arXiv subjects

Roberto Ferrara

Publications and source records attributed to Roberto Ferrara.

At least 19 recordsLinked to original sources

arXiv2025

Identification Under the Semantic Effective Secrecy Constraint

The problem of identification over a discrete memoryless wiretap channel is examined under the criterion of semantic effective secrecy. This secrecy criterion guarantees both the requirement of semantic secrecy and of stealthy communication. Additionally, we introduce the related problem of combining approximation-of-output statistics and transmission. We derive a capacity theorem for approximation-of-output statistics transmission codes. For a general model, we present lower and upper bounds on the capacity, showing that these bounds are tight for more capable wiretap channels. We also provide illustrative examples for more capable wiretap channels, along with examples of wiretap channel classes where a gap exists between the lower and upper bounds.

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arXiv2024

Optimal depth and a novel approach to variational quantum process tomography

In this work, we present two new methods for Variational Quantum Circuit (VQC) Process Tomography onto $n$ qubits systems: PT_VQC and U-VQSVD. Compared to the state of the art, PT_VQC halves in each run the required amount of qubits for process tomography and decreases the required state initializations from $4^{n}$ to just $2^{n}$, all while ensuring high-fidelity reconstruction of the targeted unitary channel $U$. It is worth noting that, for a fixed reconstruction accuracy, PT_VQC achieves faster convergence per iteration step compared to Quantum Deep Neural Network (QDNN) and tensor network schemes. The novel U-VQSVD algorithm utilizes variational singular value decomposition to extract eigenvectors (up to a global phase) and their associated eigenvalues from an unknown unitary representing a general channel. We assess the performance of U-VQSVD by executing an attack on a non-unitary channel Quantum Physical Unclonable Function (QPUF). U-VQSVD outperforms an uninformed impersonation attack (using randomly generated input states) by a factor of 2 to 5, depending on the qubit dimension. For the two presented methods, we propose a new approach to calculate the complexity of the displayed VQC, based on what we denote as optimal depth.

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arXiv2024

Existential Unforgeability in Quantum Authentication From Quantum Physical Unclonable Functions Based on Random von Neumann Measurement

Physical Unclonable Functions (PUFs) leverage inherent, non-clonable physical randomness to generate unique input-output pairs, serving as secure fingerprints for cryptographic protocols like authentication. Quantum PUFs (QPUFs) extend this concept by using quantum states as input-output pairs, offering advantages over classical PUFs, such as challenge reusability via public channels and eliminating the need for trusted parties due to the no-cloning theorem. Recent work introduced a generalized mathematical framework for QPUFs. It was shown that random unitary QPUFs cannot achieve existential unforgeability against Quantum Polynomial Time (QPT) adversaries. Security was possible only with additional uniform randomness. To avoid the cost of external randomness, we propose a novel measurement-based scheme. Here, the randomness naturally arises from quantum measurements. Additionally, we introduce a second model where the QPUF functions as a nonunitary quantum channel, which guarantees existential unforgeability. These are the first models in the literature to demonstrate a high level of provable security. Finally, we show that the Quantum Phase Estimation (QPE) protocol, applied to a Haar random unitary, serves as an approximate implementation of the second type of QPUF by approximating a von Neumann measurement on the unitary's eigenbasis.

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arXiv2023

Information-Theoretically Secret Reed-Muller Identification with Affine Designs

We consider the problem of information-theoretic secrecy in identification schemes rather than transmission schemes. In identification, large identities are encoded into small challenges sent with the sole goal of allowing at the receiver reliable verification of whether the challenge could have been generated by a (possibly different) identity of his choice. One of the reasons to consider identification is that it trades decoding for an exponentially larger rate, however this may come with such encoding complexity and latency that it can render this advantage unusable. Identification still bears one unique advantage over transmission in that practical implementation of information-theoretic secrecy becomes possible, even considering that the information-theoretic secrecy definition needed in identification is that of semantic secrecy. Here, we implement a family of encryption schemes, recently shown to achieve semantic-secrecy capacity, and apply it to a recently-studied family of identification codes, confirming that, indeed, adding secrecy to identification comes at essentially no cost. While this is still within the one-way communication scenario, it is a necessary step into implementing semantic secrecy with two-way communication, where the information-theoretic assumptions are more realistic.

