Intelligent Data Analytics for Terror Threat Prediction : Architectures, Methodologies, Techniques and Applications /

"Intelligent data analytics for terror threat prediction is an emerging field of research at the intersection of information science and computer science, bringing with it a new era of tremendous opportunities and challenges due to plenty of easily available criminal data for further analysis....

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Main Authors: Pani, Subhendu Kumar, 1980-, editor 636870, Singh, Sanjay Kumar, 1963-, editor 636871, Garg, Lalit, 1977-, editor 636872, Pachori, Ram Bilas, editor 636873, Zhang, Xiaobo, editor 636874
Format: text
Language:eng
Published: Hoboken, NJ : John Wiley & Sons ; Beverly, MA : Scrivener Publishing LLC, 2021
Subjects:
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author Pani, Subhendu Kumar, 1980-, editor 636870
Singh, Sanjay Kumar, 1963-, editor 636871
Garg, Lalit, 1977-, editor 636872
Pachori, Ram Bilas, editor 636873
Zhang, Xiaobo, editor 636874
author_facet Pani, Subhendu Kumar, 1980-, editor 636870
Singh, Sanjay Kumar, 1963-, editor 636871
Garg, Lalit, 1977-, editor 636872
Pachori, Ram Bilas, editor 636873
Zhang, Xiaobo, editor 636874
author_sort Pani, Subhendu Kumar, 1980-, editor 636870
collection OCEAN
description "Intelligent data analytics for terror threat prediction is an emerging field of research at the intersection of information science and computer science, bringing with it a new era of tremendous opportunities and challenges due to plenty of easily available criminal data for further analysis. The aim of data analytics is to prevent threats before they happen using classical statistical issues, machine learning, artificial intelligence, rule induction methods, neural networks, fuzzy logic, and stochastic search methods on various data sources, including social media, GPS devices, video feed from street cameras; and license plate readers, travel and credit card records and the news media, as well as government and proprietary systems. Intelligent data analytics ensures efficient data mining techniques to solve criminal investigations. Prediction of future terrorist attacks according to city, type of attack, target and weapon, claim mode, and motive for attack through classification techniques will facilitate the decision-making process of security organizations so as to learn from previously stored attack information; and then rate the targeted sectors/areas accordingly for security measures. By using intelligent data analytics models with multiple levels of representation, raw to higher abstract level representation can be learned at each level of the system. Algorithms based on intelligent data analytics have demonstrated great performance in a variety of areas, including data visualization, data pre-processing (fusion, editing, transformation, filtering, and sampling), data engineering, database mining techniques, tools and applications, etc"--
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spelling KOHA-OAI-TEST:5932422024-04-16T07:25:28ZIntelligent Data Analytics for Terror Threat Prediction : Architectures, Methodologies, Techniques and Applications / Pani, Subhendu Kumar, 1980-, editor 636870 Singh, Sanjay Kumar, 1963-, editor 636871 Garg, Lalit, 1977-, editor 636872 Pachori, Ram Bilas, editor 636873 Zhang, Xiaobo, editor 636874 textHoboken, NJ : John Wiley & Sons ; Beverly, MA : Scrivener Publishing LLC,2021©2021eng"Intelligent data analytics for terror threat prediction is an emerging field of research at the intersection of information science and computer science, bringing with it a new era of tremendous opportunities and challenges due to plenty of easily available criminal data for further analysis. The aim of data analytics is to prevent threats before they happen using classical statistical issues, machine learning, artificial intelligence, rule induction methods, neural networks, fuzzy logic, and stochastic search methods on various data sources, including social media, GPS devices, video feed from street cameras; and license plate readers, travel and credit card records and the news media, as well as government and proprietary systems. Intelligent data analytics ensures efficient data mining techniques to solve criminal investigations. Prediction of future terrorist attacks according to city, type of attack, target and weapon, claim mode, and motive for attack through classification techniques will facilitate the decision-making process of security organizations