Papers for

quantum security engineers

Papers whose findings have a practical use for this group, as judged from the abstract. Open a paper to read what it means in practice.

Quantum machine learning detects hidden attacks in military key distribution

Quantum Machine Learning Protection of Military Quantum Key Distribution Against Cryptographically Camouflaged Attacks

Abstract: Quantum key distribution proves its protocol secure and says nothing about the hardware beneath it, so military and government operators fielding it for command-and-control keys monitor the channel for implementation attacks, and that monitoring has a blind spot. An adversary with a kleptographic foothold in the generator of a public per-block value \(x=g^v \pmod p\) can hide attacked blocks in honest noise, gating them on a predicate of its discrete logarithm, making detection a discrete logarithm problem that defeats every efficient classical monitor yet yields to a quantum kernel recovering \(v\) through Shor's algorithm. I formalise these cryptographically camouflaged attacks, reduce their hardness to an established learning separation, prove a single-frequency fidelity kernel cannot represent an interval predicate, and test them on Ghillie, a decoy-state BB84 simulator with a positive key rate to 142 km. From 10- to 14-bit groups over two seeds, a classical monitor reads 0.458 to 0.516 on camouflaged attacks while the quantum kernel reads 1.000, and both catch overt attacks above 0.99. Finite-precision recovery under depolarising noise and a hardened predicate lower the quantum result to 0.916 through 0.983 with the classical monitor at chance, and a feasibility probe on IBM Heron processors tracks the exact kernel within 0.034. A defender can therefore discard precisely the compromised key material, although the advantage is asymptotic, awaits fault tolerance, and holds only when the feature map matches the adversary's predicate, since a low-frequency map reads 0.545 on a residue pattern and 0.982 once aligned.

Sat 3 OctCryptography and SecurityMachine Learning
The gist
Military systems use quantum key distribution to keep communications secure, but the hardware can be secretly attacked in ways that hide in normal noise, making classical detection methods fail. The authors describe a special type of attack and show that quantum machine learning using a quantum computer can uncover the hidden attack by recovering secret information faster than classical methods. Their tests with simulations show quantum methods can detect attacks almost perfectly, while classical ones perform no better than guessing. This approach can allow defenders to discard only the compromised information, improving security in critical communications.
Open → 2610.04543v1

Quantum cryptography resists large space preprocessing attacks better

Time-space lower bounds for breaking quantum cryptography

Abstract: We prove near-optimal time-space lower bounds for breaking quantum cryptography in the random oracle model. Specifically, we show that a $T$-query adversary with $S$ qubits of non-uniform advice can recover a random key $k$ from the $n$-qubit binary phase state $|ψ_k\rangle \propto \sum_{x} R(k,x) |x\rangle$ with probability at most $O(\frac{T^2 + \sqrt{ST}}{N})$ for $N=2^n$. In contrast, the best known bound for post-quantum one-way functions is $O(\frac{T^2 + ST}{N})$, with a trivial attack at $S = N$. This demonstrates a new advantage of quantum cryptography over classical cryptography: $n$ qubits of communication suffice for security against preprocessing attacks with space up to $N^2$ rather than $N$. Our methodology is simple: express the optimal preprocessing attack as the operator norm of a random matrix, and bound this value in expectation over the random oracle via the trace-moment method. These trace moments have a natural interpretation using compressed oracles [Zhandry, Crypto 2019], which we then analyze. This can be viewed as a simplification and generalization of the approach of Liu [Eurocrypt 2023] for proving time-space tradeoffs for breaking post-quantum cryptography. We also prove the following results: (1) We tighten Liu's analysis of post-quantum PRGs in QROM, achieving a distinguishing advantage bound of $O(\frac{T^2}N + \sqrt{\frac{ST}N})$. (2) For unitary synthesis, we extend the one-query lower bound of Lombardi-Ma-Wright [STOC 2024] to hold against adversaries that can make one arbitrary function query along with polynomially many (adaptive) queries to the random oracle, either before or after the function query. This also interprets the original LMW24 result in terms of compressed oracles. (3) Finally, we prove a tight $O(\frac{\sqrt{S}}N)$ bound for the pseudorandomness of random binary phase states against space $S$ distinguishers.

