基于状态机学习算法的TLS实现库安全性分析  

Security analysis of TLS implementations based on state machine learning algorithm

作　　者：毕兴 唐朝京[1] BI Xing;TANG Chaojing(College of Electronic Science,National University of Defense Technology,Changsha 410073,China)

机构地区：[1]国防科技大学电子科学学院,湖南长沙410073

出　　处：《系统工程与电子技术》2018年第12期2810-2815,共6页Systems Engineering and Electronics

基　　金：国家自然科学基金(61672527)资助课题

摘　　要：通过状态机学习算法,可以提取传输层安全(transport layer security,TLS)协议的实现库状态机模型来分析其安全性。当前在状态机学习中需要解决状态机学习时间随目标系统状态数增长而呈指数级增长的问题。提出一种改进的状态机学习算法,通过TLS协议特定套接字约简所需测试序列;结合检查点算法构造测试序列的前缀树,简化目标系统对测试序列测试步骤。测试结果表明,提出的改进算法能够大幅减少状态机学习过程生成的等价查询数量,加速状态机学习过程。同时通过学习到的状态机模型,分析其异常状态,找到一个OpenSSl的逻辑错误,证明学习到的模型是有效的。By the finite state machine learning algorithm,the state machine model of transport layer security（TLS）implementations could be extracted to analyze its security.At present,in the state machine learning,it is necessary to solve the problem that the state machine learning time increases exponentially as the number of target system states increases.An improved state machine learning algorithm is proposed,which used the TLS implementations＇ specific sockets to reduce the required test sequence.It combined the checkpoint algorithm to construct the trie（i.e.,prefix tree）of the test sequence,simplifying the test procedure of testing the test sequence.The test results showed that the proposed method can greatly reduce the number of equivalence queries generated by the state machine learning process,therefore accelerate the state machine learning process.At the same time,an abnormal state is analyzed through the learned state machine model,and a logic flaw of OpenSSl is found,which proved that the learned model is effective.

关 键 词：有限状态机 安全协议分析 传输层安全协议 

分 类 号：TP393.08[自动化与计算机技术—计算机应用技术]