so as to learn from previously stored attack information; and then rate the targeted sectors/areas accordingly for security measures. By using intelligent data analytics models with multiple levels of representation, raw to higher abstract level representation can be learned at each level of the system. Algorithms based on intelligent data analytics have demonstrated great performance in a variety of areas, including data visualization, data pre-processing (fusion, editing, transformation, filtering, and sampling), data engineering, database mining techniques, tools and applications, etc"--Includes bibliographical references and index.Rumor Detection and Tracing its Source to Prevent Cyber-Crimes on Social Media -- Internet of Things (IoT) and Machine to Machine (M2M) Communication Techniques for Cyber Crime Prediction -- Crime Predictive Model Using Big Data Analytics -- The Role of Remote Sensing and GIS in Military Strategy to Prevent Terror Attacks -- Text Mining for Secure Cyber Space -- Analyses on Artificial Intelligence Framework to Detect Crime Pattern -- A Biometric Technology-Based Framework for Tackling and Preventing Crimes -- Rule-Based Approach for Botnet Behavior Analysis -- Securing Biometric Framework with Cryptanalysis -- The Role of Big Data Analysis in Increasing the Crime Prediction and Prevention Rates -- Crime Pattern Detection Using Data Mining -- Attacks and Security Measures in Wireless Sensor Network -- Large Sensing Data Flows Using Cryptic Techniques -- Cyber-Crime Prevention Methodology."Intelligent data analytics for terror threat prediction is an emerging field of research at the intersection of information science and computer science, bringing with it a new era of tremendous opportunities and challenges due to plenty of easily available criminal data for further analysis. The aim of data analytics is to prevent threats before they happen using classical statistical issues, machine learning, artificial intelligence, rule induction methods, neural networks, fuzzy logic, and stochastic search methods on various data sources, including social media, GPS devices, video feed from street cameras; and license plate readers, travel and credit card records and the news media, as well as government and proprietary systems. Intelligent data analytics ensures efficient data mining techniques to solve criminal investigations. Prediction of future terrorist attacks according to city, type of attack, target and weapon, claim mode, and motive for attack through classification techniques will facilitate the decision-making process of security organizations so as to learn from previously stored attack information; and then rate the targeted sectors/areas accordingly for security measures. By using intelligent data analytics models with multiple levels of representation, raw to higher abstract level representation can be learned at each level of the system. Algorithms based on intelligent data analytics have demonstrated great performance in a variety of areas, including data visualization, data pre-processing (fusion, editing, transformation, filtering, and sampling), data engineering, database mining techniques, tools and applications, etc"--PSZ_JBTerrorismComputer communication systemsData miningURN:ISBN:9781119711094
spellingShingle Terrorism
Computer communication systems
Data mining
Pani, Subhendu Kumar, 1980-, editor 636870
Singh, Sanjay Kumar, 1963-, editor 636871
Garg, Lalit, 1977-, editor 636872
Pachori, Ram Bilas, editor 636873
Zhang, Xiaobo, editor 636874
Intelligent Data Analytics for Terror Threat Prediction : Architectures, Methodologies, Techniques and Applications /
title Intelligent Data Analytics for Terror Threat Prediction : Architectures, Methodologies, Techniques and Applications /
title_full Intelligent Data Analytics for Terror Threat Prediction : Architectures, Methodologies, Techniques and Applications /
title_fullStr Intelligent Data Analytics for Terror Threat Prediction : Architectures, Methodologies, Techniques and Applications /
title_full_unstemmed Intelligent Data Analytics for Terror Threat Prediction : Architectures, Methodologies, Techniques and Applications /
title_short Intelligent Data Analytics for Terror Threat Prediction : Architectures, Methodologies, Techniques and Applications /
title_sort intelligent data analytics for terror threat prediction architectures methodologies techniques and applications
topic Terrorism
Computer communication systems
Data mining
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