TWC: Small: Hydra - Hybrid Defenses for Resilient Applications: Practical Approaches Towards Defense In Depth

TWC：小型：Hydra - 弹性应用的混合防御：纵深防御的实用方法

• 批准号: 1619211
• 负责人: Michael Franz
• 金额: $ 50万
• 依托单位: University of California-Irvine
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-07-01 至 2020-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1619211&HistoricalAwards=false
• 关键词: TWC; Small; Hydra; Hybrid; Defenses

In popular culture, cyber security is characterized as a cat-and-mouse game: an attacker finds a new exploit, defenders find a corresponding countermeasure, and the game goes on and on. Unfortunately, reality isn't far removed from this fiction: most defenses are reactive to particular threats that have already been discovered, and they are often combined on top of each other, without attempting to integrate them. Combining disjoint security mechanisms in this manner often has the effect that the individual costs of the mechanisms add up, so that at some point it becomes impractical to add more. Biological immune systems in nature do much better than this, combining an innate response against general threats (such as bacteria and viruses) with a learned response against specific previously seen threats. Moreover, the adaptive system doesn't appear to get "slower" as it learns to handle new classes of pathogens. This research focuses on "hybrid" defenses inspired by biological systems.The project investigates practical "defense in depth" approaches that synthesize hybrid defenses that are greater the sum of their parts and that have lower overheads than traditional layered security solutions. This is not trivial, since one must ensure that combining multiple defenses doesn't create (possibly hidden) feature-interaction conflicts, perhaps even leading to new vulnerabilities that an attacker might exploit. The project's approach leverages dynamic diversification, which intersperses randomization with program execution. By rapidly switching between alternative versions of the program at run-time, one can ensure that the flow of control never follows the same path for two different executions of the same program, even when operating on the same inputs. This technique provides the foundation for much of the proposed research and offers probabilistic protection. The project will benefit all domains in which computer security measures have traditionally been constrained by performance considerations, including e-commerce, consumer software, and mobile computing.

在流行文化中，网络安全被描述为一场猫捉老鼠的游戏：攻击者找到一个新的漏洞，防御者找到相应的对策，游戏就这样不断地进行下去。不幸的是，现实与这种幻想相差不远：大多数防御措施都是针对已经发现的特定威胁做出反应的，而且它们通常是叠加在一起的，而不是试图将它们整合在一起。以这种方式组合不相关的安全机制通常会导致机制的单个成本增加，因此在某些时候，添加更多的安全机制变得不切实际。自然界的生物免疫系统比这要好得多，它结合了对一般威胁（如细菌和病毒）的先天反应和对特定先前见过的威胁的后天反应。此外，适应系统在学习处理新类型的病原体时似乎不会变得“慢”。这项研究的重点是受生物系统启发的“混合”防御。该项目研究了实用的“深度防御”方法，这些方法综合了混合防御，这些防御的各部分之和更大，并且比传统的分层安全解决方案具有更低的开销。这不是微不足道的，因为必须确保组合多个防御不会产生（可能隐藏的）功能交互冲突，甚至可能导致攻击者可能利用的新漏洞。该项目的方法利用动态多样化，将随机化与程序执行穿插在一起。通过在运行时在程序的可选版本之间快速切换，可以确保对同一个程序的两次不同执行的控制流永远不会遵循相同的路径，即使在操作相同的输入时也是如此。这种技术为许多提出的研究提供了基础，并提供了概率保护。该项目将使计算机安全措施传统上受到性能考虑限制的所有领域受益，包括电子商务、消费软件和移动计算。