A Feature Model of Consensus Algorithms in Distributed Ledger Technology

Abstract

Distributed ledger technologies have gained significant attention and adoption in recent years. Despite various security features distributed ledger technology provides, they are vulnerable to different and new malicious attacks, such as selfish mining and Sybil attacks. While such vulnerabilities have been investigated, detecting and discovering appropriate countermeasures still need to be reported. Cybersecurity knowledge is limited and fragmented in this domain, while distributed ledger technology usage grows daily. Thus, research focusing on overcoming potential attacks on distributed ledgers is required. This study aims to raise awareness of the cybersecurity of distributed ledger technology by designing a security risk assessment method for distributed ledger technology applications. We have developed a database with possible security threats and known attacks on distributed ledger technologies to accompany the method, including sets of countermeasures. We employed a semisystematic literature review combined with method engineering to develop a method that organizations can use to assess their cybersecurity risk for distributed ledger applications. The method has subsequently been evaluated in three case studies, which show that the method helps to effectively conduct security risk assessments for distributed ledger applications in these organizations.