Cryptographic Tools for Privacy Preservation

Data permeates every aspect of our daily life and it is the backbone of our digitalized society. Smartphones, smartwatches and many more smart devices measure, collect, modify and share data in what is known as the Internet of Things.Often, these devices don’t have enough computation power/storage space thus out-sourcing some aspects of the data management to the Cloud. Outsourcing computation/storage to a third party poses natural questions regarding the security and privacy of the shared sensitive data.Intuitively, Cryptography is a toolset of primitives/protocols of which security prop- erties are formally proven while Privacy typically captures additional social/legislative requirements that relate more to the concept of “trust” between people, “how” data is used and/or “who” has access to data. This thesis separates the concepts by introducing an abstract model that classifies data leaks into different types of breaches. Each class represents a specific requirement/goal related to cryptography, e.g. confidentiality or integrity, or related to privacy, e.g. liability, sensitive data management and more.The thesis contains cryptographic tools designed to provide privacy guarantees for different application scenarios. In more details, the thesis:(a) defines new encryption schemes that provide formal privacy guarantees such as theoretical privacy definitions like Differential Privacy (DP), or concrete privacy-oriented applications covered by existing regulations such as the European General Data Protection Regulation (GDPR);(b) proposes new tools and procedures for providing verifiable computation’s guarantees in concrete scenarios for post-quantum cryptography or generalisation of signature schemes;(c) proposes a methodology for utilising Machine Learning (ML) for analysing the effective security and privacy of a crypto-tool and, dually, proposes a secure primitive that allows computing specific ML algorithm in a privacy-preserving way;(d) provides an alternative protocol for secure communication between two parties, based on the idea of communicating in a periodically timed fashion

Privacy in the Smart City - Applications, Technologies, Challenges and Solutions

Many modern cities strive to integrate information technology into every aspect of city life to create so-called smart cities. Smart cities rely on a large number of application areas and technologies to realize complex interactions between citizens, third parties, and city departments. This overwhelming complexity is one reason why holistic privacy protection only rarely enters the picture. A lack of privacy can result in discrimination and social sorting, creating a fundamentally unequal society. To prevent this, we believe that a better understanding of smart cities and their privacy implications is needed. We therefore systematize the application areas, enabling technologies, privacy types, attackers and data sources for the attacks, giving structure to the fuzzy term “smart city”. Based on our taxonomies, we describe existing privacy-enhancing technologies, review the state of the art in real cities around the world, and discuss promising future research directions. Our survey can serve as a reference guide, contributing to the development of privacy-friendly smart cities

Preserving Privacy Against Side-Channel Leaks

The privacy preserving issues have received significant attentions in various domains. Various models and techniques have been proposed to achieve optimal privacy with minimal costs. However, side-channel leakages (such as, publicly-known algorithms of data publishing, observable traffic information in web application, fine-grained readings in smart metering) further complicate the process of privacy preservation. In this thesis, we make the first effort on investigating a general framework to model side-channel attacks across different domains and applying the framework to various categories of applications. In privacy-preserving data publishing with publicly-known algorithms, we first theoretically study a generic strategy independent of data utility measures and syntactic privacy properties. We then propose an efficient approach to preserving diversity. In privacy-preserving traffic padding in Web applications, we first propose a formal PPTP model to quantify the privacies and costs based on the key observation about the similarity between data publishing and traffic padding. We then introduce randomness into the previous solutions to provide background knowledge-resistant privacy guarantee. In privacy-preserving smart metering, we propose a light-weight approach to simultaneously preserving privacy on both billing and consumption aggregation based on the key observation about the privacy issue beyond the fine-grained readings

Shared and Searchable Encrypted Data for Untrusted Servers

Current security mechanisms pose a risk for organisations that outsource their data management to untrusted servers. Encrypting and decrypting sensitive data at the client side is the normal approach in this situation but has high communication and computation overheads if only a subset of the data is required, for example, selecting records in a database table based on a keyword search. New cryptographic schemes have been proposed that support encrypted queries over encrypted data but all depend on a single set of secret keys, which implies single user access or sharing keys among multiple users, with key revocation requiring costly data re-encryption. In this paper, we propose an encryption scheme where each authorised user in the system has his own keys to encrypt and decrypt data. The scheme supports keyword search which enables the server to return only the encrypted data that satisfies an encrypted query without decrypting it. We provide two constructions of the scheme giving formal proofs of their security. We also report on the results of a prototype implementation. This research was supported by the UK’s EPSRC research grant EP/C537181/1. The authors would like to thank the members of the Policy Research Group at Imperial College for their support

Key exchange with the help of a public ledger

Blockchains and other public ledger structures promise a new way to create globally consistent event logs and other records. We make use of this consistency property to detect and prevent man-in-the-middle attacks in a key exchange such as Diffie-Hellman or ECDH. Essentially, the MitM attack creates an inconsistency in the world views of the two honest parties, and they can detect it with the help of the ledger. Thus, there is no need for prior knowledge or trusted third parties apart from the distributed ledger. To prevent impersonation attacks, we require user interaction. It appears that, in some applications, the required user interaction is reduced in comparison to other user-assisted key-exchange protocols