A novel method for detecting anomalous program behavior is presented, which is applicable to hostbased intrusion detection systems that monitor system call activities. The method constructs a homogeneous Markov chain ...A novel method for detecting anomalous program behavior is presented, which is applicable to hostbased intrusion detection systems that monitor system call activities. The method constructs a homogeneous Markov chain model to characterize the normal behavior of a privileged program, and associates the states of the Markov chain with the unique system calls in the training data. At the detection stage, the probabilities that the Markov chain model supports the system call sequences generated by the program are computed. A low probability indicates an anomalous sequence that may result from intrusive activities. Then a decision rule based on the number of anomalous sequences in a locality frame is adopted to classify the program＇s behavior. The method gives attention to both computational efficiency and detection accuracy, and is especially suitable for on-line detection. It has been applied to practical host-based intrusion detection systems.展开更多
With the capability of the virtual machine monitor, a novel approach for logging system activities is designed. In the design, the guest operating system runs on the virtual machine monitor as non-privileged mode. The...With the capability of the virtual machine monitor, a novel approach for logging system activities is designed. In the design, the guest operating system runs on the virtual machine monitor as non-privileged mode. The redirecting and monitoring modules are added into the virtual machine monitor. When a guest application is calling a system call, it is trapped and redirected from the least privileged level into the virtual machine monitor running in the most privileged level. After logging is finished. it returns to the guest operating system running in the more privileged level and starts the system call. Compared with the traditional methods for logging system activities, the novel method makes it more difficult to destroy or tamper the logs. The preliminary evaluation shows that the prototype is simple and efficient.展开更多
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...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.展开更多
基金the National Grand Fundamental Research "973" Program of China (2004CB318109)the High-Technology Research and Development Plan of China (863-307-7-5)the National Information Security 242 Program ofChina (2005C39).
文摘A novel method for detecting anomalous program behavior is presented, which is applicable to hostbased intrusion detection systems that monitor system call activities. The method constructs a homogeneous Markov chain model to characterize the normal behavior of a privileged program, and associates the states of the Markov chain with the unique system calls in the training data. At the detection stage, the probabilities that the Markov chain model supports the system call sequences generated by the program are computed. A low probability indicates an anomalous sequence that may result from intrusive activities. Then a decision rule based on the number of anomalous sequences in a locality frame is adopted to classify the program＇s behavior. The method gives attention to both computational efficiency and detection accuracy, and is especially suitable for on-line detection. It has been applied to practical host-based intrusion detection systems.
文摘With the capability of the virtual machine monitor, a novel approach for logging system activities is designed. In the design, the guest operating system runs on the virtual machine monitor as non-privileged mode. The redirecting and monitoring modules are added into the virtual machine monitor. When a guest application is calling a system call, it is trapped and redirected from the least privileged level into the virtual machine monitor running in the most privileged level. After logging is finished. it returns to the guest operating system running in the more privileged level and starts the system call. Compared with the traditional methods for logging system activities, the novel method makes it more difficult to destroy or tamper the logs. The preliminary evaluation shows that the prototype is simple and efficient.
文摘以传统有限自动机(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.
