System Call Traces

Yaqoob S. Ikram Yaqoob S. Ikram
2019 journal of King Abdulaziz University Computing and Information Technology Sciences  
This provides high capability to detect zero-day attacks and also makes it flexible to cope with any environmental changes since it can learn quickly and incrementally without the need to rebuild the whole  ...  To the best of our knowledge, the obtained results of the proposed system are superior to all up-to-date published systems in terms of computational cost and learning time.  ...  Moreover, the detection technique should be precise enough to detect abnormalities.  ... 
doi:10.4197/comp.8-2.7 fatcat:tibnt64cljh4fgdhi5my47wzcy

Biologically-inspired Network "Memory" for Smarter Networking

Bassem Mokhtar, Mohamed Eltoweissy
2012 Proceedings of the 8th IEEE International Conference on Collaborative Computing: Networking, Applications and Worksharing  
NetMem provides associative access to data patterns and relevant derived semantics to enable enhancements in early anomaly detection, more accurate behavior prediction and satisfying QoS requirements with  ...  associative rule learning to recognize data patterns, and hidden Markov models for reasoning and extracting semantics clarifying normaVabnormal behavior.  ...  So, routers learn early semantics of their services and they limit resources assigned to abnormal flows. SM keeps learning data patterns at StM and it matches them with registered semantics.  ... 
doi:10.4108/icst.collaboratecom.2012.250508 dblp:conf/colcom/MokhtarE12 fatcat:zodrh6pbcrczllbqvyke4mes2i

Network "memory" system for enhanced network services

B. Mokhtar, M. Eltoweissy, H. El-Sayed
2013 2013 9th International Conference on Innovations in Information Technology (IIT)  
NetMem provides associative access to data patterns and relevant derived semantics to enable enhancements in decision making, QoS guarantees and utilization of resources, early anomaly detection, and more  ...  NetMem provides capabilities for semantics management through integrating data virtualization, cloud-like scalable storage, associative rule learning and predictive analytics.  ...  We show the capability of the bottleneck router to learn semantics of TCP service derived in NetMem to enhance the service's QoS by allocating required resources and to aid in detecting abnormal TCP flows  ... 
doi:10.1109/innovations.2013.6544387 fatcat:gjv7fkr7lndlnirlie4jpnaipy
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