The advent of Grover’s algorithm presents a significant threat to classical block cipher security,spurring research into post-quantum secure cipher design.This study engineers quantum circuit implementations for thre...The advent of Grover’s algorithm presents a significant threat to classical block cipher security,spurring research into post-quantum secure cipher design.This study engineers quantum circuit implementations for three versions of the Ballet family block ciphers.The Ballet‑p/k includes a modular-addition operation uncommon in lightweight block ciphers.Quantum ripple-carry adder is implemented for both“32+32”and“64+64”scale to support this operation.Subsequently,qubits,quantum gates count,and quantum circuit depth of three versions of Ballet algorithm are systematically evaluated under quantum computing model,and key recovery attack circuits are constructed based on Grover’s algorithm against each version.The comprehensive analysis shows:Ballet-128/128 fails to NIST Level 1 security,while when the resource accounting is restricted to the Clifford gates and T gates set for the Ballet-128/256 and Ballet-256/256 quantum circuits,the design attains Level 3.展开更多
The current Grover quantum searching algorithm cannot identify the difference in importance of the search targets when it is applied to an unsorted quantum database, and the probability for each search target is equal...The current Grover quantum searching algorithm cannot identify the difference in importance of the search targets when it is applied to an unsorted quantum database, and the probability for each search target is equal. To solve this problem, a Grover searching algorithm based on weighted targets is proposed. First, each target is endowed a weight coefficient according to its importance. Applying these different weight coefficients, the targets are represented as quantum superposition states. Second, the novel Grover searching algorithm based on the quantum superposition of the weighted targets is constructed. Using this algorithm, the probability of getting each target can be approximated to the corresponding weight coefficient, which shows the flexibility of this algorithm. Finally, the validity of the algorithm is proved by a simple searching example.展开更多
基金State Key Lab of Processors,Institute of Computing Technology,Chinese Academy of Sciences(CLQ202516)the Fundamental Research Funds for the Central Universities of China(3282025047,3282024051,3282024009)。
文摘The advent of Grover’s algorithm presents a significant threat to classical block cipher security,spurring research into post-quantum secure cipher design.This study engineers quantum circuit implementations for three versions of the Ballet family block ciphers.The Ballet‑p/k includes a modular-addition operation uncommon in lightweight block ciphers.Quantum ripple-carry adder is implemented for both“32+32”and“64+64”scale to support this operation.Subsequently,qubits,quantum gates count,and quantum circuit depth of three versions of Ballet algorithm are systematically evaluated under quantum computing model,and key recovery attack circuits are constructed based on Grover’s algorithm against each version.The comprehensive analysis shows:Ballet-128/128 fails to NIST Level 1 security,while when the resource accounting is restricted to the Clifford gates and T gates set for the Ballet-128/256 and Ballet-256/256 quantum circuits,the design attains Level 3.
基金the National Natural Science Foundation of China (60773065).
文摘The current Grover quantum searching algorithm cannot identify the difference in importance of the search targets when it is applied to an unsorted quantum database, and the probability for each search target is equal. To solve this problem, a Grover searching algorithm based on weighted targets is proposed. First, each target is endowed a weight coefficient according to its importance. Applying these different weight coefficients, the targets are represented as quantum superposition states. Second, the novel Grover searching algorithm based on the quantum superposition of the weighted targets is constructed. Using this algorithm, the probability of getting each target can be approximated to the corresponding weight coefficient, which shows the flexibility of this algorithm. Finally, the validity of the algorithm is proved by a simple searching example.
