Malicious actors are individuals or groups who intentionally cause harm or disruption within a system or network. These entities conduct activities such as cyberattacks, fraud, data theft, or market manipulation, often for financial gain, sabotage, or ideological motives. Their actions pose significant security risks, compromising data integrity, operational continuity, and user trust. Identifying and mitigating the threats posed by such actors is paramount for system security.
Context
In the cryptocurrency and blockchain domain, news frequently highlights the persistent threat posed by malicious actors targeting exchanges, protocols, and individual users. Discussions often involve sophisticated phishing schemes, smart contract exploits, and various forms of financial fraud that exploit vulnerabilities in decentralized systems. A critical future development centers on enhancing cryptographic security, implementing robust audit procedures, and fostering user education to counter evolving attack vectors. Vigilance against these threats is essential for safeguarding digital assets.
This research introduces a novel methodology and taxonomy for formally analyzing blockchain consensus algorithm liveness against malicious attacks, ensuring robust system progress.
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