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Window-Based Statistical Analysis Of Timing Subcomponents For Efficient Detection Of Malware In Life-Critical Systems

机译：基于窗口的计时子组件统计分析，可在生命关键系统中有效检测恶意软件

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Securing life-critical embedded systems, particularly medical devices, requires both proactive security measures that prevent intrusions and reactive measures that detect intrusions. This paper presents a novel model for specifying the normal timing for operations in software applications using cumulative distribution functions of timing subcomponent within sliding execution windows. We present a probabilistic formulation for estimating the presence of malware for individual operations by monitoring the internal timing of the different components of the system, and we define thresholds to minimize false positives based on training data. Experimental results with a smart connected pacemaker and three sophisticated mimicry malware scenarios demonstrate improved performance and accuracy compared to state-of-the-art timing-based malware detection.

机译：要确保对生命至关重要的嵌入式系统（尤其是医疗设备）的安全，既需要预防入侵的主动安全措施，也需要检测入侵的被动措施。本文提出了一种新颖的模型，该模型使用滑动执行窗口内的时序子组件的累积分布函数来指定软件应用程序中操作的正常时序。我们提出了一种概率公式，用于通过监视系统不同组件的内部计时来估计单个操作的恶意软件的存在，并且我们根据训练数据定义阈值以最大程度地减少误报。与最新的基于定时的恶意软件检测相比，智能连接的起搏器和三种复杂的模仿恶意软件场景的实验结果证明了改进的性能和准确性。

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来源
《2019 Spring Simulation Conference》|2019年|1-12|共12页
会议地点 Tucson(US)
作者
Nadir Carreon; Allison Gilbreath; Roman Lysecky;
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作者单位

Department of Electrical and Computer Engineering, University of Arizona, Tucson, AZ, USA;

Department of Electrical and Computer Engineering, University of Arizona, Tucson, AZ, USA;

Department of Electrical and Computer Engineering, University of Arizona, Tucson, AZ, USA;

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原文格式 PDF
正文语种 eng
中图分类
关键词
Timing; Malware; Anomaly detection; Monitoring; Runtime; Embedded systems;

机译：时间;恶意软件;异常检测;监视;运行时;嵌入式系统;;

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1. Semantics-Based Online Malware Detection: Towards Efficient Real-Time Protection Against Malware [J] . Das Sanjeev, Liu Yang, Zhang Wei, Information Forensics and Security, IEEE Transactions on . 2016,第2期

机译：基于语义的在线恶意软件检测：针对恶意软件的高效实时保护
2. Volatile memory analysis using the MinHash method for efficient and secured detection of malware in private cloud [J] . Nissim Nir, Lahav Omri, Cohen Aviad, Computers & Security . 2019,第Nova期

机译：使用MinHash方法进行易失性内存分析，可有效，安全地检测私有云中的恶意软件
3. Dynamics and an efficient malware detection system using opcode sequence graph generation and ml algorithm [J] . Bharathi Panduri, Madhurika Vummenthala, Spoorthi Jonnalagadda, E3S Web of Conferences . 2020,第10期

机译：使用操作码序列图生成和ML算法的动态和高效恶意软件检测系统
4. WINDOW-BASED STATISTICAL ANALYSIS OF TIMING SUBCOMPONENTS FOR EFFICIENT DETECTION OF MALWARE IN LIFE-CRITICAL SYSTEMS [C] . Nadir Carreon, Allison Gilbreath, Roman Lysecky Modeling and Simulation in Medicine Symposium . 2019

机译：基于窗口的定时子组件统计分析，以便有效地检测生理系统中恶意软件
5. Efficient and accurate statistical timing analysis for non-linear non-Gaussian variability with incremental attributes. [D] . Dobhal, Ashish. 2006

机译：具有增量属性的非线性非高斯变异性的高效且准确的统计时序分析。
6. A study on efficient detection of network-based IP spoofing DDoS and malware-infected Systems [O] . Jung Woo Seo, Sang Jin Lee -1

机译：基于网络的IP欺骗DDoS和受恶意软件感染的系统的有效检测的研究
7. Window-based Statistical Analysis of Timing Subcomponents for Efficient Detection of Malware in Life-critical Systems [O] . 2019

机译：基于窗口的定时子组件统计分析，以便有效地检测生理系统中恶意软件

Window-Based Statistical Analysis Of Timing Subcomponents For Efficient Detection Of Malware In Life-Critical Systems

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