Covert Network Analysis for Key Player Detection and Event Prediction Using a Hybrid Classifier
National security has gained vital importance due to increasing number of suspicious and terrorist events across the globe. Use of different subfields of information technology has also gained much attraction of researchers and practitioners to design systems which can detect main members which are...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2014-01-01
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| Series: | The Scientific World Journal |
| Online Access: | http://dx.doi.org/10.1155/2014/615431 |
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| _version_ | 1832564138524540928 |
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| author | Wasi Haider Butt M. Usman Akram Shoab A. Khan Muhammad Younus Javed |
| author_facet | Wasi Haider Butt M. Usman Akram Shoab A. Khan Muhammad Younus Javed |
| author_sort | Wasi Haider Butt |
| collection | DOAJ |
| description | National security has gained vital importance due to increasing number of suspicious and terrorist events across the globe. Use of different subfields of information technology has also gained much
attraction of researchers and practitioners to design systems which can detect main members which are actually responsible for such kind of events. In this paper, we present a novel method to predict key players from a covert network by applying a hybrid framework. The proposed system calculates certain centrality measures for each node in the network and then applies novel hybrid classifier for detection of key players. Our system also applies anomaly detection to predict any terrorist activity in order to help law enforcement agencies to destabilize the involved network. As a proof of concept, the proposed framework has been implemented and tested using different case studies including two publicly available datasets and one local network. |
| format | Article |
| id | doaj-art-ab6389bbfcfa4205a2931d2ab36c60dd |
| institution | Kabale University |
| issn | 2356-6140 1537-744X |
| language | English |
| publishDate | 2014-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | The Scientific World Journal |
| spelling | doaj-art-ab6389bbfcfa4205a2931d2ab36c60dd2025-02-03T01:11:42ZengWileyThe Scientific World Journal2356-61401537-744X2014-01-01201410.1155/2014/615431615431Covert Network Analysis for Key Player Detection and Event Prediction Using a Hybrid ClassifierWasi Haider Butt0M. Usman Akram1Shoab A. Khan2Muhammad Younus Javed3Department of Computer Engineering, College of Electrical and Mechanical Engineering, National University of Sciences and Technology, Islamabad 44000, PakistanDepartment of Computer Engineering, College of Electrical and Mechanical Engineering, National University of Sciences and Technology, Islamabad 44000, PakistanDepartment of Computer Engineering, College of Electrical and Mechanical Engineering, National University of Sciences and Technology, Islamabad 44000, PakistanDepartment of Computer Engineering, College of Electrical and Mechanical Engineering, National University of Sciences and Technology, Islamabad 44000, PakistanNational security has gained vital importance due to increasing number of suspicious and terrorist events across the globe. Use of different subfields of information technology has also gained much attraction of researchers and practitioners to design systems which can detect main members which are actually responsible for such kind of events. In this paper, we present a novel method to predict key players from a covert network by applying a hybrid framework. The proposed system calculates certain centrality measures for each node in the network and then applies novel hybrid classifier for detection of key players. Our system also applies anomaly detection to predict any terrorist activity in order to help law enforcement agencies to destabilize the involved network. As a proof of concept, the proposed framework has been implemented and tested using different case studies including two publicly available datasets and one local network.http://dx.doi.org/10.1155/2014/615431 |
| spellingShingle | Wasi Haider Butt M. Usman Akram Shoab A. Khan Muhammad Younus Javed Covert Network Analysis for Key Player Detection and Event Prediction Using a Hybrid Classifier The Scientific World Journal |
| title | Covert Network Analysis for Key Player Detection and Event Prediction Using a Hybrid Classifier |
| title_full | Covert Network Analysis for Key Player Detection and Event Prediction Using a Hybrid Classifier |
| title_fullStr | Covert Network Analysis for Key Player Detection and Event Prediction Using a Hybrid Classifier |
| title_full_unstemmed | Covert Network Analysis for Key Player Detection and Event Prediction Using a Hybrid Classifier |
| title_short | Covert Network Analysis for Key Player Detection and Event Prediction Using a Hybrid Classifier |
| title_sort | covert network analysis for key player detection and event prediction using a hybrid classifier |
| url | http://dx.doi.org/10.1155/2014/615431 |
| work_keys_str_mv | AT wasihaiderbutt covertnetworkanalysisforkeyplayerdetectionandeventpredictionusingahybridclassifier AT musmanakram covertnetworkanalysisforkeyplayerdetectionandeventpredictionusingahybridclassifier AT shoabakhan covertnetworkanalysisforkeyplayerdetectionandeventpredictionusingahybridclassifier AT muhammadyounusjaved covertnetworkanalysisforkeyplayerdetectionandeventpredictionusingahybridclassifier |