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Systemic Methodology for Cyber Offense and Defense

机译:网络犯罪和防御系统方法论

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This paper describes a systemic method towards standardization of a cyber weapon effectiveness and effectiveness prediction process to promote consistency and improve cyber weapon system evaluation accuracy - for both offensive and defensive postures. The approach included theoretical examination of existing effectiveness prediction processes for kinetic and directed energy weapons, complemented with technical and social aspects of cyber realm. The examination highlighted several paradigm-shifts needed to transition from purely kinetic-based processes and transition into the realm of combined kinetic and cyber weapons. Components of the new method for cyber weapons are cyber payload assessment, effects identification, and target assessment. The ultimate outcome of method is the 'Probability of Kill' for a cyber weapon paired with a threat and within a given situation. This probability is a function of factors such as intelligence gathered on the latency of information, access points, hardware and software configurations, accuracy and completeness of network map, understanding of operations tempo; likelihood that vulnerabilities being exploited are patched and IT's ability to detect and respond to the delivery of the cyber payload; and probability that the payload will achieve the desired mission effects. Aside from the use of this method for offensive purposes, it can also be mirrored as cyber defense and can serve as basis for developing cyber defense strategies, such as focused counter intelligence on access points, hardware and software configurations, and network map and architecture, comprehensive patching to assure most current and complete patches are deployed, and well trained and equipped IT with ability to detect and respond to cyber payloads.
机译:本文介绍了一种用于促进一致性和提高网络武器系统评估准确性的网络武器效力和有效预测过程的系统方法 - 用于攻击性和防御性姿态。该方法包括对动力学和定向能源武器的现有有效性预测过程的理论审查,辅以网络领域的技术和社会方面。考试强调了从纯粹基于动力学的过程转变和过渡到合并动力学和网络武器领域所需的几种范例转变。网络武器的新方法的组成部分是网络有效载量评估,效果识别和目标评估。方法的终极结果是在与威胁和在特定情况下配对的网络武器的“杀戮概率”。这种概率是智能等因素的函数,这些因素聚集在信息,接入点,硬件和软件配置,网络地图的准确性和完整性,对操作的理解时延迟;被剥削的漏洞的可能性被修补,并且能够检测和响应网络有效载荷的交付;有效载荷将达到所需的任务效果的概率。除了使用这种方法的令人反感的目的,它也可以被镜像为网络防御,可以作为开发网络防御策略的基础,例如在接入点,硬件和软件配置和网络地图和架构上聚焦的反智能,综合修补以确保大多数当前和完整的补丁都已部署,培训良好,并配备了检测和响应网络有效载荷的能力。

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