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Anubhab Baksi

Publications and source records attributed to Anubhab Baksi.

6 recordsLinked to original sources

Guess My Weight: Profiled Side-Channel Recovery of Floating-Point Neural-Network Weights

Neural-network parameters deployed on embedded devices may be exposed through physical side-channel leakage during inference. Existing side-channel attacks on floating-point neural-network parameters have often targeted reduced numerical precision, while recovering the complete IEEE-754 representation remains considerably more challenging because of the large and structured 32-bit candidate space. We present a profiled template attack for bit-exact recovery of an IEEE-754 single-precision neural-network weight from power measurements. The attack targets the floating-point multiplication between a known input and a first-layer weight. During profiling, multivariate Gaussian templates are learned from randomized network configurations using Hamming-weight classes of the multiplication result, while the remaining network parameters act as nuisance variables. To efficiently search the structured 32-bit floating-point candidate space, we use a hierarchical coarse-to-fine-to-exact procedure that progressively increases both the numerical and leakage-model resolution. Experiments on a ChipWhisperer-Lite with an Arm Cortex-M4 demonstrate recovery of the exact float32 representation of the target weight. In the evaluated setting, the attack reaches a bit-exact success rate of 99% with 171 traces and 100% from 263 traces onward. These results demonstrate that profiling can enable practical full-precision extraction of floating-point neural-network parameters from physical leakage.

cs.CR↗

Quantum Arithmetic Circuits in Public-Key Cryptography

Quantum computing has advanced rapidly in recent decades, driven by developments across the technology stack, including quantum error-correcting codes and efficient quantum algorithms. Among these, quantum arithmetic circuits serve as fundamental building blocks for various promising algorithms. Despite their crucial role, the design of quantum arithmetic circuits faces challenges arising from the no-cloning theorem, qubit limitations, and circuit depth constraints, which significantly impact the efficiency of large-scale quantum computing. We provide an overview of quantum arithmetic circuits in the context of public-key cryptanalysis, with particular emphasis on optimization strategies such as measurement-based uncomputation and conditionally clean ancilla. We review state-of-the-art designs for essential arithmetic operations in public-key cryptanalysis such as addition, multiplication, and modular exponentiation. We also present an overview of the techniques used for fault-tolerant runtime and resource estimation in quantum cryptanalysis. In brief, this chapter emphasizes strategies for designing resource-efficient quantum arithmetic circuits, providing a basis for realistic evaluations of quantum cryptanalytic capabilities.

quant-ph↗

On Exact Space-Depth Trade-Offs in Multi-Controlled Toffoli Decomposition

In this paper, we consider the optimized implementation of Multi Controlled Toffoli (MCT) using the Clifford $+$ T gate sets. While there are several recent works in this direction, here we explicitly quantify the trade-off (with concrete formulae) between the Toffoli depth (this means the depth using the classical 2-controlled Toffoli) of the $n$-controlled Toffoli (hereform we will tell $n$-MCT) and the number of clean ancilla qubits. Additionally, we achieve a reduced Toffoli depth (and consequently, T-depth), which is an extension of the technique introduced by Khattar et al. (2024). In terms of a negative result, we first show that using such conditionally clean ancilla techniques, Toffoli depth can never achieve exactly $\ceil{\log_2 n}$, though it remains of the same order. This highlights the limitation of the techniques exploiting conditionally clean ancilla [Nie et al., 2024, Khattar et al., 2024]. Then we prove that, in a more general setup, the T-Depth in the Clifford + T decomposition, via Toffoli gates, is lower bounded by $\ceil{\log_2 n}$, and this bound is achieved following the complete binary tree structure. Since the ($2$-controlled) Toffoli gate can further be decomposed using Clifford $+$ T, various methodologies are explored too in this regard for trade-off related implications.

quant-ph↗

Security and Privacy Issues for Urban Smart Traffic Infrastructure

In recent times, the research works relating to smart traffic infrastructure have gained serious attention. As a result, research has been carried out in multiple directions to ensure that such infrastructure can improve upon our existing (mostly) human-controlled traffic infrastructure, without violating the safety margins. For this reason, cyber security issues of such infrastructure are of paramount interest. Keeping this in mind, we conduct a review of existing models, their vulnerabilities and how such vulnerabilities can be handled. Our work covers a vast area from the domain of security, starting from the theoretical notions of cryptography to the real-life adaptation of them. At the same time, we also consider the security issues that may arise due to the usage of artificial intelligence/machine learning in the infrastructure. We believe that our work will help future researchers to gain a comprehensive yet concise look at cyber security for smart traffic infrastructure.

cs.CR↗

A Higher Radix Architecture for Quantum Carry-lookahead Adder

In this paper, we propose an efficient quantum carry-lookahead adder based on the higher radix structure. For the addition of two $n$-bit numbers, our adder uses $O(n)-O(\frac{n}{r})$ qubits and $O(n)+O(\frac{n}{r})$ T gates to get the correct answer in T-depth $O(r)+O(\log{\frac{n}{r}})$, where $r$ is the radix. Quantum carry-lookahead adder has already attracted some attention because of its low T-depth. Our work further reduces the overall cost by introducing a higher radix layer. By analyzing the performance in T-depth, T-count, and qubit count, it is shown that the proposed adder is superior to existing quantum carry-lookahead adders. Even compared to the Draper out-of-place adder which is very compact and efficient, our adder is still better in terms of T-count.

quant-ph↗

Reversible Logic Circuit Complexity Analysis via Functional Decomposition

Reversible computation is gaining increasing relevance in the context of several post-CMOS technologies, the most prominent of those being Quantum computing. One of the key theoretical problem pertaining to reversible logic synthesis is the upper bound of the gate count. Compared to the known bounds, the results obtained by optimal synthesis methods are significantly less. In this paper, we connect this problem with the multiplicative complexity analysis of classical Boolean functions. We explore the possibility of relaxing the ancilla and if that approach makes the upper bound tighter. Our results are negative. The ancilla-free synthesis methods by using transformations and by starting from an Exclusive Sum-of-Product (ESOP) formulation remain, theoretically, the synthesis methods for achieving least gate count for the cases where the number of variables $n$ is $< 8$ and otherwise, respectively.

cs.ET↗