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Covert channels are designed to protect the communication relationship of the sender and receiver. Traditional covert channels have become insecure due to the continuous improvement of traffic analysis techniques. In this context, there is an urgent need to identify new approaches for covert channels. Blockchain is an emerging technique with characteristics of user anonymity, a flooding propagation mechanism, and tamper resistance, which make it a compelling platform for covert channels. Previous approaches applied Bitcoin as the underlying blockchain, and its pseudoanonymity may expose the communication relationship. Moreover, the reliance of these approaches on prenegotiated labels to identify transactions containing covert messages further reduced their concealment. In this work, we present a practical and secure covert channel over Monero. Compared to Bitcoin, Monero's full anonymity efficiently protects the relationship between the sender and receiver. Moreover, no labels are employed to identify special transactions. The receiver filters and extracts the covert message using his private key. In this study, we make a complete assessment of the robustness, reliability, and anti-traceability of our protocol, as these properties are regarded as desirable for a covert channel. We also formalize the definition of security for covert channels through a transaction distinguishing experiment. A rigorous proof shows that our protocol meets this definition and is secure to use. Finally, we make a detailed comparison between our protocol and the existing blockchain-based covert channels.

We are in the Internet era, when protecting the security of personal information is both vital and challenging. As the most commonly used methods of communication, centralized systems cannot meet the increasing need for information security. Blockchain, with its characteristics of openness, decentralization, and tamper resistance, is an innovative technology underlying Bitcoin. There is potential to use blockchain in developing decentralized and transparent communication systems. Bitmessage is a well-known decentralized messaging system that enables users to exchange messages and prevents accidental eavesdropping. Bitmessage achieves anonymity and privacy by relying on the blockchain flooding propagation mechanism and asymmetric encryption algorithm. Unfortunately, Bitmessage uses proof-of-work as the solution to prevent spam, which wastes computational power and makes it inefficient to be used in practice. To address this problem, we improve Bitmessage with a novel antispam mechanism based on proof-of-space, which requires the user to dedicate a certain amount of disk space to send a message. This improvement reduces the time and computing resource costs by eliminating computationally heavy hash operations. Moreover, we achieve a high level of anonymity by using the stealth address as the destination of the delivered message, which can only be identified by the intended receiver. Finally, we improve the protocol's reliability by taking the blockchain as an immutable database to store the delivered messages.

The ever-increasing pervasiveness of decentralized applications, such as blockchain, is creating challenges for sources of randomness, which play an integral part in decentralized settings. Distributed randomness generation (DRG) protocols, aiming at producing high-quality randomness without a central party, have drawn increased attention from academia as well as industry. Previous approaches lacked security proofs, and their dependence on secure messaging channels reduced their practicality. In this work, we first formalize the desired properties of a secure DRG protocol and build a security model using these formal definitions. To the best of our knowledge, this is the first work to build a security model for DRG protocols, which can be used as a general framework for security analysis of DRG protocols. We then present SecRand, a secure DRG protocol with high practicality and scalability. We improve upon previous approaches by modifying the secret generation method in the reconstruction phase, which ensures the same scalability but achieves resistance against an adversary's malicious behavior of withholding its secret shares. We also provide strict proofs under our security model, showing that SecRand achieves the desired properties and is secure enough to be used in decentralized applications. Furthermore, we present a detailed performance evaluation of SecRand by deploying it on a laptop with a Windows 10 environment in the C language. The experimental data showed that SecRand achieved a better performance compared with previous approaches in the presence of corrupted participants, and this performance advantage grew linearly with the number of corrupted participants.