Mitigating Leakage in Secure Cloud-Hosted Data Structures: Volume-Hiding for Multi-Maps via Hashing

Volume leakage has recently been identified as a major threat to the security of cryptographic cloud-based data structures by Kellaris et al. [CCS’16] (see also the attacks in Grubbs et al. [CCS’18] and Lacharité et al. [S&P’18]). In this work, we focus on volume-hiding implementations of encrypted multi-maps as first considered by Kamara and Moataz [Eurocrypt’19]. Encrypted multi-maps consist of outsourcing the storage of a multi-map to an untrusted server, such as a cloud storage system, while maintaining the ability to perform private queries. Volume-hiding encrypted multi-maps ensure that the number of responses (volume) for any query remains hidden from the adversarial server. As a result, volume-hiding schemes can prevent leakage attacks that leverage the adversary’s knowledge of the number of query responses to compromise privacy. We present both conceptual and algorithmic contributions towards volume-hiding encrypted multi-maps. We introduce the first formal definition of volume-hiding leakage functions. In terms of design, we present the first volume-hiding encrypted multi-map dprfMM whose storage and query complexity are both asymptotically optimal. Furthermore, we experimentally show that our construction is practically efficient. Our server storage is smaller than the best previous construction while we improve query complexity by a factor of 10-16x. In addition, we introduce the notion of differentially private volume-hiding leakage functions which strikes a better, tunable balance between privacy and efficiency. To accompany our new notion, we present a differentially private volume-hiding encrypted multi-map dpMM whose query complexity is the volume of the queried key plus an additional logarithmic factor. This is a significant improvement compared to all previous volume-hiding schemes whose query overhead was the maximum volume of any key. In natural settings, our construction improves the average query overhead by a factor of 150-240x over the previous best volume-hiding construction even when considering small privacy budget of $\epsilon = 0.2$

Range Search over Encrypted Multi-Attribute Data

This work addresses expressive queries over encrypted data by presenting the first systematic study of multi-attribute range search on a symmetrically encrypted database outsourced to an honest-but-curious server. Prior work includes a thorough analysis of single-attribute range search schemes (e.g. Demertzis et al. 2016) and a proposed high-level approach for multi-attribute schemes (De Capitani di Vimercati et al. 2021). We first introduce a flexible framework for building secure range search schemes over multiple attributes (dimensions) by adapting a broad class of geometric search data structures to operate on encrypted data. Our framework encompasses widely used data structures such as multi-dimensional range trees and quadtrees, and has strong security properties that we formally prove. We then develop six concrete highly parallelizable range search schemes within our framework that offer a sliding scale of efficiency and security tradeoffs to suit the needs of the application. We evaluate our schemes with a formal complexity and security analysis, a prototype implementation, and an experimental evaluation on real-world datasets

CCA-Secure Deterministic Identity-Based Encryption Scheme

Deterministic public-key encryption, encrypting a plaintext into a unique ciphertext without involving any randomness, was introduced by Bellare, Boldyreva, and O'Neill (CRYPTO 2007) as a realistic alternative to some inherent drawbacks in randomized public-key encryption. Bellare, Kiltz, Peikert and Waters (EUROCRYPT 2012) bring deterministic public-key encryption to the identity-based setting, and propose deterministic identity-based encryption scheme (DIBE). Although the construc- tions of chosen plaintext attack (CPA) secure DIBE scheme have been studied intensively, the construction of chosen ciphertext attack (CCA) secure DIBE scheme is still challenging problems. In this paper, we introduce the notion of identity-based all-but-one trapdoor functions (IB-ABO-TDF), which is an extension version of all-but-one lossy trapdoor function in the public-key setting. We give a instantiation of IB-ABO-TDF under decisional linear assumption. Based on an identity-based lossy trapdoor function and our IB-ABO-TDF, we present a generic construction of CCA-secure DIBE scheme

Hidden in the Cloud : Advanced Cryptographic Techniques for Untrusted Cloud Environments

