Fractional-Order Uncertain Chaotic Cryptovirology in Blockchain System Stabilization using a Robust Adaptive Sliding Mode Controller

One of the most critical security problems today concerns our data on the internet. Cybercrimes, perpetrated through malicious programs, have become commonplace, posing risks to personal and public information during data exchanges or in data storage. In recent studies, the worm propagation dynamics in cryptovirology in blockchain systems could be successfully modeled by means of three-dimensional fractional-order chaotic systems based on the SEI nonlinear epidemic representation. This paper introduces an adaptive sliding mode control design for the robust stabilization of fractional-order cryptovirology in blockchain systems in presence of disturbance. The problem of stabilizing chaos in cryptovirology systems is solved analytically following the methodology of Lyapunov's theorem. We were able to show that the application of the proposed adaptive SMC control approach allows the system states to converge towards stable values. Furthermore, this is largely validated by numerical simulations on Matlab/Simulink.