Collaborative Research: CIF: Small: Not All Eggs in One Basket: Authority Distribution for Resilience Against Compromised Nodes in Communication Networks

网络通信系统在社会中的普遍存在引起了越来越多的安全和隐私问题。特别是，这样的问题存在于收集私人用户信息的应用中，如在健康监测、电子商务和金融服务中，以及与关键基础设施相关联的应用中，如在交通、智能电网或过程监督管理系统中。事实上，对于这些应用程序，网络的单个受损/恶意代理或节点可能引发灾难性事件，例如支付赎金以恢复私人数据，大规模停电，服务中断，数据泄露，财务损失或死亡。该项目旨在探索如何将启动关键任务的权限分配给多个节点或网络用户，而不是单个节点或用户，这是一种有效的手段，可以避免出现单点故障，从而在安全漏洞的情况下完全丢失私有数据。此外，拟议的研究研究如何授权分配能够使网络有能力应对受损的设备或人员之前，他们被确定为恶意的，最重要的是，在他们能够做任何伤害。该项目研究超越传统的阈值密码学的新解决方案，以解决具有挑战性的路障，在数据访问和生物特征认证的权限分配。具体而言，该项目旨在克服（i）使用生物识别技术带来的隐私挑战，（ii）需要昂贵的资源作为完全安全的通信渠道，（iii）随着用户数量的增加，缩放行为较差，以及（iv）需要一个与分布式系统不兼容的中央实体，以解决隐私和存储要求之间的根本权衡。该项目包括三个相互关联的重点。第一个推力研究的基本安全和隐私保证，权威分布可以提供在存在的，潜在的未被注意到的，受损的用户或节点。第二个推力调查建设的低复杂度的编码方案的权力分配，在有限的块长度，基于新的方法来自错误控制编码和密码学。第三个目标是通过独立于数据统计的深度学习实现权威分发的通用学习框架。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估而被认为值得支持。

The ubiquity of networked communication systems in society raises ever-growing security and privacy concerns. In particular, such concerns exist for applications that collect private user information, as in health monitoring, e-commerce, and financial services, and applications associated with critical infrastructure as in transportation, smart grids, or process supervisory management systems. Indeed, for these applications, a single compromised/malicious agent or node of the network can provoke catastrophic events such as ransom payments to recover private data, large-scale electricity blackouts, interruptions of service, data breaches, financial losses, or fatalities. This project aims to explore how distributing the authority to launch critical tasks in the hands of multiple, rather than a single, nodes or users of the network can be an efficient means to avoid having a single point of failure and hence losing private data in its entirety in the case of a security breach. Furthermore, the proposed research studies how authority distribution is able to empower networks with the capability of coping with compromised devices or persons before they are identified as malicious and, most importantly, before they are able to do any harm.The project investigates novel solutions beyond traditional threshold cryptography to address challenging roadblocks in authority distribution for data access and biometric authentication. Specifically, the project aims to overcome (i) privacy challenges with the use of biometrics, (ii) the need for costly resources as perfectly secure communication channels, (iii) a poor scaling behavior with the number of users, and (iv) the need for a central entity which is not compatible with distributed systems, to unravel fundamental trade-offs between privacy and storage requirements. The project comprises three interrelated thrusts. The first thrust studies the fundamental security and privacy guarantees that authority distribution can offer in the presence of, potentially unnoticed, compromised users or nodes. The second thrust investigates the construction of low-complexity coding schemes for authority distribution that operate at finite blocklengths, based on novel methods derived from error control coding and cryptography. The third thrust aims to enable a universal learning framework for authority distribution via deep learning that is independent of the data statistics.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.