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arXiv2023

A Review of the Applications of Quantum Machine Learning in Optical Communication Systems

In the context of optical signal processing, quantum and quantum-inspired machine learning algorithms have massive potential for deployment. One of the applications is in error correction protocols for the received noisy signals. In some scenarios, non-linear and unknown errors can lead to noise that bypasses linear error correction protocols that optical receivers generally implement. In those cases, machine learning techniques are used to recover the transmitted signal from the received signal through various estimation procedures. Since quantum machine learning algorithms promise advantage over classical algorithms, we expect that optical signal processing can benefit from these advantages. In this review, we survey several proposed quantum and quantum-inspired machine learning algorithms and their applicability with current technology to optical signal processing.

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arXiv2023

Testing of Hybrid Quantum-Classical K-Means for Nonlinear Noise Mitigation

Nearest-neighbour clustering is a powerful set of heuristic algorithms that find natural application in the decoding of signals transmitted using the M-Quadrature Amplitude Modulation (M-QAM) protocol. Lloyd et al. proposed a quantum version of the algorithm that promised an exponential speed-up. We analyse the performance of this algorithm by simulating the use of a hybrid quantum-classical implementation of it upon 16-QAM and experimental 64-QAM data. We then benchmark the implementation against the classical k-means clustering algorithm. The choice of quantum encoding of the classical data plays a significant role in the performance, as it would for the hybrid quantum-classical implementation of any quantum machine learning algorithm. In this work, we use the popular angle embedding method for data embedding and the swap test for overlap estimation. The algorithm is emulated in software using Qiskit and tested on simulated and real-world experimental data. The discrepancy in accuracy from the perspective of the induced metric of the angle embedding method is discussed, and a thorough analysis regarding the angle embedding method in the context of distance estimation is provided. We detail an experimental optic fibre setup as well, from which we collect 64-QAM data. This is the dataset upon which the algorithms are benchmarked. Finally, some promising current and future directions for further research are discussed.

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arXiv2023

Quantum and Quantum-Inspired Stereographic K Nearest-Neighbour Clustering

Nearest-neighbour clustering is a simple yet powerful machine learning algorithm that finds natural application in the decoding of signals in classical optical-fibre communication systems. Quantum k-means clustering promises a speed-up over the classical k-means algorithm; however, it has been shown to not currently provide this speed-up for decoding optical-fibre signals due to the embedding of classical data, which introduces inaccuracies and slowdowns. Although still not achieving an exponential speed-up for NISQ implementations, this work proposes the generalised inverse stereographic projection as an improved embedding into the Bloch sphere for quantum distance estimation in k-nearest-neighbour clustering, which allows us to get closer to the classical performance. We also use the generalised inverse stereographic projection to develop an analogous classical clustering algorithm and benchmark its accuracy, runtime and convergence for decoding real-world experimental optical-fibre communication data. This proposed 'quantum-inspired' algorithm provides an improvement in both the accuracy and convergence rate with respect to the k-means algorithm. Hence, this work presents two main contributions. Firstly, we propose the general inverse stereographic projection into the Bloch sphere as a better embedding for quantum machine learning algorithms; here, we use the problem of clustering quadrature amplitude modulated optical-fibre signals as an example. Secondly, as a purely classical contribution inspired by the first contribution, we propose and benchmark the use of the general inverse stereographic projection and spherical centroid for clustering optical-fibre signals, showing that optimizing the radius yields a consistent improvement in accuracy and convergence rate.

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arXiv2023

Capacity Bounds for Identification With Effective Secrecy

An upper bound to the identification capacity of discrete memoryless wiretap channels is derived under the requirement of semantic effective secrecy, combining semantic secrecy and stealth constraints. A previously established lower bound is improved by applying it to a prefix channel, formed by concatenating an auxiliary channel and the actual channel. The bounds are tight if the legitimate channel is more capable than the eavesdropper's channel. An illustrative example is provided for a wiretap channel that is composed of a point-to-point channel, and a parallel, reversely degraded wiretap channel. A comparison with results for message transmission and for identification with only secrecy constraint is provided.

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arXiv2023

Deterministic Identification Over Multiple-Access Channels

Deterministic identification over K-input multiple-access channels with average input cost constraints is considered. The capacity region for deterministic identification is determined for an average-error criterion, where arbitrarily large codes are achievable. For a maximal-error criterion, upper and lower bounds on the capacity region are derived. The bounds coincide if all average partial point-to-point channels are injective under the input constraint, i.e. all inputs at one terminal are mapped to distinct output distributions, if averaged over the inputs at all other terminals. The achievability is proved by treating the MAC as an arbitrarily varying channel with average state constraints. For injective average channels, the capacity region is a hyperrectangle. The modulo-2 and modulo-3 binary adder MAC are presented as examples of channels which are injective under suitable input constraints. The binary multiplier MAC is presented as an example of a non-injective channel, where the achievable identification rate region still includes the Shannon capacity region.

