Abstract
Peer‐to‐Peer (P2P) botnets have emerged as one of the most serious threats to Internet security. To effectively eliminate P2P botnets, in this paper, the authors present two novel dynamical models to portray the process of formation of P2P botnets, one of which is called microlevel model, the other is called macrolevel model. Also, the stability of equilibria is investigated along with the analysis of how to prevent the P2P botnet. Furthermore, by analyzing the relationship between infection rate and the proportion of the hosts with countermeasures, we obtain the mathematical expressions of effective immune regions and depict their numerical simulations. Finally, numerical simulations verify the correctness of mathematical analysis. Our results can provide the guidance for security practitioners to defend and eliminate P2P botnet at a cost‐effective way.
Highlights
A botnet is a network of thousands or more of compromised hosts under the control of a botnetmaster, which usually recruits new vulnerable computers by running all kinds of malicious software malware, such as Trojan horses, worms, computer viruses, and so forth 1
Our key contributions are summarized as follows: i we propose novel dynamical models which reflect the formation of P2P botnets; ii we derive mathematically the feasible region of immunization and depict their numerical simulations; iii we suggest a probable immune method for researchers and security professionals
Considering bot candidates and the network a botnet attaches itself to, we roughly divide P2P botnets into three categories 18 : i Parasite P2P botnet, in which all bot members are chosen from an existing P2P network; ii Leaching P2P botnet, which is a botnet that bot candidates are from vulnerable hosts throughout the Internet, but they will join in and depend on an existing P2P network; iii Bot-only P2P botnet, which refers to a botnet that occurs in an unattached network, and there are no nonmalignant peers except bots
Summary
A botnet is a network of thousands or more of compromised hosts under the control of a botnetmaster, which usually recruits new vulnerable computers by running all kinds of malicious software malware , such as Trojan horses, worms, computer viruses, and so forth 1. Kolesnichenko et al developed a mean-field model to analyze P2P botnet behaviors In their seminal work, Yan et al mathematically elaborated the performance of a new type of P2P botnet—AntBot from perspectives of reachability, resilience to pollution and scalability. Yan et al mathematically elaborated the performance of a new type of P2P botnet—AntBot from perspectives of reachability, resilience to pollution and scalability They developed a P2P botnet simulator to evaluate the effectiveness of analysis. For security workers to be better prepared for potentially destructive P2P botnets, it is necessary for them to understand deeply factors that influence the formation of P2P botnets Against this backdrop, in this paper, we utilize mathematical modeling method to investigate how immunizations affect the dynamical actions of P2P botnets.
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