A blockchain provides a secure method to achieve consensus using a distributed and peer-to-peer network in which no trusted central party is required. As a result, it has the potential to resolve many challenges that are faced with current centralized controllers in globally distributed applications. To date, the blockchain technology has been used for recording transactions and tracking objects in which multiple participants reach a consensus on whether a transaction is valid or not. This paper introduces the novel paradigm of probabilistic blockchains, an extension of the current blockchains that allows building efficient and distributed risk assessment and decision-making applications in which multiple untrusting parties collaborate but may not completely agree on the outcome. The paradigm is particularly useful for risk assessment, where a group of decision-makers needs to decide or analyze an event based on imperfect information. The proposed approach can be used in applications like intrusion detections, stock market predictions, insurance, and recommendation systems. The paper presents and analyzes the application of probabilistic blockchains for intrusion detection systems for computer networks. The results show the feasibility and efficiency of the proposed paradigm in making such decisions.
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