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* Abstract is not available.

 

Logic encryption is an IC protection technique which inserts extra logic and key inputs to hide a circuit's functionality. An encrypted circuit needs to be activated with a secret key for being functional. Recently, a tree-based encryption method was proposed to mitigate a powerful SAT-based attack method. Although the encryption method is effective, it could be vulnerable to a removal-based attack method. Thus, in this paper, we enhance the encryption method to resist the two attack methods simultaneously. We introduce a new type of tree encryption to obfuscate attackers, which is structurally identical to the original one but has different functionality. The experimental results show that the proposed method is effective for encrypting a set of benchmarks from IWLS. Additionally, compared to the state-of-the-art logic encryption methods, the proposed method provides better security for most benchmarks.

 

Uniform sampling is an important method in statistics and has various applications in model counting, system verification, algorithm design, among others. Symbolic sampling in a Boolean space is a recently proposed technique that combines sampling and symbolic representation for effective Boolean reasoning. Under the framework of symbolic sampling, we propose a method to construct compact XOR circuits achieving uniform sampling in a given Boolean space. The method is further extended to biased sampling within a focused subspace of interest. Experimental results show the effectiveness of compact sampling circuit generation and its potential to facilitate Boolean reasoning.

 

Quantum computing is greatly advanced in recent years and is expected to transform the computation paradigm in the near future. Quantum circuit simulation plays a key role in the toolchain for the development of quantum hardware and software systems. However, due to the enormous Hilbert space of quantum states, simulating quantum circuits with classical computers is extremely challenging despite notable efforts have been made. In this paper, we enhance quantum circuit simulation in two dimensions: accuracy and scalability. The former is achieved by using an algebraic representation of complex numbers; the latter is achieved by bit-slicing the number representation and replacing matrix-vector multiplication with symbolic Boolean function manipulation. Experimental results demonstrate that our method can be superior to the state-of-the-art for various quantum circuits and can simulate certain benchmark families with up to tens of thousands of qubits.