针对目前大多数的函数调用关系分析工具无法分析函数指针、系统启动过程以及可加载模块的函数调用关系的现象,在CG-RTL的基础上提出了基于内核跟踪的动态函数调用图生成方法,并开发了动态函数调用图生成工具DCG-RTL(dynamic call graph ...针对目前大多数的函数调用关系分析工具无法分析函数指针、系统启动过程以及可加载模块的函数调用关系的现象,在CG-RTL的基础上提出了基于内核跟踪的动态函数调用图生成方法,并开发了动态函数调用图生成工具DCG-RTL(dynamic call graph based on RTL)。DCG-RTL在S2E模拟器中运行待跟踪内核,通过指令捕获插件和函数解析插件记录运行时的函数调用和返回信息,分析跟踪信息得到动态和静态函数调用关系,利用CG-RTL工具在浏览器中展示。实验结果表明,DCG-RTL能全面和准确地跟踪包括函数指针引用和可加载内核模块在内的函数调用关系。展开更多
Support vector machine (SVM) technique has recently become a research focus in intrusion detection field for its better generalization performance when given less priori knowledge than other soft-computing techniques....Support vector machine (SVM) technique has recently become a research focus in intrusion detection field for its better generalization performance when given less priori knowledge than other soft-computing techniques. But the randomicity of parameter selection in its implement often prevents it achieving expected performance. By utilizing genetic algorithm (GA) to optimize the parameters in data preprocessing and the training model of SVM simultaneously, a hybrid optimization algorithm is proposed in the paper to address this problem. The experimental results demonstrate that it’s an effective method and can improve the performance of SVM-based intrusion detection system further.展开更多
Predicting anomalous behaviour of a running process using system call trace is a common practice among security community and it is still an active research area. It is a typical pattern recognition problem and can be...Predicting anomalous behaviour of a running process using system call trace is a common practice among security community and it is still an active research area. It is a typical pattern recognition problem and can be dealt with machine learning algorithms. Standard system call datasets were employed to train these algorithms. However, advancements in operating systems made these datasets outdated and un-relevant. Australian Defence Force Academy Linux Dataset (ADFA-LD) and Australian Defence Force Academy Windows Dataset (ADFA-WD) are new generation system calls datasets that contain labelled system call traces for modern exploits and attacks on various applications. In this paper, we evaluate performance of Modified Vector Space Representation technique on ADFA-LD and ADFA-WD datasets using various classification algorithms. Our experimental results show that our method performs well and it helps accurately distinguishing process behaviour through system calls.展开更多
文摘针对目前大多数的函数调用关系分析工具无法分析函数指针、系统启动过程以及可加载模块的函数调用关系的现象,在CG-RTL的基础上提出了基于内核跟踪的动态函数调用图生成方法,并开发了动态函数调用图生成工具DCG-RTL(dynamic call graph based on RTL)。DCG-RTL在S2E模拟器中运行待跟踪内核,通过指令捕获插件和函数解析插件记录运行时的函数调用和返回信息,分析跟踪信息得到动态和静态函数调用关系,利用CG-RTL工具在浏览器中展示。实验结果表明,DCG-RTL能全面和准确地跟踪包括函数指针引用和可加载内核模块在内的函数调用关系。
基金This work was supported by the Research Grant of SEC E-Institute :Shanghai High Institution Grid and the Science Foundation ofShanghai Municipal Commission of Science and Technology No.00JC14052
文摘Support vector machine (SVM) technique has recently become a research focus in intrusion detection field for its better generalization performance when given less priori knowledge than other soft-computing techniques. But the randomicity of parameter selection in its implement often prevents it achieving expected performance. By utilizing genetic algorithm (GA) to optimize the parameters in data preprocessing and the training model of SVM simultaneously, a hybrid optimization algorithm is proposed in the paper to address this problem. The experimental results demonstrate that it’s an effective method and can improve the performance of SVM-based intrusion detection system further.
文摘Predicting anomalous behaviour of a running process using system call trace is a common practice among security community and it is still an active research area. It is a typical pattern recognition problem and can be dealt with machine learning algorithms. Standard system call datasets were employed to train these algorithms. However, advancements in operating systems made these datasets outdated and un-relevant. Australian Defence Force Academy Linux Dataset (ADFA-LD) and Australian Defence Force Academy Windows Dataset (ADFA-WD) are new generation system calls datasets that contain labelled system call traces for modern exploits and attacks on various applications. In this paper, we evaluate performance of Modified Vector Space Representation technique on ADFA-LD and ADFA-WD datasets using various classification algorithms. Our experimental results show that our method performs well and it helps accurately distinguishing process behaviour through system calls.
