Accurate and efficient exploit capture and classification

Accurate and efficient exploit capture and classification
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准确高效的漏洞捕获和分类

DOI:
10.1007/s11432-016-5521-0
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发表时间:
2016-09
期刊:
SCIENCE CHINA
影响因子:
--
通讯作者:
Xinhui HAN
Xinhui HAN
中科院分区:
其他
文献类型:
--
作者:
Yu DING;Tao WEI;Hui XUE;Yulong ZHANG;Chao ZHANG;Xinhui HAN

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软件漏洞,特别是零日漏洞,是主要的安全威胁。每天,安全专家都会从蜜罐、恶意软件取证和地下渠道发现并收集大量漏洞。然而,没有简单的方法可以将这些漏洞分类为有意义的类别,并加速诊断和详细分析。为了满足这一需求,我们提出了SeismoMeter,它可以识别控制流劫持,并通过结合近似控制流的完整性,快速动态污点分析和API沙箱计划的数据攻击。一旦检测到漏洞事件,SeismoMeter会生成一个简洁的数据表示,称为漏洞骨架,以描述捕获的漏洞。SeismoMeter然后通过对提取的骨架执行距离计算将捕获的漏洞分类为不同的漏洞家族。为了评估SeismoMeter的效率,我们使用来自公共漏洞数据库(如Metasploit)的漏洞样本以及野生捕获的漏洞进行了现场测试。我们的实验表明,SeismoMeter是一个实用的系统,成功地检测和正确分类所有这些利用攻击。
Software exploits, especially zero-day exploits, are major security threats. Every day, security experts discover and collect numerous exploits from honeypots, malware forensics, and underground channels. However, no easy methods exist to classify these exploits into meaningful categories and to accelerate diagnosis as well as detailed analysis. To address this need, we present SeismoMeter, which recognizes both control-flowhijacking, and data-only attacks by combining approximate control-flow integrity, fast dynamic taint analysis and API sandboxing schemes. Once it detects an exploit incident, SeismoMeter generates a succinct data representation, called an exploit skeleton, to characterize the captured exploit. SeismoMeter then classifies the captured exploits into different exploit families by performing distance computing on the extracted skeletons. To evaluate the efficiency of SeismoMeter, we conduct a field test using exploit samples from public exploit databases, such as Metasploit, as well as wild-captured exploits. Our experiments demonstrate that SeismoMeter is a practical system that successfully detects and correctly classifies all these exploit attacks.
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