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              <text>Detection of cyber crime based on facial pattern enhancement using machine learning and image processing techniques</text>
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              <text>Cybercrime has several antecedents, including the rapid expansion of the internet and the wide variety of users around the world. It is now possible to use this data for a variety of purposes, whether for profit, non-profit, or purely for the benefit of the individual. As a result, tracing and detecting online acts of terrorism requires the development of a sound technique. Detection and prevention of cybercrime has been the subject of numerous studies and investigations throughout the years. An effective criminal detection system based on face recognition has been developed to prevent this from happening. Principle component analysis (PCA) and linear discriminant analysis (LDA) algorithms can be used to identify criminals based on facial recognition data. Quality, illumination, and vision are all factors that affect the efficiency of the system. The goal of this chapter is to improve accuracy in the facial recognition process for criminal identification over currently used conventional methods. Using proposed hybrid model, we can get the accuracy of 99.9.5%.  2022, IGI Global. All rights reserved.</text>
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              <text>Jujjuri R.D.; Tripathi A.K.; Chandrika V.S.; Majji S.; Prathap B.R.; Patnala T.R.</text>
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              <text>Using Computational Intelligence for the Dark Web and Illicit Behavior Detection, pp. 150-165.</text>
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              <text>IGI Global</text>
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              <text>2022-01-01</text>
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              <text>&lt;a href="https://doi.org/10.4018/978-1-6684-6444-1.ch008" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.4018/978-1-6684-6444-1.ch008&lt;/a&gt;
&lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85136912918&amp;amp;doi=10.4018%2F978-1-6684-6444-1.ch008&amp;amp;partnerID=40&amp;amp;md5=ad1474993aed6ccb8d3b76306c194305" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/inward/record.uri?eid=2-s2.0-85136912918&amp;amp;doi=10.4018%2f978-1-6684-6444-1.ch008&amp;amp;partnerID=40&amp;amp;md5=ad1474993aed6ccb8d3b76306c194305&lt;/a&gt;</text>
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              <text>Restricted Access</text>
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              <text>ISBN: 978-166846445-8; 978-166846444-1</text>
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              <text>Jujjuri R.D., PVP Siddhartha Institute of Technology, India; Tripathi A.K., KIET Group of Institutions, Delhi, India; Chandrika V.S., KPR Institute of Engineering and Technology, India; Majji S., Gokaraju Rangaraju Institute of Engineering and Technology, India; Prathap B.R., CHRIST (Deemed to be University), India; Patnala T.R., GITAM University, India</text>
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