An Identity-Based Encryption Scheme for Data Security in Fog Computing

Abstract

This book series publishes research on the analysis and development of algorithms for intelligent systems with their applications to various real world problems. It covers research related to autonomous agents, multi-agent systems, behavioral modeling, reinforcement learning, game theory, mechanism design, machine learning, meta-heuristic search, optimization, planning and scheduling, artificial neural networks, evolutionary computation, swarm intelligence and other algorithms for intelligent systems. The book series includes recent advancements, modification and applications of the artificial neural networks, evolutionary computation, swarm intelligence, artificial immune systems, fuzzy system, autonomous and multi agent systems, machine learning and other intelligent systems related areas. The material will be beneficial for the graduate students, post-graduate students as well as the researchers who want a broader view of advances in algorithms for intelligent systems. The contents will also be useful to the researchers from other fields who have no knowledge of the power of intelligent systems, e.g. the researchers in the field of bioinformatics, biochemists, mechanical and chemical engineers, economists, musicians and medical practitioners. The series publishes monographs, edited

Hybrid Lightweight Proxy Re-Encryption Scheme for Secure Fog-to-Things Environment

“…It can be used to perform heavy computation operations and reduce the computational overhead required on resource-constrained devices. Nonetheless, few works have focused on security and privacy in fog computing [23].…”

“…Literature [25]- [27] has applied ciphertext-policy attribute-base encryption (CP-ABE) to establish secure access control over encrypted data in fog computing, thereby enabling a data owner to specify the access policy over a universe of attributes that a user needs to decrypt the ciphertext. A further proposed scheme in [23] uses identity-based cryptography to provide secure communication through unauthorized users in fog. The authors in [43] presented an ID-based PRE scheme with auxiliary input.…”

“…The issues of risk become even more critical when low-resource devices exchange sensitive data because of their direct access to the internet [10]. Most of the research on fog computing and IoT focuses on architecture issues and applications development without properly supporting security and privacy-preserving mechanisms [23]. When sensitive data are outsourced to fog nodes, data owners lose physical control over their data and, hence, become vulnerable to various security and privacy attacks, as fog devices are not considered fully trusted.…”

An efficient ID‐based cryptographic technique using IFP and GDLP

“…Ramadan et al 16 investigated identity‐based encryption scheme under the RSA assumption and providing equality test. Meshram et al 17,18 presented efficient transformation model for cryptosystem and short signature schemes using chaotic maps under cloud computing environment with fuzzy user data sharing Farjana et al 19 demonstrated the new identity‐based encryption technique that confirms protected information transmission to certified users and showed its implementation in fog computing.…”

Cloud, Edge, and Fog Computing and Security for the Internet of Things

“…The author also proposed the fog computing base face identification and resolution framework used to improve the processing capacity to save the bandwidth and observes the protection and privacy issues. A privacy security scheme is for the data encryption and integrity finder to resolve the confidentiality, availability issue, and integrity in the data processing (Farjana, et al 2020).…”