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Survivability Analysis of a Computer System Under an Advanced Persistent Threat Attack

机译:持续威胁威胁下计算机系统的生存能力分析

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Computer systems are potentially targeted by cybercrimi-nals by means of specially crafted malicious software called Advanced Persistent Threats (APTs). As a consequence, any security attribute of the computer system may be compromised: disruption of service (availability), unauthorized data modification (integrity), or exfiltration of sensitive data (confidentiality). An APT starts with the exploitation of software vulnerability within the system. Thus, vulnerability mitigation strategies must be designed and deployed in a timely manner to reduce the window of exposure of vulnerable systems. In this paper, we evaluate the survivability of a computer system under an APT attack using a Markov model. Generation and solution of the Markov model are facilitated by means of a high-level formalism based on stochastic Petri nets. Survivability metrics are defined to quantify security attributes of the system from the public announcement of a software vulnerability and during the system recovery. The proposed model and metrics not only enable us to quantitatively assess the system survivability in terms of security attributes but also provide insights on the cost/revenue tradeoffs of investment efforts in system recovery such as vulnerability mitigation strategies. Sensitivity analysis through numerical experiments is carried out to study the impact of key parameters on system secure survivability.
机译:计算机系统通过Cyber​​Crimi-NALS通过特制的恶意软件来定位,称为高级持久威胁(APTS)。结果,计算机系统的任何安全属性可能会受到影响:服务中断(可用性),未授权的数据修改(完整性)或敏感数据的exfiltration(机密性)。 APT从系统内的软件漏洞开发。因此,必须及时设计和部署漏洞缓解策略,以减少弱势系统的曝光窗口。在本文中,我们使用Markov模型评估了计算机系统在APT攻击下的生存能力。通过基于随机培养网的高级形式主义,促进了马尔可夫模型的生成和解决方案。救用性度量定义为量化系统的安全属性,从公开发布软件漏洞和系统恢复过程中。拟议的模型和指标不仅使我们能够在安全属性方面可以定量评估系统生存能力,而且还提供了对系统恢复中投资努力的成本/收入权衡的见解,例如漏洞缓解策略。通过数值实验进行敏感性分析,以研究关键参数对系统安全生存能力的影响。

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