A derivative matrix-based covert communication method in blockchain

Abstract

The data in the blockchain cannot be tampered with and the users are anonymous, which enables the blockchain to be a natural carrier for covert communication. However, the existing methods of covert communication in blockchain suffer from the predefined channel structure, the capacity of a single transaction is not high, and the fixed transaction behaviors will lower the concealment of the communication channel. Therefore, this paper proposes a derivation matrix-based covert communication method in blockchain. It uses dual-key to derive two types of blockchain addresses and then constructs an address matrix by dividing addresses into multiple layers to make full use of the redundancy of addresses. Subsequently, to solve the problem of the lack of concealment caused by the fixed transaction behaviors, divide the rectangular matrix into square blocks with overlapping regions and then encrypt different blocks sequentially to make the transaction behaviors of the channel addresses match better with those of the real addresses. Further, the linear congruence algorithm is used to generate random sequence, which provides a random order for blocks encryption, and thus enhances the security of the encryption algorithm. Experimental results show that this method can effectively reduce the abnormal transaction behaviors of addresses while ensuring the channel transmission efficiency.