Can Liu’s research while affiliated with Soochow University and other places

Coded computing has proven its efficiency in tolerating stragglers in distributed computing. Workers return the sub-computation results to the master after computing, and the master recovers the final computation result by decoding. However, the workers may provide incorrect results, which leads to wrong final result. Therefore, it is meaningful to improve the resilience of coded computing against errors. Most existing verification schemes only use the workers’ fully correct computations to recover the final result, and the defective computations are not considered for decoding. In this paper, we focus on matrix multiplication and design a general Test-and-Decode (TD) scheme to recover the final result efficiently. Furthermore, we divide each sub-computation result into multiple parts and fully use the correct parts for partial recovery, which can improve the tolerance for errors in computations. Decoding is performed only when the verification result satisfies the permission, which avoids repetitive decoding. We conduct extensive simulation experiments to evaluate the probability of successful recovery of the results and the computation time of the TD scheme. We also compare the TD scheme with other verification schemes and the results show that it outperforms the current schemes in terms of efficiency in verifying and recovering computational results.

Recently, permissioned blockchain has been extensively explored in various fields, such as asset management, supply chain, healthcare, and many others. Many scholars are dedicated to improving its verifiability, scalability, and performance based on sharding techniques, including grouping nodes and handling cross-shard transactions. However, they ignore the node vulnerability problem, i.e., there is no guarantee that nodes will not be maliciously controlled throughout their life cycle. Facing this challenge, we propose RecAGT, a novel identification scheme aimed at reducing communication overhead and identifying potential malicious nodes. First, shard testable codes are designed to encode the original data in case of a leak of confidential data. Second, a new identity proof protocol is presented as evidence against malicious behavior. Finally, adaptive group testing is chosen to identify malicious nodes. Notably, our work focuses on the internal operation within the committee and can thus be applied to any sharding permissioned blockchains. Simulation results show that our proposed scheme can effectively identify malicious nodes with low communication and computational costs.

Edge computing is an efficient computing paradigm, which can utilize computing devices at the edge of network to provide real-time proximity service. Since edge devices lack centralized management, they are more vulnerable to being attacked. Therefore, the issues of data security and user privacy in edge computing are particularly important. A large number of existing literature focus on the data security and user privacy with independent attackers. However, cooperative attacks, in which multiple attackers can collaborate to obtain the data content and user privacy, have not been fully investigated. In particular, we take the matrix-vector multiplication which is a basic component of most machine learning algorithms as the basic task. Therefore, in this paper, we focus on the Secure and Privacy Matrix-vector Multiplication (SPMM) issue for edge computing against cooperative attack and design a general coded computation scheme to achieve lowest system resource consumption, i.e. communication cost and computational load. Specifically, we propose two coding schemes: Secure and Private Coding with lower communication Cost (SPCC) and Secure and Private Coding with lower computational Load (SPCL). We also conduct solid theoretical analyses and extensive experiments to demonstrate that both two proposed coding schemes can achieve lower communication cost and computational load than existing work. Finally, we perform extensive analyses to the superiority of the proposed schemes.