We introduce a compiler that automatically inserts software countermeasures to protect cryptographic algorithms against power-based side-channel attacks. The compiler first estimates which instruction instances leak the most information through side-channels. This information is obtained either by dynamic analysis, evaluating an information theoretic metric over the power traces acquired during the execution of the input program, or by static analysis. As information leakage implies a loss of security, the compiler then identifies (groups of) instruction instances to protect with a software countermeasure such as random precharging or Boolean masking. As software protection incurs significant overhead in terms of cryptosystem runtime and memory usage, the compiler protects the minimum number of instruction instances to achieve a desired level of security. The compiler is evaluated on two block ciphers, AES and Clefia; our experiments demonstrate that the compiler can automatically identify and protect the most important instruction instances. To date, these software countermeasures have been inserted manually by security experts, who are not necessarily the main cryptosystem developers. Our compiler offers significant productivity gains for cryptosystem developers who wish to protect their implementations from side-channel attacks.

This paper introduces a generic and automated methodology to protect hardware designs from side-channel attacks in a manner that is fully compatible with commercial standard cell design flows. The paper describes a tool that artificially adds jitter to the clocks of the sequential elements of a cryptographic unit, which increases the non-determinism of signal timing, thereby making the physical device more difficult to attack. Timing constraints are then specified to commercial EDA tools, which restore the circuit functionality and efficiency while preserving the introduced randomness. The protection scheme is applied to an AES-128 hardware implementation that is synthesized using both ASIC and FPGA design flows.

Embedded cryptographic systems, such as smart cards, require secure implementations that are robust to a variety of low-level attacks. Side-Channel Attacks (SCA) exploit the information such as power consumption, electromagnetic radiation and acoustic leaking through the device to uncover the secret information. Attackers can mount successful attacks with very modest resources in a short time period. Therefore, many methods have been proposed to increase the security against SCA. Randomizing the execution order of the instructions that are independent, i.e., random shuffling , is one of the most popular among them. Implementing instruction shuffling in software is either implementation specific or has a significant performance or code size overhead. To overcome these problems, we propose in this work a generic custom hardware unit to implement random instruction shuffling as an extension to existing processors. The unit operates between the CPU and the instruction cache (or memory, if no cache exists), without any modification to these components. Both true and pseudo random number generators are used to dynamically and locally provide the shuffling sequence. The unit is mainly designed for in-order processors, since the embedded devices subject to these kind of attacks use simple in-order processors. More advanced processors (e.g., superscalar, VLIW or EPIC processors) are already more resistant to these attacks because of their built-in ILP and wide word size. Our experiments on two different soft in-order processor cores, i.e., OpenRISC and MicroBlaze, implemented on FPGA show that the proposed unit could increase the security drastically with very modest resource overhead. With around 2% area, 1.5% power and no performance overhead, the shuffler increases the effort to mount a successful power analysis attack on AES software implementation over 360 times.

In cryptography, side channel attacks, such as power analysis, attempt to uncover secret information from the physical implementation of cryptosystems rather than exploiting weaknesses in the cryptographic algorithms themselves. The design and implementation of physically secure cryptosystems is a challenge for both hardware and software designers. Measuring and evaluating the security of a system is manual and empirical, which is costly and time consuming; this work demonstrates that it is possible to automate these processes. We introduce a systematic methodology for automatic application of software countermeasures and demonstrate its effectiveness on an AES software implementation running on an 8-bit AVR microcontroller. The framework identifies the most vulnerable instructions of the implementation to power analysis attacks, and then transforms the software using a chosen countermeasure to protect the vulnerable instructions. Lastly, it evaluates the security of the system using an information-theoretic metric and a direct attack.