Izvorni znanstveni članak
https://doi.org/10.1080/00051144.2022.2140391
GAN Base feedback analysis system for industrial IOT networks
K. Ashok
; Department of Computer Science and Engineering, New Horizon College of Engineering, Bangalore, India
Rajasekhar Boddu
; Department of Software Engineering, College of Computing and Informatics, Haramaya University, Dire Dawa, Ethiopia
*
Salman Ali Syed
; Department of Computer Science, Applied College, Jouf University, Tabarjal, Kingdom of Saudi Arabia
Vijay R. Sonawane
; Department of Information Technology, MVPS’s Karmaveer Adv.Baburao Ganpatrao Thakare College of Engineering, Nashik, India
Ravindra G. Dabhade
; Department of Electronics & Telecommunication Engineering, Matoshri College of Engineering & Research Centre, Nashik, India
Pundru Chandra Shaker Reddy
; School of Computing and Information Technology, REVA University, Bangalore, India
* Autor za dopisivanje.
Sažetak
The internet, like automated tools, has grown to better our daily lives. Interacting IoT products
and cyber-physical systems. Generative Adversarial Network’s (GANs’) generator and discriminator may have different inputs, allowing feedback in supervised models. AI systems use neural networks, and adversarial networks analyse neural network feedback. Cyber-physical production systems (CPPS) herald intelligent manufacturing . CPPS may launch cross-domain attacks since the virtual and real worlds are interwoven. This project addresses enhanced Cyber-Physical System(CPS) feedback structure for Denial-of-Service (DoS) defence . Comparing sensor-controller and controller-to-actuator DoS attack channels shows a swapping system modelling solution for the CPS’s complex response feedback. Because of the differential in bandwidth between the two channels and the suspects’ limited energy, one person can only launch so many DoS assaults. DoS attacks are old and widespread. Create a layered switching paradigm that employs packet-based transfer techniques to prevent assaults. The discriminator’s probability may be used to assess whether feedback samples came from real or fictional data. Cognitive feedback can assess GA feedback data.
Ključne riječi
Denial-of-Service; cyber-physical production systems (CPPS); cognitive feedback; generative adversarial networks (GANs)
Hrčak ID:
315747
URI
Datum izdavanja:
11.11.2022.
Posjeta: 582 *