Control and synchronization of chaos in some fractional computer virus models.
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| Title: | Control and synchronization of chaos in some fractional computer virus models. |
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| Authors: | Kahouli, Omar1 (AUTHOR) omarkahouli@yahoo.fr, Zouak, Imane2 (AUTHOR), Ouannas, Adel3 (AUTHOR), Abidi, Ilyes4 (AUTHOR), Bahou, Younes5 (AUTHOR), Elgharbi, Sarra6 (AUTHOR), Chaabane, Mohamed7 (AUTHOR) |
| Source: | Asian Journal of Control. Jan2026, Vol. 28 Issue 1, p240-248. 9p. |
| Subjects: | Synchronization, Computer viruses, Technological complexity, Computer simulation, Internet security, Feedback control systems, Network theory (Statistical physics), Dynamical systems |
| Abstract: | The present study investigates a fractional‐order discrete computer virus system control and synchronization, encompassing commensurate systems. Unlike traditional integer‐order models, which are limited to integer derivatives, fractional‐order models excel at capturing intricate dynamics with memory effects, crucial for accurately representing virus spread in complex networks. We delve into chaos control strategies for commensurate systems, demonstrating their effectiveness through numerical simulations. Our results indicate that stabilization is achieved for parameter values d1=0.89,d2=0.79$$ {d}_1=0.89,{d}_2=0.79 $$, and d3=0.92$$ {d}_3=0.92 $$, with controlled dynamics converging to a steady state. Furthermore, we explore chaos synchronization techniques, crucial for coordinated behavior in distributed systems, and present simulation results, showing that synchronization is attained when the coupling parameters satisfy u1=−0.4,u2=−0.52$$ {u}_1=-0.4,{u}_2=-0.52 $$, and u3=−0.82$$ {u}_3=-0.82 $$. This research provides valuable insights into controlling and mitigating the spread of computer viruses in heterogeneous networks, contributing to enhanced cybersecurity measures. [ABSTRACT FROM AUTHOR] |
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| Database: | Engineering Source |
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| Abstract: | The present study investigates a fractional‐order discrete computer virus system control and synchronization, encompassing commensurate systems. Unlike traditional integer‐order models, which are limited to integer derivatives, fractional‐order models excel at capturing intricate dynamics with memory effects, crucial for accurately representing virus spread in complex networks. We delve into chaos control strategies for commensurate systems, demonstrating their effectiveness through numerical simulations. Our results indicate that stabilization is achieved for parameter values d1=0.89,d2=0.79$$ {d}_1=0.89,{d}_2=0.79 $$, and d3=0.92$$ {d}_3=0.92 $$, with controlled dynamics converging to a steady state. Furthermore, we explore chaos synchronization techniques, crucial for coordinated behavior in distributed systems, and present simulation results, showing that synchronization is attained when the coupling parameters satisfy u1=−0.4,u2=−0.52$$ {u}_1=-0.4,{u}_2=-0.52 $$, and u3=−0.82$$ {u}_3=-0.82 $$. This research provides valuable insights into controlling and mitigating the spread of computer viruses in heterogeneous networks, contributing to enhanced cybersecurity measures. [ABSTRACT FROM AUTHOR] |
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| ISSN: | 15618625 |
| DOI: | 10.1002/asjc.3693 |
