TurboSHAKE

In a recent presentation, we promoted the use of 12-round instances of Keccak, collectively called “TurboSHAKE”, in post-quantum cryptographic schemes, but without defining them further. The goal of this note is to fill this gap: The definition of the TurboSHAKE family simply consists in exposing and generalizing the primitive already defined inside KangarooTwelve

ERINYES: A CONTINUOUS AUTHENTICATION PROTOCOL

The need for user authentication in the digital domain is paramount as the number of digital interactions that involve sensitive data continues to increase. Advances in the fields of machine learning (ML) and biometric encryption have enabled the development of technologies that can provide fully remote continuous user authentication services. This thesis introduces the Erinyes protocol. The protocol leverages state of the art ML models, biometric encryption of asymmetric cryptographic keys, and a trusted third-party client-server architecture to continuously authenticate users through their behavioral biometrics. The goals in developing the protocol were to identify if biometric encryption using keystroke timing and mouse cursor movement sequences were feasible and to measure the performance of a continuous authentication system that utilizes biometric encryption. Our research found that with a combined keystroke and mouse cursor movement dataset, the biometric encryption system can perform with a 0.93% False Acceptance Rate (FAR), 0.00% False Reject Rate (FRR), and 99.07% accuracy. Using a similar dataset, the overall integrated system averaged 0% FAR, 2% FRR and 98% accuracy across multiple users. These metrics demonstrate that the Erinyes protocol can achieve continuous user authentication with minimal user intrusion.Lieutenant, United States NavyLieutenant, United States NavyApproved for public release. Distribution is unlimited

SALSA VERDE: a machine learning attack on Learning With Errors with sparse small secrets

Learning with Errors (LWE) is a hard math problem used in post-quantum cryptography. Homomorphic Encryption (HE) schemes rely on the hardness of the LWE problem for their security, and two LWE-based cryptosystems were recently standardized by NIST for digital signatures and key exchange (KEM). Thus, it is critical to continue assessing the security of LWE and specific parameter choices. For example, HE uses secrets with small entries, and the HE community has considered standardizing small sparse secrets to improve efficiency and functionality. However, prior work, SALSA and PICANTE, showed that ML attacks can recover sparse binary secrets. Building on these, we propose VERDE, an improved ML attack that can recover sparse binary, ternary, and narrow Gaussian secrets. Using improved preprocessing and secret recovery techniques, VERDE can attack LWE with larger dimensions ($n=512$) and smaller moduli ($\log_2 q=12$ for $n=256$), using less time and power. We propose novel architectures for scaling. Finally, we develop a theory that explains the success of ML LWE attacks.Comment: 18 pages, accepted to NeurIPS 202

SALSA: Attacking Lattice Cryptography with Transformers

Currently deployed public-key cryptosystems will be vulnerable to attacks by full- scale quantum computers. Consequently, quantum resistant cryptosystems are in high demand, and lattice-based cryptosystems, based on a hard problem known as Learning With Errors (LWE), have emerged as strong contenders for standardization. In this work, we train transformers to perform modular arithmetic and combine half-trained models with statistical cryptanalysis techniques to propose SALSA: a machine learning attack on LWE-based cryptographic schemes. SALSA can fully recover secrets for small-to-mid size LWE instances with sparse binary secrets, and may scale to attack real-world LWE-based cryptosystems

