Ratish Agarwal

dblp:22/7660 · DBLP profile ↗
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6ranked-venue papers
0as first author
6since 2021 · last 2026
0000-0003-4143-1483ORCID · corroborated

Domains — the database's venue-derived domains; a paper can count in several

Systems, architecture and hardware · 5 · 5 since 2021Artificial intelligence and machine learning · 1 · 1 since 2021Applied, interdisciplinary, general and emerging computing · 1 · 1 since 2021
YearPublicationVenuePosition
2026 Adaptive game-theoretic fairness enforcement for selfish MAC back-off misbehavior in IIoT networks: the SAFE-MAC protocol
Chanchal Lohi, Piyush Kumar Shukla, Ratish Agarwal
J. Supercomput.3
2026 A deep learning-driven cyber attack avoidance framework for secure IoT-enabled smart city transportation systems
Prashant Kumar Shukla, Ratish Agarwal
J. Supercomput.2
2026 Deep neural network-based cyber-attack avoidance system with hybrid optimization
Prashant Kumar Shukla, Ratish Agarwal
J. Supercomput.2
2025 A blockchain-enabled encrypted neural network framework for trust-aware key management and node authentication in Industrial Internet of Things
Abhishek Dwivedi, Ratish Agarwal, Mohammad A. Yahya, Noha Alduaiji, Piyush Kumar Shukla
J. Supercomput.2
2024 A competent CCHFMO with AMDH for QoS improvisation and efficient route protection in MANET
abstract
Summary The ability of mobile ad hoc networks (MANET) to be used as communication tools in a variety of industries, including healthcare, the military, smart traffic, and smart cities, has drawn special consideration. Traditional Manet's multicast routing methods seem to be inappropriate to massive with Adaptive systems because the problem is NP‐complete, resulting in an enchanting QoS restrictions. In order to conquer that the paper proficiently introduces the Conglomerate Crumb Horde Formicary Meta‐Heuristic (CCHFMO) with Asymmetrical Meander Diffie‐Hellman (AMDH) to tackle the major obstacles are multicast routing problems and lack of data protection. Initially, the fusion of crumb horde optimization (CHO) and formicary optimization (FO) is exploited to strengthen QoS limitations and reduce QoS data loss. However, the massive and dynamic nature of the network with the combination of more QoS restrictions, deficient security has become extremely difficult. Therefore, the research work establishes the asymmetrical meander Diffie‐Hellman (AMDH) to significantly improve performance and concealment while ensuring channel security during data transfer. Finally, the results demonstrated that by employing the novel optimization approaches, the MANET can increase data protection while still achieving high transmission rates and sophistication of communication. As a consequence, it adequately explicates the article to improve QoS performances.
Gajendra Kumar Ahirwar, Ratish Agarwal, Anjana Pandey
Concurr. Comput. Pract. Exp.2
2022 Comparative Study on Black Hole Attack in Mobile Ad-Hoc Networks
Gajendra Kumar Ahirwar, Ratish Agarwal, Anjana Pandey
ISDA (4)2