Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Faculty Publications Book Chapter Faculty Publications- Book Chapter Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Sathish, P.K.; Krishna, A.V.N. Title A name given to the resource SECURE VIDEO SURVEILLANCE SYSTEMS FOR PERSON REIDENTIFICATION USING ELLIPTIC CURVE CRYPTOGRAPHY Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2025 Source A related resource from which the described resource is derived Attacks on Artificial Intelligence: The New Facets of Cyber Ecospace;pp.105-120 Identifier An unambiguous reference to the resource within a given context <a href="https://www.scopus.com/pages/publications/105018284344?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105018284344?origin=resultslist</a> Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Sathish P.K., Department of Computer Science Engineering, CHRIST University, Bangalore, India; Krishna A.V.N., Department of Computer Science Engineering, CHRIST University, Bangalore, India Description An account of the resource This chapter explores the challenges associated with person reidentification in nonoverlapping multi-camera surveillance setups, considering the wide spread use of video surveillance in public spaces. Automated techniques are crucial to handle the large amounts of data from video surveillance. The topic focuses on person detection and reidentification, addressing challenges like changes in size, pose, and background. Various methods for person reidentification are explored, emphasizing the importance of soft biometric details for accurate identification. Elliptic curve cryptography (ECC) is considered as a secure method for ensuring privacy and data integrity in surveillance systems. ECC's efficiency is highlighted in comparison to RSA, showcasing its ability to provide equivalent security with shorter key lengths, reducing computational requirements. The study employs adaptive background detection, Kalman filtering for multiple object tracking, and a CNN-based deep learning model for pedes trian image classification. Encryption using ECC secures the transmitted data, and at the receiver end, the images undergo decryption, classification, and feature extraction for person reidentification. 2026 by Apple Academic Press, Inc. Publisher An entity responsible for making the resource available Apple Academic Press Relation A related resource ISBN: 978-104009235-4; 978-177491622-3; Language A language of the resource English Type The nature or genre of the resource Book chapter Rights Information about rights held in and over the resource Restricted Access; Hardcopy may be available in the library Format The file format, physical medium, or dimensions of the resource online