Lattice-Based Dual Receiver Encryption and More

Dual receiver encryption (DRE), proposed by Diament et al. at ACM CCS 2004, is a special extension notion of public-key encryption, which enables two independent receivers to decrypt a ciphertext into a same plaintext. This primitive is quite useful in designing combined public key cryptosystems and denial of service attack-resilient protocols. Up till now, a series of DRE schemes are constructed from bilinear pairing groups and lattices. In this work, we introduce a construction of lattice-based DRE. Our scheme is indistinguishable against chosen-ciphertext attacks (IND-CCA) from the standard Learning with Errors (LWE) assumption with a public key of bit-size about $2nm\log q$, where $m$ and $q$ are small polynomials in $n$. Additionally, for the DRE notion in the identity-based setting, identity-based DRE (IB-DRE), we also give a lattice-based IB-DRE scheme that achieves chosen-plaintext and adaptively chosen identity security based on the LWE assumption with public parameter size about $(2\ell +1)nm\log q$, where $\ell$ is the bit-size of the identity in the scheme

Decoding by Embedding: Correct Decoding Radius and DMT Optimality

The closest vector problem (CVP) and shortest (nonzero) vector problem (SVP) are the core algorithmic problems on Euclidean lattices. They are central to the applications of lattices in many problems of communications and cryptography. Kannan's \emph{embedding technique} is a powerful technique for solving the approximate CVP, yet its remarkable practical performance is not well understood. In this paper, the embedding technique is analyzed from a \emph{bounded distance decoding} (BDD) viewpoint. We present two complementary analyses of the embedding technique: We establish a reduction from BDD to Hermite SVP (via unique SVP), which can be used along with any Hermite SVP solver (including, among others, the Lenstra, Lenstra and Lov\'asz (LLL) algorithm), and show that, in the special case of LLL, it performs at least as well as Babai's nearest plane algorithm (LLL-aided SIC). The former analysis helps to explain the folklore practical observation that unique SVP is easier than standard approximate SVP. It is proven that when the LLL algorithm is employed, the embedding technique can solve the CVP provided that the noise norm is smaller than a decoding radius $\lambda_1/(2\gamma)$, where $\lambda_1$ is the minimum distance of the lattice, and $\gamma \approx O(2^{n/4})$. This substantially improves the previously best known correct decoding bound $\gamma \approx {O}(2^{n})$. Focusing on the applications of BDD to decoding of multiple-input multiple-output (MIMO) systems, we also prove that BDD of the regularized lattice is optimal in terms of the diversity-multiplexing gain tradeoff (DMT), and propose practical variants of embedding decoding which require no knowledge of the minimum distance of the lattice and/or further improve the error performance.Comment: To appear in IEEE Transactions on Information Theor

A Performance Evaluation of Pairing-Based Broadcast Encryption Systems

In a broadcast encryption system, a sender can encrypt a message for any subset of users who are listening on a broadcast channel. The goal of broadcast encryption is to leverage the broadcasting structure to achieve better efficiency than individually encrypting to each user; in particular, reducing the bandwidth (i.e., ciphertext size) required to transmit securely, although other factors such as public and private key size and the time to execute setup, encryption and decryption are also important. In this work, we conduct a detailed performance evaluation of eleven public-key, pairing-based broadcast encryption schemes offering different features and security guarantees, including public-key, identity-based, traitor-tracing, private linear and augmented systems. We implemented each system using the MCL Java pairings library, reworking some of the constructions to achieve better efficiency. We tested their performance on a variety of parameter choices, resulting in hundreds of data points to compare, with some interesting results from the classic Boneh-Gentry-Waters scheme (CRYPTO 2005) to Zhandry\u27s recent generalized scheme (CRYPTO 2020), and more. We combine this performance data and knowledge of the systems\u27 features with data we collected on practical usage scenarios to determine which schemes are likely to perform best for certain applications, such as video streaming services, online gaming, live sports betting and smartphone streaming. This work can inform both practitioners and future cryptographic designs in this area

International Symposium on Mathematics, Quantum Theory, and Cryptography

This open access book presents selected papers from International Symposium on Mathematics, Quantum Theory, and Cryptography (MQC), which was held on September 25-27, 2019 in Fukuoka, Japan. The international symposium MQC addresses the mathematics and quantum theory underlying secure modeling of the post quantum cryptography including e.g. mathematical study of the light-matter interaction models as well as quantum computing. The security of the most widely used RSA cryptosystem is based on the difficulty of factoring large integers. However, in 1994 Shor proposed a quantum polynomial time algorithm for factoring integers, and the RSA cryptosystem is no longer secure in the quantum computing model. This vulnerability has prompted research into post-quantum cryptography using alternative mathematical problems that are secure in the era of quantum computers. In this regard, the National Institute of Standards and Technology (NIST) began to standardize post-quantum cryptography in 2016. This book is suitable for postgraduate students in mathematics and computer science, as well as for experts in industry working on post-quantum cryptography

International Symposium on Mathematics, Quantum Theory, and Cryptography

This open access book presents selected papers from International Symposium on Mathematics, Quantum Theory, and Cryptography (MQC), which was held on September 25-27, 2019 in Fukuoka, Japan. The international symposium MQC addresses the mathematics and quantum theory underlying secure modeling of the post quantum cryptography including e.g. mathematical study of the light-matter interaction models as well as quantum computing. The security of the most widely used RSA cryptosystem is based on the difficulty of factoring large integers. However, in 1994 Shor proposed a quantum polynomial time algorithm for factoring integers, and the RSA cryptosystem is no longer secure in the quantum computing model. This vulnerability has prompted research into post-quantum cryptography using alternative mathematical problems that are secure in the era of quantum computers. In this regard, the National Institute of Standards and Technology (NIST) began to standardize post-quantum cryptography in 2016. This book is suitable for postgraduate students in mathematics and computer science, as well as for experts in industry working on post-quantum cryptography

