Homomorphic Encryption for Financial Cryptography

This book offers insights on efficient utilization of homomorphic encryption (HE) for financial cryptography in confidentiality, phishing, anonymity, object and user identity protection. Homomorphic encryption has the potential to be a game-changer for the industry and cloud industry. HE method in cloud computing is presented in this book as a solution to increase the security of the data. Moreover, this book provides details about the set of fundamentals of cryptography, classical HE systems, properties of HE schemes, challenges and opportunities in HE methods, key infrastructure, problem of key management, key sharing, current algorithmic strategies and its limitation in implementation for solving complex problems in financial cryptography, application in blockchain, multivariate cryptosystems based on quadratic equations to avoid the explosion of the coefficients.

Presents significant contributions for homomorphic encryption and financial cryptography Provides practical homomorphic encryption to entice cryptographers and academics Highlights the current security threats in the field of cloud computing

Auteur
Dr. V. Seethalakshmi has done her B.E in Electrical and Electronics Engineering with distinction from PSG college of Technology, Coimbatore, Tamilnadu, M.Tech in Electronics and Communication Engineering from PTU university, Punjab and Ph.D in Information and Communication Engineering from Anna University, Chennai. Her research interest is Wireless Communication, Wireless and Adhoc Networks, embedded system and IoT. She has rich 25 years of experience in industry as well as teaching. She has published 43 technical papers in refereed journals, 58 research papers in national and International conferences and published 7 patents, 5 books and 10 book chapters. She is a recognized supervisor of Anna University, Chennai and 8 research scholars are pursuing PhD under her supervision and two were awarded degree. She is an active member of various professional societies like ISTE, IAENG, IACSIT, UACEE, CSTA and SDIWC. She is reviewer in 9 refereed journals and got certificate of outstanding contribution in reviewing by simulation modeling and practices, Elsevier Journal

Dr. S. Suganyadevi is an Assistant Professor in the department of ECE at KPR Institute of Engineering and Technology, Tamilnadu, India. She received the B.E. degree in Electronics and Communication Engineering from Anna University, Chennai, India in 2012 and the M.E. degree in VLSI Design from Anna University, Chennai in 2014. Currently she is pursuing her PhD from Anna University, Chennai, India. She has published around 20 papers in international journals and conferences. She has contributed 10+ Patents and 10+ chapters to the books. She is serving as a reviewer for reputed journals like IEEE Transactions on Image Processing Computers in Biology and Medicine (SCIE), Informatics in Medicine Unlocked (SCIE), The Imaging Science Journal (SCIE), The Journal of Super Computing (SCIE), International Journal of Computing and Digital Systems (SCIE), Concurrency and Computation: Practice and Experience (SCIE), Bulletin of Electrical Engineering and Informatics. She is the Life Member of ISTE. Her area of interest includes Signal Processing, Image Processing, Low power VLSI design, Internet of things.

Dr Rajesh Kumar Dhanaraj is a Professor in Symbiosis International (Deemed University), Pune, India. Prior to this assignment he was Professor, School of Computing Sciences & Engineering, Galgotias University, Greater Noida, India. He received the B.E. degree in Computer Science and Engineering from the Anna University Chennai, India in 2007 and the M.Tech from the Anna University Coimbatore, India in 2010 and Ph.D. degree in Computer Science from Anna University, Chennai, India, in 2017. He has contributed 45+ Authored and Edited books on various technologies, 21 Patents and 100+ articles and papers in various refereed journals and international conferences and contributed chapters to the books. His research interests include Machine Learning, Cyber-Physical Systems and Wireless Sensor Networks. He is a Senior Member of the Institute of Electrical and Electronics Engineers (IEEE), member of the Computer Science Teacher Association (CSTA); and International Association of Engineers (IAENG). He is serving as an Associate Editor and Guest Editor for reputed journals Elsevier Computers and Electrical Engineering, Human-centric Computing and Information Sciences, Emerald - International Journal of Pervasive Computing and Communications, Hindawi - Mobile Information Systems, etc. He is an Expert Advisory Panel Member of Texas Instruments Inc USA.

Dr. Mariya Ouaissa is currently a Professor at Institute Specializing in New Information and Communication Technologies, Researcher Associate and practitioner with industry and academic experience. She is a Ph.D. graduated in 2019 in Computer Science and Networks, at the L

Contenu

Chapter 1.- Introduction to Homomorphic Encryption for Financial Cryptography.- Chapter 2.- Survey on Homomorphic Encryption for Financial Cryptography Workout.- Chapter 3 Improved login interface algorithm for Financial Transactions using Visual Cryptographic Authentication.- Chapter 4 Securing shared data based on Homomorphic encryption schemes.- Chapter 5 Challenges and Opportunities associated with Homomorphic Encryption for Financial Cryptography.- Chapter 6 Homomorphic Encryption based Cloud Privacy-Preserving in Remote Ecg Monitoring and Surveillance.- Chapter 7 Enhancing Encryption Security against Cypher Attacks.- Chapter 8 Biometric Based Key Generation Using AES Algorithm for Real Time Security Applications.- Chapter 9 Financial Cryptography and its application in Blockchain.- Chapter 10 Algorithmic Strategies for Solving Complex Problems in Financial Cryptography.,- Chapter 11 Various Attacks on the implementation of Cryptographic Algorithms.- Chapter 12 A Survey on Private Keyword Sorting and Searching using Homomorphic Encryption.- Chapter 13 Multivariate Cryptosystem Based on a Quadratic Equation to Eliminate the Outliers Using Homomorphic Encryption Scheme.