Thu 1 OctComputational ComplexityCryptography and Security
The gist
Breaking quantum cryptography usually requires guessing secret keys, but this paper shows that attackers with limited time and quantum memory can't easily do it. The authors prove that quantum systems need much more memory to break keys than classical systems do, offering a strong security advantage. They use mathematical techniques involving random matrices and oracles to reach these conclusions. Their work also improves understanding of the security limits of related quantum cryptographic tools.
Open → 2610.02101v1

Quantum blind-unforgeability proves stronger than plus-one unforgeability

Blind Unforgeability implies Plus-One Unforgeability

Abstract: We prove that quantum blind-unforgeability implies quantum plus-one unforgeability, settling an open question in the literature. Since plus-one unforgeability is known not to imply blind-unforgeability, our result establishes that blind-unforgeability is \emph{strictly stronger} than plus-one unforgeability in the quantum setting. The implication is proven using a new \emph{smoothing} technique that coherently rescales the query histories of a quantum-query algorithm in a black-box manner. This enables us to transform any successful plus-one attacker into a blind-unforgeability attacker with only inverse-polynomial loss. Our proof represents a conceptual shift from merely extracting a useful query history as in earlier attempts, which we show inevitably fails in general, to first coherently reshaping how query histories interfere.

Wed 30 SeptCryptography and Security
The gist
Some types of security protections for quantum cryptography are stronger than others, but it wasn't clear exactly how they relate. The authors showed that if a system is secure against a type of attack called quantum blind-unforgeability, it also protects against a related, weaker attack called plus-one unforgeability. They developed a new technique that reshapes how queries in the quantum algorithm interact, which helped prove this relationship. This means one security notion is strictly better, settling a question that was open before.
Open → 2610.00517v1

Quantum function limits set by computing power and memory use

Computational Bounds for $f$-Routing

Abstract: The $f$-routing protocol is a leading candidate for quantum position verification (Kent, Munro, and Spiller, 2011), but security guarantees for explicit functions remain limited. We prove unconditional resource lower bounds for uniform attackers; our new techniques bypass communication-complexity bounds central to previous works, which are inherently at most linear in the input length. We show that, for input length $n$ and sufficiently small constant $ε>0$, a uniformly generated strategy using $q$ qubits and having description length $\mathrm{poly}(q)$, with success probability at least $1-ε$ on every input, implies the following computational bounds on $f$: 1. If the strategies are arbitrary quantum channels, then $f\in\mathrm{QSZK}(\mathrm{poly}(nq))$, where $\mathrm{QSZK}(T)$ is the class of languages having quantum statistical zero knowledge proofs in which the verifier runs in time $T$ (and the simulator in time $\mathrm{poly}(T)$). 2. If the strategies are explicit Pauli-sparse unitaries on $q$ qubits that have at most $s$ nonzero Pauli coefficients, then $f\in\mathrm{DTIME}(\mathrm{poly}(nqs))$. 3. If the strategies are Clifford+T circuits using at most $t$ magic gates, then $f\in\mathrm{DTIME}(\mathrm{poly}(nq2^t))$. Time and space hierarchies then yield explicit functions secure against polynomial and even quasipolynomial qubits $q$ under our computational restrictions. These bounds exceed the $q\le\log n$ bound of Bluhm, Christandl, and Speelman (2022) for inner product function $f=\mathrm{IP}$, at the cost of restricting adversarial computation and increasing honest evaluation complexity.

Wed 30 SeptComputational Complexity
The gist
This paper looks at a special kind of coding task called f-routing used in quantum position verification, which checks where things are based on their signals. The authors show that if someone tries to cheat this system using limited quantum computing resources, the function they can mimic must belong to certain classes of problems solvable within specific time or space boundaries. These results put clear mathematical limits on how powerful a quantum attacker’s strategy can be under different computational restrictions. This could help in designing more secure quantum location verification methods by knowing what kinds of attacks are impossible given computational limits.
Open → 2609.40278v1