Advances in Information Security and Privacy

With the recent pandemic emergency, many people are spending their days in smart working and have increased their use of digital resources for both work and entertainment. The result is that the amount of digital information handled online is dramatically increased, and we can observe a significant increase in the number of attacks, breaches, and hacks. This Special Issue aims to establish the state of the art in protecting information by mitigating information risks. This objective is reached by presenting both surveys on specific topics and original approaches and solutions to specific problems. In total, 16 papers have been published in this Special Issue

Efficient Authentication, Node Clone Detection, and Secure Data Aggregation for Sensor Networks

Sensor networks are innovative wireless networks consisting of a large number of low-cost, resource-constrained sensor nodes that collect, process, and transmit data in a distributed and collaborative way. There are numerous applications for wireless sensor networks, and security is vital for many of them. However, sensor nodes suffer from many constraints, including low computation capability, small memory, limited energy resources, susceptibility to physical capture, and the lack of infrastructure, all of which impose formidable security challenges and call for innovative approaches. In this thesis, we present our research results on three important aspects of securing sensor networks: lightweight entity authentication, distributed node clone detection, and secure data aggregation. As the technical core of our lightweight authentication proposals, a special type of circulant matrix named circulant-P2 matrix is introduced. We prove the linear independence of matrix vectors, present efficient algorithms on matrix operations, and explore other important properties. By combining circulant-P2 matrix with the learning parity with noise problem, we develop two one-way authentication protocols: the innovative LCMQ protocol, which is provably secure against all probabilistic polynomial-time attacks and provides remarkable performance on almost all metrics except one mild requirement for the verifier's computational capacity, and the HB$^C$ protocol, which utilizes the conventional HB-like authentication structure to preserve the bit-operation only computation requirement for both participants and consumes less key storage than previous HB-like protocols without sacrificing other performance. Moreover, two enhancement mechanisms are provided to protect the HB-like protocols from known attacks and to improve performance. For both protocols, practical parameters for different security levels are recommended. In addition, we build a framework to extend enhanced HB-like protocols to mutual authentication in a communication-efficient fashion. Node clone attack, that is, the attempt by adversaries to add one or more nodes to the network by cloning captured nodes, imposes a severe threat to wireless sensor networks. To cope with it, we propose two distributed detection protocols with difference tradeoffs on network conditions and performance. The first one is based on distributed hash table, by which a fully decentralized, key-based caching and checking system is constructed to deterministically catch cloned nodes in general sensor networks. The protocol performance of efficient storage consumption and high security level is theoretically deducted through a probability model, and the resulting equations, with necessary adjustments for real application, are supported by the simulations. The other is the randomly directed exploration protocol, which presents notable communication performance and minimal storage consumption by an elegant probabilistic directed forwarding technique along with random initial direction and border determination. The extensive experimental results uphold the protocol design and show its efficiency on communication overhead and satisfactory detection probability. Data aggregation is an inherent requirement for many sensor network applications, but designing secure mechanisms for data aggregation is very challenging because the aggregation nature that requires intermediate nodes to process and change messages, and the security objective to prevent malicious manipulation, conflict with each other to a great extent. To fulfill different challenges of secure data aggregation, we present two types of approaches. The first is to provide cryptographic integrity mechanisms for general data aggregation. Based on recent developments of homomorphic primitives, we propose three integrity schemes: a concrete homomorphic MAC construction, homomorphic hash plus aggregate MAC, and homomorphic hash with identity-based aggregate signature, which provide different tradeoffs on security assumption, communication payload, and computation cost. The other is a substantial data aggregation scheme that is suitable for a specific and popular class of aggregation applications, embedded with built-in security techniques that effectively defeat outside and inside attacks. Its foundation is a new data structure---secure Bloom filter, which combines HMAC with Bloom filter. The secure Bloom filter is naturally compatible with aggregation and has reliable security properties. We systematically analyze the scheme's performance and run extensive simulations on different network scenarios for evaluation. The simulation results demonstrate that the scheme presents good performance on security, communication cost, and balance

Cryptographic Foundations For Control And Optimization: Making Cloud-Based And Networked Decisions On Encrypted Data

Advances in communication technologies and computational power have determined a technological shift in the data paradigm. The resulting architecture requires sensors to send local data to the cloud for global processing such as estimation, control, decision and learning, leading to both performance improvement and privacy concerns. This thesis explores the emerging field of private control for Internet of Things, where it bridges dynamical systems and computations on encrypted data, using applied cryptography and information-theoretic tools.Our research contributions are privacy-preserving interactive protocols for cloud-outsourced decisions and data processing, as well as for aggregation over networks in multi-agent systems, both of which are essential in control theory and machine learning. In these settings, we guarantee privacy of the data providers\u27 local inputs over multiple time steps, as well as privacy of the cloud service provider\u27s proprietary information. Specifically, we focus on (i) private solutions to cloud-based constrained quadratic optimization problems from distributed private data; (ii) oblivious distributed weighted sum aggregation; (iii) linear and nonlinear cloud-based control on encrypted data; (iv) private evaluation of cloud-outsourced data-driven control policies with sparsity and low-complexity requirements. In these scenarios, we require computational privacy and stipulate that each participant is allowed to learn nothing more than its own result of the computation. Our protocols employ homomorphic encryption schemes and secure multi-party computation tools with the purpose of performing computations directly on encrypted data, such that leakage of private information at the computing entity is minimized. To this end, we co-design solutions with respect to both control performance and privacy specifications, and we streamline their implementation by exploiting the rich structure of the underlying private data