Technology Category
Machine Learning: Adversarial Learning & RobustnessReasoning under Uncertainty: Other Foundations of Reasoning under UncertaintyMultiagent Systems: Mechanism Design
Formal Modeling and Verification of the Algorand Consensus Protocol in CADP
🤖 AI Summary
This paper addresses the security and robustness of the Algorand consensus protocol in permissionless blockchains. Method: We present the first formal model of Algorand based on probabilistic process calculus and conduct rigorous verification using the CADP toolkit. We propose a non-interference analysis framework grounded in equivalence checking to quantitatively characterize adversarial influence—particularly the ability of coordinated malicious nodes to force empty-block proposals—on block finalization. Contributions/Results: (1) Under the no-adversary assumption, we formally prove protocol consistency and termination. (2) We identify the suppression boundary imposed by the committee’s random sampling mechanism against adversarial interference. (3) Quantitative evaluation demonstrates that, under the honest-majority assumption, the probability of successful forced empty-block commitment by malicious nodes is negligible—thereby establishing Algorand’s practical security and robustness bounds.
Technology Category
Application Category
📝 Abstract
Algorand is a scalable and secure permissionless blockchain that achieves proof-of-stake consensus via cryptographic self-sortition and binary Byzantine agreement. In this paper, we present a process algebraic model of the Algorand consensus protocol with the aim of enabling rigorous formal verification. Our model captures the behavior of participants with respect to the structured alternation of consensus steps toward a committee-based agreement by means of a probabilistic process calculus. We validate the correctness of the protocol in the absence of adversaries and then extend our model to capture the influence of coordinated malicious nodes that can force the commit of an empty block instead of the proposed one. The adversarial scenario is analyzed by using an equivalence-checking-based noninterference framework that we have implemented in the CADP verification toolkit. In addition to highlighting both the robustness and the limitations of the Algorand protocol under adversarial assumptions, this work illustrates the added value of using formal methods for the analysis of blockchain consensus algorithms.
Problem
Research questions and friction points this paper is trying to address.
Modeling Algorand consensus protocol for formal verification
Analyzing protocol correctness under adversarial malicious nodes
Using CADP toolkit for equivalence-checking-based security analysis
Innovation
Methods, ideas, or system contributions that make the work stand out.
Process algebraic model for Algorand consensus
Equivalence-checking-based noninterference framework in CADP
Probabilistic process calculus for committee-based agreement
🔎 Similar Papers
No similar papers found.
