First CPIR Protocol with Data-Dependent Computation

We design a new $(n, 1)$-CPIR protocol $\mathsf{BddCpir}$ for $\ell$-bit strings as a combination of a noncryptographic (BDD-based) data structure and a more basic cryptographic primitive (communication-efficient $(2, 1)$-CPIR). $\mathsf{BddCpir}$ is the first CPIR protocol where server\u27s online computation depends substantially on the concrete database. We then show that (a) for reasonably small values of $\ell$, $\mathsf{BddCpir}$ is guaranteed to have simultaneously log-squared communication and sublinear online computation, and (b) $\mathsf{BddCpir}$ can handle huge but sparse matrices, common in data-mining applications, significantly more efficiently compared to all previous protocols. The security of $\mathsf{BddCpir}$ can be based on the well-known Decisional Composite Residuosity assumptio

A practical and secure multi-keyword search method over encrypted cloud data

Cloud computing technologies become more and more popular every year, as many organizations tend to outsource their data utilizing robust and fast services of clouds while lowering the cost of hardware ownership. Although its benefits are welcomed, privacy is still a remaining concern that needs to be addressed. We propose an efficient privacy-preserving search method over encrypted cloud data that utilizes minhash functions. Most of the work in literature can only support a single feature search in queries which reduces the effectiveness. One of the main advantages of our proposed method is the capability of multi-keyword search in a single query. The proposed method is proved to satisfy adaptive semantic security definition. We also combine an effective ranking capability that is based on term frequency-inverse document frequency (tf-idf) values of keyword document pairs. Our analysis demonstrates that the proposed scheme is proved to be privacy-preserving, efficient and effective

Privately Connecting Mobility to Infectious Diseases via Applied Cryptography

Human mobility is undisputedly one of the critical factors in infectious disease dynamics. Until a few years ago, researchers had to rely on static data to model human mobility, which was then combined with a transmission model of a particular disease resulting in an epidemiological model. Recent works have consistently been showing that substituting the static mobility data with mobile phone data leads to significantly more accurate models. While prior studies have exclusively relied on a mobile network operator's subscribers' aggregated data, it may be preferable to contemplate aggregated mobility data of infected individuals only. Clearly, naively linking mobile phone data with infected individuals would massively intrude privacy. This research aims to develop a solution that reports the aggregated mobile phone location data of infected individuals while still maintaining compliance with privacy expectations. To achieve privacy, we use homomorphic encryption, zero-knowledge proof techniques, and differential privacy. Our protocol's open-source implementation can process eight million subscribers in one and a half hours. Additionally, we provide a legal analysis of our solution with regards to the EU General Data Protection Regulation.Comment: Added differentlial privacy experiments and new benchmark

Industrial Feasibility of Private Information Retrieval

A popular security problem in database management is how to guarantee to a querying party that the database owner will not learn anything about the data that is retrieved --- a problem known as Private Information Retrieval (PIR). While a variety of PIR schemes are known, they are rarely considered for practical use cases yet. We investigate the feasibility of PIR in the telecommunications world to open up data of carriers to external parties. To this end, we first provide a comparative survey of the current PIR state of the art (including ORAM schemes as a generalized concept) as well as implementation and analysis of two PIR schemes for the considered use case. While an overall conclusion is that PIR techniques are not too far away from practical use in specific cases, we see ORAM as a more suitable candidate for further R\&D investment

A fast single server private information retrieval protocol with low communication cost

Existing single server Private Information Retrieval (PIR) protocols are far from practical. To be practical, a single server PIR protocol has to be both communicationally and computationally efficient. In this paper, we present a single server PIR protocol that has low communication cost and is much faster than existing protocols. A major building block of the PIR protocol in this paper is a tree-based compression scheme, which we call folding/unfolding. This compression scheme enables us to lower the communication complexity to O(loglogn). The other major building block is the BGV fully homomorphic encryption scheme. We show how we design the protocol to exploit the internal parallelism of the BGV scheme. This significantly reduces the server side computational overhead and makes our protocol much faster than the existing protocols. Our protocol can be further accelerated by utilising hardware parallelism. We have built a prototype of the protocol. We report on the performance of our protocol based on the prototype and compare it with the current most efficient protocols

A Simpler Rate-Optimal CPIR Protocol

In PETS 2015, Kiayias, Leonardos, Lipmaa, Pavlyk, and Tang proposed the first $(n, 1)$-CPIR protocol with rate $1 - o (1)$. They use advanced techniques from multivariable calculus (like the Newton-Puiseux algorithm) to establish optimal rate among a large family of different CPIR protocols. It is only natural to ask whether one can achieve similar rate but with a much simpler analysis. We propose parameters to the earlier $(n, 1)$-CPIR protocol of Lipmaa (ISC 2005), obtaining a CPIR protocol that is asymptotically almost as communication-efficient as the protocol of Kiayias et al. However, for many relevant parameter choices, it is slightly more communication-efficient, due to the cumulative rounding errors present in the protocol of Kiayias et al. Moreover, the new CPIR protocol is simpler to understand, implement, and analyze. The new CPIR protocol can be used to implement (computationally inefficient) FHE with rate $1 - o (1)$