tBox: A system to protect a "bad" user from targeted and user-oriented attacks

Amur G. Tokhtabayev, Batyrulan Aimyshev, Y. Seitkulov
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Abstract

We introduce tBox system that enables protection from targeted and user-oriented attacks. Such attacks relay on users mistakes such as misinterpreting or ignoring security alerts, which leads to proliferation of malicious objects inside trusted perimeter of cyber-security systems (e.g. exclusion list of AV). These attacks include strategic web compromise, spear phishing, insider threat and social network malware. Moreover, targeted attacks often deliver zero-day malware that is made difficult to be detected, e.g. due to distributed malicious payload. The tBox system allows for protecting even a "bad" user who does not cooperate with security products. To accomplish this, tBox seamlessly transfers user activity with vulnerable applications into specific virtual environment that provides three key factors: user-activity isolation, behavior self-monitoring and security inheritance for user-carried objects. To provide self-monitoring, our team developed a novel technology for deep dynamic analysis of system-wide behavior, which allows for run-time recognition of malicious functionalities including obfuscated and distributed ones. We evaluate the tBox prototype with corpus of real malware families. Results show high efficiency of tBox in detecting and blocking malware while having low system overhead.
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tBox:保护“坏”用户免受定向和面向用户的攻击的系统
我们介绍了tBox系统,使保护免受针对性和面向用户的攻击。此类攻击依赖于用户的错误,例如误解或忽视安全警报,从而导致恶意对象在网络安全系统的可信范围内扩散(例如AV排除列表)。这些攻击包括战略性网络入侵、鱼叉式网络钓鱼、内部威胁和社交网络恶意软件。此外,有针对性的攻击通常会提供难以检测到的零日恶意软件,例如由于分布式恶意负载。tBox系统甚至可以保护不配合安全产品的“坏”用户。为此,tBox将带有易受攻击应用程序的用户活动无缝转移到特定的虚拟环境中,该环境提供了三个关键因素:用户活动隔离、行为自我监控和用户携带对象的安全继承。为了提供自我监控,我们的团队开发了一种新的技术,用于对系统范围内的行为进行深度动态分析,该技术允许在运行时识别恶意功能,包括混淆和分布式功能。我们用真实恶意软件家族的语料库对tBox原型进行了评估。结果表明,tBox在检测和拦截恶意软件方面效率高,且系统开销低。
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