Physical Unclonability Framework for the Internet of Things

Ph. D. ThesisThe rise of the Internet of Things (IoT) creates a tendency to construct unified architectures with a great number of edge nodes and inherent security risks due to centralisation. At the same time, security and privacy defenders advocate for decentralised solutions which divide the control and the responsibility among the entirety of the network nodes. However, spreading secrets among several parties also expands the attack surface. This conflict is in part due to the difficulty in differentiating between instances of the same hardware, which leads to treating physically distinct devices as identical. Harnessing the uniqueness of each connected device and injecting it into security protocols can provide solutions to several common issues of the IoT. Secrets can be generated directly from this uniqueness without the need to manually embed them into devices, reducing both the risk of exposure and the cost of managing great numbers of devices. Uniqueness can then lead to the primitive of unclonability. Unclonability refers to ensuring the difficulty of producing an exact duplicate of an entity via observing and measuring the entity’s features and behaviour. Unclonability has been realised on a physical level via the use of Physical Unclonable Functions (PUFs). PUFs are constructions that extract the inherent unclonable features of objects and compound them into a usable form, often that of binary data. PUFs are also exceptionally useful in IoT applications since they are low-cost, easy to integrate into existing designs, and have the potential to replace expensive cryptographic operations. Thus, a great number of solutions have been developed to integrate PUFs in various security scenarios. However, methods to expand unclonability into a complete security framework have not been thoroughly studied. In this work, the foundations are set for the development of such a framework through the formulation of an unclonability stack, in the paradigm of the OSI reference model. The stack comprises layers propagating the primitive from the unclonable PUF ICs, to devices, network links and eventually unclonable systems. Those layers are introduced, and work towards the design of protocols and methods for several of the layers is presented. A collection of protocols based on one or more unclonable tokens or authority devices is proposed, to enable the secure introduction of network nodes into groups or neighbourhoods. The role of the authority devices is that of a consolidated, observable root of ownership, whose physical state can be verified. After their introduction, nodes are able to identify and interact with their peers, exchange keys and form relationships, without the need of continued interaction with the authority device. Building on this introduction scheme, methods for establishing and maintaining unclonable links between pairs of nodes are introduced. These pairwise links are essential for the construction of relationships among multiple network nodes, in a variety of topologies. Those topologies and the resulting relationships are formulated and discussed. While the framework does not depend on specific PUF hardware, SRAM PUFs are chosen as a case study since they are commonly used and based on components that are already present in the majority of IoT devices. In the context of SRAM PUFs and with a view to the proposed framework, practical issues affecting the adoption of PUFs in security protocols are discussed. Methods of improving the capabilities of SRAM PUFs are also proposed, based on experimental data.School of Engineering Newcastle Universit

Algorithms for Solving Linear and Polynomial Systems of Equations over Finite Fields with Applications to Cryptanalysis

This dissertation contains algorithms for solving linear and polynomial systems of equations over GF(2). The objective is to provide fast and exact tools for algebraic cryptanalysis and other applications. Accordingly, it is divided into two parts. The first part deals with polynomial systems. Chapter 2 contains a successful cryptanalysis of Keeloq, the block cipher used in nearly all luxury automobiles. The attack is more than 16,000 times faster than brute force, but queries 0.62 × 2^32 plaintexts. The polynomial systems of equations arising from that cryptanalysis were solved via SAT-solvers. Therefore, Chapter 3 introduces a new method of solving polynomial systems of equations by converting them into CNF-SAT problems and using a SAT-solver. Finally, Chapter 4 contains a discussion on how SAT-solvers work internally. The second part deals with linear systems over GF(2), and other small fields (and rings). These occur in cryptanalysis when using the XL algorithm, which converts polynomial systems into larger linear systems. We introduce a new complexity model and data structures for GF(2)-matrix operations. This is discussed in Appendix B but applies to all of Part II. Chapter 5 contains an analysis of "the Method of Four Russians" for multiplication and a variant for matrix inversion, which is log n faster than Gaussian Elimination, and can be combined with Strassen-like algorithms. Chapter 6 contains an algorithm for accelerating matrix multiplication over small finite fields. It is feasible but the memory cost is so high that it is mostly of theoretical interest. Appendix A contains some discussion of GF(2)-linear algebra and how it differs from linear algebra in R and C. Appendix C discusses algorithms faster than Strassen's algorithm, and contains proofs that matrix multiplication, matrix squaring, triangular matrix inversion, LUP-factorization, general matrix in- version and the taking of determinants, are equicomplex. These proofs are already known, but are here gathered into one place in the same notation