The second generation of blockchain represented by smart contract has experienced an explosive growth of its platforms and applications in recent years. However, frequent smart contract vulnerability incidents pose a serious risk to blockchain ecosystem security. Since code auditing based on expert experience is inefficient in smart contracts vulnerability mining, the significance of developing universal automated tools to mining smart contracts vulnerability was proposed. Firstly, the security threats faced by smart contracts were investigated and analyzed. Top 10 vulnerabilities, including code reentrancy, access control and integer overflow, as well as corresponding attack modes were summarized. Secondly, mainstream detection methods of smart contract vulnerabilities and related works were discussed. Thirdly, the performance of three existing tools based on symbolic execution were verified through experiments. For a single type of vulnerability, the highest false negative rate was 0.48 and the highest false positive rate was 0.38. The experimental results indicate that existing studies only support incomplete types of vulnerability with many false negatives and positives and depend on manual review. Finally, future research directions were forecasted aiming at these limitations, and a symbolic-execution-based fuzzy test framework was proposed. The framework can alleviate the problems of insufficient code coverage in fuzzy test and path explosion in symbolic execution, thus improving vulnerability mining efficiency for large and medium-sized smart contracts.

Since the protocol classification of network traffic is a prerequisite for protocol analysis and network management, the network protocol recognition techniques were researched and reviewed. Firstly, the target of network protocol recognition was described, and the general process of protocol recognition was analyzed. The practical requirements for protocol recognition were discussed, and the criteria for evaluating protocol recognition methods were given. Then, the research status of network protocol techniques was summarized from two categories:packet-based protocol recognition methods and flow-based protocol recognition methods, and the variety of techniques used for protocol recognition were analyzed and compared. Finally, with the defects of current protocol recognition methods and the practical application requirements considered, the research trend of protocol recognition techniques was forecasted.