Towards a science of trust

Dusko Pavlovic
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引用次数: 5

Abstract

The diverse views of science of security have opened up several alleys towards applying the methods of science to security. We pursue a different kind of connection between science and security. This paper explores the idea that security is not just a suitable subject for science,. but that the process of security is also similar to the process of science. This similarity arises from the fact that both science and security depend on the methods of inductive inference. Because of this dependency, a scientific theory can never be definitely proved, but can only be disproved by new evidence, and improved into a better theory. Because of the same dependency, every security claim and method has a lifetime, and always eventually needs to be improved. In this general framework of security-as-science, we explore the ways to apply the methods of scientific induction in the process of trust. The process of trust building and updating is viewed as hypothesis testing. We propose to formulate the trust hypotheses by the methods of algorithmic learning, and to build more robust trust testing and vetting methodologies on the solid foundations of statistical inference.
走向信任的科学
安全科学的不同观点为科学方法在安全领域的应用开辟了若干条道路。我们追求科学与安全之间的另一种联系。这篇论文探讨了安全不仅仅是一个适合科学研究的课题。但安全的过程也类似于科学的过程。这种相似性源于科学和安全都依赖于归纳推理的方法这一事实。由于这种依赖性,一个科学理论永远不可能被明确地证明,而只能被新的证据推翻,并改进成一个更好的理论。由于同样的依赖关系,每一种安全声明和方法都有生命周期,并且最终总是需要改进的。在安全即科学的总体框架下,探讨了在信任过程中运用科学归纳法的方法。信任建立和更新的过程被视为假设检验。我们建议通过算法学习的方法来制定信任假设,并在统计推断的坚实基础上建立更强大的信任测试和审查方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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