摘要
智能合约是区块链的重要组成部分,具有去中心化、可追溯、自动化执行以及不可篡改等特点,在理论和技术层面能够有效适应无人机集群安全性方面的需求。以智能合约在无人机集群中飞行数据管理、自主协同、安全维护以及安全认证4个方面的应用为例,重点分析智能合约在应用过程中潜在的整数溢出、时间戳、重入、交易顺序依赖及交易授权5种安全漏洞。在此研究基础上,针对潜在的智能合约安全漏洞提出一种基于注意力机制的混合神经网络漏洞检测模型。实验表明,与当前流行的智能合约漏洞检测技术相比,该漏洞检测模型检测效果更好,具有较高的准确率和精确率。该研究结果对于提高无人机集群建设安全系数具有一定的实际意义,也为无人化建设与发展提供了参考。
Smart contracts are an important component of blockchain,characterized by decentralization,traceability,automated execution,and non tampering.They can effectively meet the security requirements of drone clusters at both the theoretical and technical levels.Taking the application of smart contracts in flight data management,autonomous collaboration,security maintenance,and security authentication in un⁃manned aerial vehicle clusters as an example,this paper focuses on analyzing the potential security vulnerabilities of smart contracts in the ap⁃plication process,including integer overflow,timestamp,reentry,transaction sequence dependency,and transaction authorization.Based on this research,a hybrid neural network vulnerability detection model based on attention mechanism is proposed for potential security vulnerabil⁃ities in smart contracts.Experiments have shown that compared to the current popular smart contract vulnerability detection technology,the proposed vulnerability detection model ACBSC has better detection performance,and has better accuracy and precision in detecting vulnera⁃bilities.The research results have certain practical significance for improving the safety factor of drone cluster construction,and also provide reference for unmanned construction and development.
作者
杨忠举
朱卫星
何红悦
王梅娟
YANG Zhongju;ZHU Weixing;HE Hongyue;WANG Meijuan(School of Command and Control Engineering,PLA Army Engineering University,Nanjing 210007,China)
出处
《软件导刊》
2023年第8期164-171,共8页
Software Guide
基金
国家重点研发计划项目(2018YFB1403400)
陆军工程大学基础前沿科技创新项目(KYZYJQZL2203)。
关键词
智能合约
无人机集群
注意力机制
混合神经网络
漏洞检测
smart contract
drone swarm
attention mechanism
hybrid neural network
vulnerability detection