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Predicting Spread Probability of Learning-Effect Computer Virus

Author

Listed:
  • Wei-Chang Yeh
  • Edward Lin
  • Chia-Ling Huang
  • Luxing Yang

Abstract

With the rapid development of network technology, computer viruses have developed at a fast pace. The threat of computer viruses persists because of the constant demand for computers and networks. When a computer virus infects a facility, the virus seeks to invade other facilities in the network by exploiting the convenience of the network protocol and the high connectivity of the network. Hence, there is an increasing need for accurate calculation of the probability of computer-virus-infected areas for developing corresponding strategies, for example, based on the possible virus-infected areas, to interrupt the relevant connections between the uninfected and infected computers in time. The spread of the computer virus forms a scale-free network whose node degree follows the power rule. A novel algorithm based on the binary-addition tree algorithm (BAT) is proposed to effectively predict the spread of computer viruses. The proposed BAT utilizes the probability derived from PageRank from the scale-free network together with the consideration of state vectors with both the temporal and learning effects. The performance of the proposed algorithm was verified via numerous experiments.

Suggested Citation

  • Wei-Chang Yeh & Edward Lin & Chia-Ling Huang & Luxing Yang, 2021. "Predicting Spread Probability of Learning-Effect Computer Virus," Complexity, Hindawi, vol. 2021, pages 1-17, July.
  • Handle: RePEc:hin:complx:6672630
    DOI: 10.1155/2021/6672630
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    Cited by:

    1. Yeh, Wei-Chang, 2024. "Time-reliability optimization for the stochastic traveling salesman problem," Reliability Engineering and System Safety, Elsevier, vol. 248(C).
    2. Yeh, Wei-Chang, 2023. "Novel recursive inclusion-exclusion technology based on BAT and MPs for heterogeneous-arc binary-state network reliability problems," Reliability Engineering and System Safety, Elsevier, vol. 231(C).
    3. Yeh, Wei-Chang, 2023. "QB-II for evaluating the reliability of binary-state networks," Reliability Engineering and System Safety, Elsevier, vol. 230(C).
    4. Yeh, Wei-Chang & Du, Chia-Ming & Tan, Shi-Yi & Forghani-elahabad, Majid, 2023. "Application of LSTM based on the BAT-MCS for binary-state network approximated time-dependent reliability problems," Reliability Engineering and System Safety, Elsevier, vol. 235(C).
    5. Yeh, Wei-Chang, 2024. "A new hybrid inequality BAT for comprehensive all-level d-MP identification using minimal paths in Multistate Flow Network reliability analysis," Reliability Engineering and System Safety, Elsevier, vol. 244(C).
    6. Hao, Zhifeng & Yeh, Wei-Chang & Tan, Shi-Yi, 2021. "One-batch preempt deterioration-effect multi-state multi-rework network reliability problem and algorithms," Reliability Engineering and System Safety, Elsevier, vol. 215(C).
    7. Yeh, Wei-Chang, 2022. "BAT-based algorithm for finding all Pareto solutions of the series-parallel redundancy allocation problem with mixed components," Reliability Engineering and System Safety, Elsevier, vol. 228(C).

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