In the contemporary digital age, the ability to search and perform operations on encrypted data has become increasingly important. This significance is primarily due to the exponential growth of data, often referred to as the "new oil," and the corresponding rise in data privacy concerns. As more and more data is stored in the cloud, the need for robust security measures to protect this data from unauthorized access and misuse has become paramount. One of the key challenges in this context is the ability to perform meaningful operations on the data while it remains encrypted. Traditional encryption techniques, while providing a high level of security, render the data unusable for any practical purpose other than storage. This is where advanced cryptographic protocols like Symmetric Searchable Encryption (SSE), Functional Encryption (FE), Homomorphic Encryption (HE), and Hybrid Homomorphic Encryption (HHE) come into play. These protocols not only ensure the confidentiality of data but also allow computations on encrypted data, thereby offering a higher level of security and privacy. The ability to search and perform operations on encrypted data has several practical implications. For instance, it enables efficient Boolean queries on encrypted databases, which is crucial for many "big data" applications. It also allows for the execution of phrase searches, which are important for many machine learning applications, such as intelligent medical data analytics. Moreover, these capabilities are particularly relevant in the context of sensitive data, such as health records or financial information, where the privacy and security of user data are of utmost importance. Furthermore, these capabilities can help build trust in digital systems. Trust is a critical factor in the adoption and use of digital services. By ensuring the confidentiality, integrity, and availability of data, these protocols can help build user trust in cloud services. This trust, in turn, can drive the wider adoption of digital services, leading to a more inclusive digital society. However, it is important to note that while these capabilities offer significant advantages, they also present certain challenges. For instance, the computational overhead of these protocols can be substantial, making them less suitable for scenarios where efficiency is a critical requirement. Moreover, these protocols often require sophisticated key management mechanisms, which can be challenging to implement in practice. Therefore, there is a need for ongoing research to address these challenges and make these protocols more efficient and practical for real-world applications. The research publications included in this thesis offer a deep dive into the intricacies and advancements in the realm of cryptographic protocols, particularly in the context of the challenges and needs highlighted above. Publication I presents a novel approach to hybrid encryption, combining the strengths of ABE and SSE. This fusion aims to overcome the inherent limitations of both techniques, offering a more secure and efficient solution for key sharing and access control in cloud-based systems. Publication II further expands on SSE, showcasing a dynamic scheme that emphasizes forward and backward privacy, crucial for ensuring data integrity and confidentiality. Publication III and Publication IV delve into the potential of MIFE, demonstrating its applicability in real-world scenarios, such as designing encrypted private databases and additive reputation systems. These publications highlight the transformative potential of MIFE in bridging the gap between theoretical cryptographic concepts and practical applications. Lastly, Publication V underscores the significance of HE and HHE as a foundational element for secure protocols, emphasizing its potential in devices with limited computational capabilities. In essence, these publications not only validate the importance of searching and performing operations on encrypted data but also provide innovative solutions to the challenges mentioned. They collectively underscore the transformative potential of advanced cryptographic protocols in enhancing data security and privacy, paving the way for a more secure digital future

Rich Queries on Encrypted Data: Beyond Exact Matches

We extend the searchable symmetric encryption (SSE) protocol of [Cash et al., Crypto\u2713] adding support for range, substring, wildcard, and phrase queries, in addition to the Boolean queries supported in the original protocol. Our techniques apply to the basic single-client scenario underlying the common SSE setting as well as to the more complex Multi-Client and Outsourced Symmetric PIR extensions of [Jarecki et al., CCS\u2713]. We provide performance information based on our prototype implementation, showing the practicality and scalability of our techniques to very large databases, thus extending the performance results of [Cash et al., NDSS\u2714] to these rich and comprehensive query types

Improving Efficiency, Expressiveness and Security of Searchable Encryption

A large part of our personal data, ranging from medical and financial records to our social activity, is stored online in cloud servers. Frequent data breaches threaten to expose these data to malicious third parties, often with catastrophic consequences (estimated to several billion of US dollars annually). In this thesis, we use, extend and improve Searchable Encryption (SE) in order to build the next generation encrypted databases/systems that will prevent such undesirable situations. Our goal is to build systems that are both practical and provably secure, while allowing expressive search and computation on encrypted data. Towards this goal, we have proposed new SE schemes that achieve the following: (i) have better search/computation time, (ii) allow expressive queries such as range, join, group-by, as well as dynamic query workloads, and (iii) provide new adjustable security-efficiency trade-offs---leading to robust and efficient schemes even against very powerful adversaries

Machine-Checked Formalisation and Verification of Cryptographic Protocols

PhD ThesisAiming for strong security assurance, researchers in academia and industry focus their interest on formal verification of cryptographic constructions. Automatising formal verification has proved itself to be a very difficult task, where the main challenge is to support generic constructions and theorems, and to carry out the mathematical proofs. This work focuses on machine-checked formalisation and automatic verification of cryptographic protocols. One aspect we covered is the novel support for generic schemes and real-world constructions among old and novel protocols: key exchange schemes (Simple Password Exponential Key Exchange, SPEKE), commitment schemes (with the popular Pedersen scheme), sigma protocols (with the Schnorr’s zero-knowledge proof of knowledge protocol), and searchable encryption protocols (Sophos). We also investigated aspects related to the reasoning of simulation based proofs, where indistinguishability of two different algorithms by any adversary is the crucial point to prove privacy-related properties. We embedded information-flow techniques into the EasyCrypt core language, then we show that our effort not only makes some proofs easier and (sometimes) fewer, but is also more powerful than other existing techniques in particular situations