We conduct research on realizing and evaluating the safety of hardware capable of quickly executing key encapsulation and digital signature algorithms of quantum-resistant cryptography, even in the event of quantum computing realization.
We are researching the implementation of Spiking Neural Networks (SNNs) with high energy efficiency without compromising accuracy, and TFHE, which allows computation on secure ciphertext.
We implement hardware suitable for multi-party computation, allowing multiple parties to compute a function jointly while keeping their individual inputs secret.
Logic locking is a technology that protects the intellectual property and security of integrated circuits. We are conducting research on robust logic lock methods against quantum computing.
Advanced cryptographic algorithms, such as aggregate signatures and attribute-based encryption, usually involve extensive computations. Therefore, we believe high-performance accelerators are useful and are researching their design optimization.
We propose a method to estimate the area and computation time when using dedicated hardware, and perform security assessments and computational cost comparisons for actual cryptographic algorithms.
We are researching the implementation of high-level synthesis methods using Python descriptions to automatically generate scheduling for parallel processing that considers architecture and data dependencies suitable for algorithms, and to support higher levels of abstract design.