面向新数据生态下分布式网络安全的隐私管理框架

T. Breaux, Catherine B. Lotrionte
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引用次数: 4

摘要

随着个人、团体或国家试图窃取信息或破坏系统和服务,网络安全越来越依赖于对新出现威胁的提前通知。提前通知依赖于在正确的时间获得正确的信息。这些信息包括可追踪的数字证据,分布在公共和私人网络上,这些网络受各种隐私政策、机构间协议、联邦和州法律以及国际条约的管辖。为了在保护隐私的前提下实现快速、可靠的信息共享,美国政府需要一种平衡隐私与共享需求的方法。在本文中,我们回顾了美国管理政府监督的法律和政策,并描述了隐私管理框架的关键要素,该框架旨在使政府调查成为可能,同时以系统的方式保护隐私。该框架将现有的联邦调查指导方针与第四修正案“对隐私的合理期望”和几项公平信息实践原则所产生的自动决策的担忧联系起来,以确定网络攻击的原因。我们将讨论那些寻求实施该框架的人所面临的技术挑战。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Towards a privacy management framework for distributed cybersecurity in the new data ecology
Cyber security increasingly depends on advance notice of emerging threats as individuals, groups or nations attempt to exfiltrate information or disrupt systems and services. Advance notice relies on having access to the right information at the right time. This information includes trace digital evidence, distributed across public and private networks that are governed by various privacy policies, inter-agency agreements, federal and state laws and international treaties. To enable rapid and assured information sharing that protects privacy, the US government needs a means to balance privacy with the need to share. In this paper, we review US laws and policies governing government surveillance and describe key elements for a privacy management framework that seeks to enable government investigations while protecting privacy in a systematic way. The framework aligns existing Federal investigative guidelines for attributing a cyberattack with concerns for automated decision making that arise from the Fourth Amendment “reasonable expectation of privacy” and several fair information practice principles. We discuss technical challenges for those seeking to implement this framework.
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