INVESTIGATING VIRUS SPREAD ANALYSIS IN COMPUTER NETWORKS WITH ATANGANA-BALEANU FRACTIONAL DERIVATIVE MODELS
This paper proposes a mathematical model to investigate the dynamic behaviors of a modified computer virus model using the Atangana-Baleanu fractional derivative in the Caputo sense, aiming to elucidate the connection between its parameters and network attributes. By introducing a relatively new num...
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2025
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my.uniten.dspace-370242025-03-03T15:46:43Z INVESTIGATING VIRUS SPREAD ANALYSIS IN COMPUTER NETWORKS WITH ATANGANA-BALEANU FRACTIONAL DERIVATIVE MODELS Ahmad I. Bakar A.A. Ahmad H. Khan A. Abdeljawad T. 57220824630 35178991300 57220768187 56865012200 6508051762 Computer networks Numerical methods Anti virus Anti-virus measure Atanganum?baleanu fractional mathematical model Dynamic behaviors Efficient energy usage Energy usage Fractional derivative model Network environments Sustainable network environment Virus spreads Computer viruses This paper proposes a mathematical model to investigate the dynamic behaviors of a modified computer virus model using the Atangana-Baleanu fractional derivative in the Caputo sense, aiming to elucidate the connection between its parameters and network attributes. By introducing a relatively new numerical method, we address the memory-dependent and nonlocal features of the system. The existence and uniqueness of the model's solution are confirmed. To explore solution trajectories and assess the impact of various input factors on computer virus dynamics, we employ an efficient numerical technique. Our simulations provide insights into the consequences of fractional order, anti-virus measures, asymptotic fraction, damage rate, and removal rate in the system. These findings illuminate the relationships between model parameters, facilitating the design of networks that minimize the risk of virus outbreaks and prevent future cyber threats. By identifying critical factors involved in the progression of viruses, these results enable the development of more effective defense mechanisms. ? 2024 The Author(s). Final 2025-03-03T07:46:43Z 2025-03-03T07:46:43Z 2024 Article 10.1142/S0218348X24400437 2-s2.0-85196932950 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85196932950&doi=10.1142%2fS0218348X24400437&partnerID=40&md5=c8daf7130887f87456b10ece1d185f5e https://irepository.uniten.edu.my/handle/123456789/37024 32 7-Aug 2440043 World Scientific Scopus |
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Computer networks Numerical methods Anti virus Anti-virus measure Atanganum?baleanu fractional mathematical model Dynamic behaviors Efficient energy usage Energy usage Fractional derivative model Network environments Sustainable network environment Virus spreads Computer viruses |
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Computer networks Numerical methods Anti virus Anti-virus measure Atanganum?baleanu fractional mathematical model Dynamic behaviors Efficient energy usage Energy usage Fractional derivative model Network environments Sustainable network environment Virus spreads Computer viruses Ahmad I. Bakar A.A. Ahmad H. Khan A. Abdeljawad T. INVESTIGATING VIRUS SPREAD ANALYSIS IN COMPUTER NETWORKS WITH ATANGANA-BALEANU FRACTIONAL DERIVATIVE MODELS |
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This paper proposes a mathematical model to investigate the dynamic behaviors of a modified computer virus model using the Atangana-Baleanu fractional derivative in the Caputo sense, aiming to elucidate the connection between its parameters and network attributes. By introducing a relatively new numerical method, we address the memory-dependent and nonlocal features of the system. The existence and uniqueness of the model's solution are confirmed. To explore solution trajectories and assess the impact of various input factors on computer virus dynamics, we employ an efficient numerical technique. Our simulations provide insights into the consequences of fractional order, anti-virus measures, asymptotic fraction, damage rate, and removal rate in the system. These findings illuminate the relationships between model parameters, facilitating the design of networks that minimize the risk of virus outbreaks and prevent future cyber threats. By identifying critical factors involved in the progression of viruses, these results enable the development of more effective defense mechanisms. ? 2024 The Author(s). |
| author2 |
57220824630 |
| author_facet |
57220824630 Ahmad I. Bakar A.A. Ahmad H. Khan A. Abdeljawad T. |
| format |
Article |
| author |
Ahmad I. Bakar A.A. Ahmad H. Khan A. Abdeljawad T. |
| author_sort |
Ahmad I. |
| title |
INVESTIGATING VIRUS SPREAD ANALYSIS IN COMPUTER NETWORKS WITH ATANGANA-BALEANU FRACTIONAL DERIVATIVE MODELS |
| title_short |
INVESTIGATING VIRUS SPREAD ANALYSIS IN COMPUTER NETWORKS WITH ATANGANA-BALEANU FRACTIONAL DERIVATIVE MODELS |
| title_full |
INVESTIGATING VIRUS SPREAD ANALYSIS IN COMPUTER NETWORKS WITH ATANGANA-BALEANU FRACTIONAL DERIVATIVE MODELS |
| title_fullStr |
INVESTIGATING VIRUS SPREAD ANALYSIS IN COMPUTER NETWORKS WITH ATANGANA-BALEANU FRACTIONAL DERIVATIVE MODELS |
| title_full_unstemmed |
INVESTIGATING VIRUS SPREAD ANALYSIS IN COMPUTER NETWORKS WITH ATANGANA-BALEANU FRACTIONAL DERIVATIVE MODELS |
| title_sort |
investigating virus spread analysis in computer networks with atangana-baleanu fractional derivative models |
| publisher |
World Scientific |
| publishDate |
2025 |
| _version_ |
1826077459864354816 |
| score |
13.244413 |