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Correlation of biological and computer viruses through evolutionary game theory

Dimitris Kostadimas, Kalliopi Kastampolidou, Theodore Andronikos

TL;DR

The paper addresses whether evolutionary game theory can bridge insights between computer viruses and biological viruses by comparing the Virlock ransomware to the bacteriophage φ6. It models Virlock dynamics with a payoff matrix for ransom payment versus non-payment and discusses φ6 as a canonical biological analog in EGT contexts. The authors compare operational traits across domains, presenting cross-domain recovery tables and payoff reasoning to highlight shared principles such as replication, mutation, host interaction, and evasion. The work aims to broaden defensive perspectives and inspire cross-domain simulations and strategy transfer to improve interventions against both computer and biological threats.

Abstract

Computer viruses have many similarities to biological viruses, and their association may offer new perspectives and new opportunities in the effort to tackle and even eradicate them. Evolutionary game theory has been established as a useful tool for modeling viral behaviors. This work attempts to correlate a well-known virus, namely Virlock, with the bacteriophage $\phi6$. Furthermore, the paper suggests certain efficient strategies and practical ways that may reduce infection by Virlock and similar such viruses.

Correlation of biological and computer viruses through evolutionary game theory

TL;DR

The paper addresses whether evolutionary game theory can bridge insights between computer viruses and biological viruses by comparing the Virlock ransomware to the bacteriophage φ6. It models Virlock dynamics with a payoff matrix for ransom payment versus non-payment and discusses φ6 as a canonical biological analog in EGT contexts. The authors compare operational traits across domains, presenting cross-domain recovery tables and payoff reasoning to highlight shared principles such as replication, mutation, host interaction, and evasion. The work aims to broaden defensive perspectives and inspire cross-domain simulations and strategy transfer to improve interventions against both computer and biological threats.

Abstract

Computer viruses have many similarities to biological viruses, and their association may offer new perspectives and new opportunities in the effort to tackle and even eradicate them. Evolutionary game theory has been established as a useful tool for modeling viral behaviors. This work attempts to correlate a well-known virus, namely Virlock, with the bacteriophage . Furthermore, the paper suggests certain efficient strategies and practical ways that may reduce infection by Virlock and similar such viruses.

Paper Structure

This paper contains 9 sections, 10 figures.

Figures (10)

  • Figure 1: Representation of VirLock Cloud Storage Infection. In the case above, the bottom left computer is getting infected with the VirLock malware through a malicious email attachment that the user opened. VirLock will infect the files in the cloud storage as well, and the rest of the computers in the network might eventually get the malware. The red arrows represent the path of the infection, while the blue arrows represent interaction with the cloud.
  • Figure 2: Ransom Payment Payoff Matrix. The user has the option to pay and the option not to pay the ransom, while the VirLock malware may or may not decrypt the users' data. The payoff matrix makes clear that the user will benefit the malware creator/s less by not proceeding in the ransom payment, and that paying the ransom holds an additional risk.
  • Figure 3: Similarities between the two viruses.
  • Figure 4: Differences between the two viruses.
  • Figure 5: Complexity of the steps taken in every recovery strategy.
  • ...and 5 more figures