The method of extracting and describing the intended behavior of software precisely has become one of the key points in the fields of software behavior＇s dynamic and trusted authentication. In this paper, the author proposes a specified measure of extracting SIBDS （software intended behaviors describing sets） statically from the binary executable using the software＇s API functions invoking, and also introduces the definition of the structure used to store the SIBDS in detail. Experimental results demonstrate that the extracting method and the storage structure definition offers three strong properties： （i） it can describe the software＇s intended behavior accurately; （ii） it demands a small storage expense; （iii） it provides strong capability to defend against mimicry attack.
PENG Guojun PAN Xuanchen FU Jianming ZHANG Huanguo
应用软件一般需要输入和处理敏感信息,如密码,以实现用户和远程服务器之间的可靠认证和安全交互.定量度量敏感信息在敏感信息处理中的安全性是目前研究的难点.根据敏感信息处理的流程和敏感信息出现点的上下文,定义敏感信息处理的固有属性、可变属性和推求属性,设计了从固有属性和可变属性到数据操作的映射规则,提出了基于层次分析法(analytic hierarchy process,AHP)及折中型多属性决策(technique for order preference by similarity to an ideal solution,TOPSIS)的敏感度计算方法,从而实现敏感度的定量计算,展示在敏感信息处理中敏感度的动态变化规律,为敏感信息处理的安全防护提供支持.该方法可以应用于可信软件的安全分析和可信度量,最后,实验分析了3种敏感信息在处理中的敏感度变化,发现了敏感信息处理的潜在危险点,从而证实了该方法的有效性.
Facing the increasing security issues in P2P networks, a scheme for resource sharing using trusted computing technologies is proposed in this paper. We advance a RS-UCON model with decision continuity and attribute mutability to control the usage process and an architecture to illustrate how TC technologies support policy enforcement with bidirectional attestation. The properties required for attestation should include not only integrity measurement value of platform and related application, but also reputation of users and access history, in order to avoid the limitation of the existing approaches. To make a permission, it is required to evaluate both the authorization and conditions of the subject and the object in resource usage to ensure trustable resources to be transferred to trusted users and platform.
以传统有限自动机(finite state automata,简称FSA)为基础,从系统调用参数中解析出系统对象,提出了一种基于系统对象的软件行为模型(model of software behavior based on system objects,简称SBO).该模型的行为状态由软件所关联的所有系统对象表示,从而赋予状态的语义信息,解决了不同行为迹中PC(program counter)值的语义不相关问题;同时,该模型可以对抗系统调用参数的直接和间接修改,从而可以检测基于数据语义的攻击.最后,实现了基于SBO的软件异常检测原型工具(intrusion detection prototype system based on SBO,简称SBOIDS),其实验和分析结果表明,该模型可以有效地检测基于控制流的攻击、模仿攻击以及针对数据语义的攻击,并给出了该工具的性能开销.
