Biblio

Machine Learning as a Service (MLaaS) is becoming a popular practice where Service Consumers, e.g., end-users, send their data to a ML Service and receive the prediction outputs. However, the emerging usage of MLaaS has raised severe privacy concerns about users' proprietary data. PrivacyPreserving Machine Learning (PPML) techniques aim to incorporate cryptographic primitives such as Homomorphic Encryption (HE) and Multi-Party Computation (MPC) into ML services to address privacy concerns from a technology standpoint. Existing PPML solutions have not been widely adopted in practice due to their assumed high overhead and integration difficulty within various ML front-end frameworks as well as hardware backends. In this work, we propose PlaidML-HE, the first end-toend HE compiler for PPML inference. Leveraging the capability of Domain-Specific Languages, PlaidML-HE enables automated generation of HE kernels across diverse types of devices. We evaluate the performance of PlaidML-HE on different ML kernels and demonstrate that PlaidML-HE greatly reduces the overhead of the HE primitive compared to the existing implementations.

The impending realization of scalable quantum computers will have a significant impact on today's security infrastructure. With the advent of powerful quantum computers public key cryptographic schemes will become vulnerable to Shor's quantum algorithm, undermining the security current communications systems. Post-quantum (or quantum-resistant) cryptography is an active research area, endeavoring to develop novel and quantum resistant public key cryptography. Amongst the various classes of quantum-resistant cryptography schemes, lattice-based cryptography is emerging as one of the most viable options. Its efficient implementation on software and on commodity hardware has already been shown to compete and even excel the performance of current classical security public-key schemes. This work discusses the next step in terms of their practical deployment, i.e., addressing the physical security of lattice-based cryptographic implementations. We survey the state-of-the-art in terms of side channel attacks (SCA), both invasive and passive attacks, and proposed countermeasures. Although the weaknesses exposed have led to countermeasures for these schemes, the cost, practicality and effectiveness of these on multiple implementation platforms, however, remains under-studied.

Funded under the European Union's Horizon 2020 research and innovation programme, SAFEcrypto will provide a new generation of practical, robust and physically secure post-quantum cryptographic solutions that ensure long-term security for future ICT systems, services and applications. The project will focus on the remarkably versatile field of Lattice-based cryptography as the source of computational hardness, and will deliver optimised public key security primitives for digital signatures and authentication, as well identity based encryption (IBE) and attribute based encryption (ABE). This will involve algorithmic and design optimisations, and implementations of lattice-based cryptographic schemes addressing cost, energy consumption, performance and physical robustness. As the National Institute of Standards and Technology (NIST) prepares for the transition to a post-quantum cryptographic suite B, urging organisations that build systems and infrastructures that require long-term security to consider this transition in architectural designs; the SAFEcrypto project will provide Proof-of-concept demonstrators of schemes for three practical real-world case studies with long-term security requirements, in the application areas of satellite communications, network security and cloud. The goal is to affirm Lattice-based cryptography as an effective replacement for traditional number-theoretic public-key cryptography, by demonstrating that it can address the needs of resource-constrained embedded applications, such as mobile and battery-operated devices, and of real-time high performance applications for cloud and network management infrastructures.

Fabrication process introduces some inherent variability to the attributes of transistors (in particular length, widths, oxide thickness). As a result, every chip is physically unique. Physical uniqueness of microelectronics components can be used for multiple security applications. Physically Unclonable Functions (PUFs) are built to extract the physical uniqueness of microelectronics components and make it usable for secure applications. However, the microelectronics components used by PUFs designs suffer from external, environmental variations that impact the PUF behavior. Variations of temperature gradients during manufacturing can bias the PUF responses. Variations of temperature or thermal noise during PUF operation change the behavior of the circuit, and can introduce errors in PUF responses. Detailed knowledge of the behavior of PUFs operating over various environmental factors is needed to reliably extract and demonstrate uniqueness of the chips. In this work, we present a detailed and exhaustive analysis of the behavior of two PUF designs, a ring oscillator PUF and a timing path violation PUF. We have implemented both PUFs using FPGA fabricated by Xilinx, and analyzed their behavior while varying temperature and supply voltage. Our experiments quantify the robustness of each design, demonstrate their sensitivity to temperature and show the impact which supply voltage has on the uniqueness of the analyzed PUFs.