CIF: Small: Collaborative Research:Towards more Secure Systems: Uniformization for Secrecy

随着通信网络在我们的社会中扮演着越来越重要的角色，确保信息传输和存储的保密性已经成为人们越来越关注的问题。诸如异构无线网络和分布式存储网络等新类型的网络正在出现，在这些网络中，现成的加密解决方案的部署面临着一些限制。例如，维护同步私钥和公钥的密钥管理开销；在客户端强加的严格延迟约束下分发密钥的挑战；以及曾经被认为不可能发生的大规模袭击。因此，从网络编码到物理层安全的几种解决方案已经开发出来，以提高现代无线网络中数据的机密性。已经开发了许多与密钥无关和无密钥的方案，以提供额外的抗攻击鲁棒性和更大的网络操作灵活性。这些方案的共同之处在于，它们利用编码数据作为密钥，摆脱了数据是商品、信息包必须独立传输和保护的传统范式。相反，这些方案设想信息包可以以受控的方式混合，从而引入针对对手的内在安全级别。大多数现有的保密结果都依赖于一个关键假设，即数据是均匀分布的，并且从一个数据包到另一个数据包是独立的。不幸的是，最近的结果表明，即使是最优的数据压缩算法也只能在非常弱的意义上统一编码数据的统计信息。因此，在文献中建立的几个安全保证很可能在缺乏任何关于数据一致性假设的证明的鲁棒性的情况下崩溃。该项目的目标是更好地理解密码和数据的统计特性如何影响保密系统的安全性。该项目调查了若干相互关联的研究任务：(i)分析具有改进的均匀性的数据压缩技术的基本限制；（ii）设计低复杂度的统一编码；（iii）此类算法在云存储系统中的应用。其他活动还包括向高中生推广活动。

As communication networks play an increasingly vital role in our society, ensuring the confidentiality of information transmission and storage has become an increasing concern. New classes of networks, such as heterogeneous wireless networks and distributed storage networks, are emerging, in which the deployment of off-the-shelf cryptographic solutions faces several limitations. These include, for instance, the overhead of key management to maintain synchronized private and public keys; the challenge of distributing keys within the stringent delay constraints imposed by clients; and the exposure to large-scale attacks that were once deemed infeasible. Consequently, several solutions from network coding to physical-layer security have been developed to improve the confidentiality of data over modern wireless networks. Many key-independent and keyless schemes have been developed to provide additional robustness against attacks and more flexibility in the network operation. These schemes have in common that they exploit coded data as keys and move away from the traditional paradigm in which data is a commodity and in which information packets must be transmitted and protected independently. Instead, these schemes envision that information packets could be mixed in a controlled manner so as to introduce an intrinsic level of security against adversaries.Most existing secrecy results hinge on the crucial assumption that data is uniformly distributed and independent from a packet to another. Unfortunately, recent results have shown that even optimal data compression algorithms uniformize the statistics of coded data only in a very weak sense. Consequently, several security guarantees established in the literature may well collapse in the absence of any proven robustness with respect to data uniformity assumptions. The objective of this project is to develop a better understanding of how the statistical properties of passwords and data influence the security of secrecy systems. The project investigates several interrelated research tasks: (i) the analysis of the fundamental limits of data-compression techniques with improved uniformity properties; (ii) the design of low-complexity codes for uniformization; (iii) the application of such algorithms in cloud storage systems. Additional activities include an outreach effort to high-school students.