Candidate: Nusa Zidaric
Title: Automated Design Space Exploration and Datapath Synthesis for Finite Field Arithmetic with Applications in Lightweight Cryptography
Date: May 11, 2020
Time: 8:00 AM
Place: REMOTE PARTICIPATION
Supervisor(s): Aagaard, Mark - Gong, Guang
Abstract:
Today, emerging technologies are reaching astronomical proportions. For example, the Internet of Things has numerous applications and consists of countless different devices using different technologies with different capabilities. But the one invariant is their connectivity. Consequently, secure communications, and cryptographic hardware as a means of providing them, are faced with new challenges. Cryptographic algorithms intended for hardware implementations must be designed with a good trade-off between implementation efficiency and sufficient cryptographic strength. The implementations must follow good practices of hardware design while considering numerous design choices. Finite fields are widely used in cryptography. Examples of algorithm design choices related to finite field arithmetic are the field size, which arithmetic operations to use, how to represent the field elements, etc. As there are many parameters to be considered and analyzed, an automation framework is needed.
This thesis proposes a framework for automated design, implementation and verification of finite field arithmetic hardware. The underlying motif throughout this work is “math meets hardware”. The automation framework is designed to bring the awareness of underlying mathematical structures to the hardware design flow. It is implemented in GAP, an open source computer algebra system that can work with finite fields and has symbolic computation capabilities. The framework is roughly divided into two phases, the architectural decisions and the automated design generation. The architectural decisions phase supports parameter search and produces a list of candidates. The automated design generation phase is invoked for each candidate, and the generated VHDL files are passed on to conventional synthesis tools. The candidates and their implementation results form the design space, and the framework allows rapid design space exploration in a systematic way. In this thesis, design space exploration is focused on finite field arithmetic.
Three distinctive features of the proposed framework are the structure of finite fields, tower field support, and on-the-fly submodule generation. Each finite field used in the design is represented as both a field and its corresponding vector space. It is easy for a designer to switch between fields and vector spaces, but strict distinction of the two is necessary for hierarchical designs. When an expression is defined over an extension field, the top-level module contains element signals and submodules for arithmetic operations on those signals. The submodules are generated with corresponding vector signals and the arithmetic operations are now performed on the coordinates. For tower fields, the submodules are generated for the subfield operations, and the design is generated in a top-down fashion. The binding of expressions to the appropriate finite fields or vector spaces and a set of customized methods allow the on-the-fly generation of expressions for implementation of arithmetic operations, and hence submodule generation.
In the light of NIST Lightweight Cryptography Project (LWC), this work focuses mainly on small finite fields. The thesis illustrates the impact of hardware implementation results during the design process of WAGE, a Round 2 candidate in the NIST LWC standardization competition. WAGE is a hardware oriented authenticated encryption scheme. The parameter selection for WAGE was aimed at balancing the security and hardware implementation area, using hardware implementation results for many design decisions, for example field size, representation of field elements, etc. In the proposed framework, the components of WAGE are used as an example to illustrate different automation flows and demonstrate the design space exploration on a real-world algorithm.