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arXiv2022

Comparison of Quantum PUF models

Physical unclonable functions (PUFs) are hardware structures in a physical system (e.g. semiconductor, crystals etc.) that are used to enable unique identification of the semiconductor or to secure keys for cryptographic processes. A PUF thus generates a noisy secret reproducible at runtime. This secret can either be used to authenticate the chip, or it is available as a cryptographic key after removing the noise. Latest advancements in the field of quantum hardware, in some cases claiming to achieve quantum supremacy, highly target the fragility of current RSA type classical cryptosystems. As a solution, one would like to develop Quantum PUFs to mitigate such problem. There are several approaches for this technology. In our work we compare these different approaches and introduce the requirements for QTOKSim, a quantum token based authentication simulator testing its performance on a multi-factor authentication protocol.

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arXiv2021

Integrating Quantum Simulation for Quantum-Enhanced Classical Network Emulation

We describe a method of investigating the near-term potential of quantum communication technology for communication networks from the perspective of current networks. For this, we integrate an instance of the quantum network simulator QuNetSim at the link layer into the communication network emulator ComNetsEmu. This novel augmented version of ComNetsEmu is thereby enabled to run arbitrary quantum protocols between any directly connected pair of network hosts. To give an example of the proposed method, we implement the link layer method of generating and storing entanglement while idle, to accelerate data transmission at later times using superdense coding.

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arXiv2021

Reed-Muller Identification

Ahlswede and Dueck identification has the potential of exponentially reducing traffic or exponentially increasing rates in applications where a full decoding of the message is not necessary and, instead, a simple verification of the message of interest suffices. However, the proposed constructions can suffer from exponential increase in the computational load at the sender and receiver, rendering these advantages unusable. This has been shown in particular to be the case for a construction achieving identification capacity based on concatenated Reed-Solomon codes. Here, we consider the natural generalization of identification based on Reed-Muller codes and we show that, although without achieving identification capacity, they allow to achieve the exponentially large rates mentioned above without the computational penalty increasing too much the latency with respect to transmission.

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arXiv2021

Implementation and Experimental Evaluation of Reed-Solomon Identification

Identification is a communication paradigm that promises exponential advantages over transmission for applications that do not actually require all messages to be reliably transmitted. Notably, the identification capacity theorems prove exponentially larger rates compared to classical transmission. However, there exist additional trade-offs that are not captured by these theorems and which become relevant for the deployment of identification in practical communication settings. In particular, in this paper we evaluate the latency introduced by computations at the encoder and decoder when employing identification codes. For this, we implement them using an explicit code construction based on Reed-Solomon codes and integrate it into a single carrier transmission system using software-defined radios. Our evaluation of the practical aspects of identification codes show that unless care is taken, these trade-offs can compromise the theoretical advantage given by the exponentially large identification rates.

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arXiv2021

The Computational and Latency Advantage of Quantum Communication Networks

This article summarises the current status of classical communication networks and identifies some critical open research challenges that can only be solved by leveraging quantum technologies. By now, the main goal of quantum communication networks has been security. However, quantum networks can do more than just exchange secure keys or serve the needs of quantum computers. In fact, the scientific community is still investigating on the possible use cases/benefits that quantum communication networks can bring. Thus, this article aims at pointing out and clearly describing how quantum communication networks can enhance in-network distributed computing and reduce the overall end-to-end latency, beyond the intrinsic limits of classical technologies. Furthermore, we also explain how entanglement can reduce the communication complexity (overhead) that future classical virtualised networks will experience.

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arXiv2021

Key Assistance, Key Agreement, and Layered Secrecy for Bosonic Broadcast Channels

Secret-sharing building blocks based on quantum broadcast communication are studied. The confidential capacity region of the pure-loss bosonic broadcast channel is determined, both with and without key assistance, and an achievable region is established for the lossy bosonic broadcast channel. If the main receiver has a transmissivity of \eta<1/2, then confidentiality solely relies on the key-assisted encryption of the one-time pad. We also address conference key agreement for the distillation of two keys, a public key and a secret key. A regularized formula is derived for the key-agreement capacity region in finite dimensions. In the bosonic case, the key-agreement region is included within the capacity region of the corresponding broadcast channel with confidential messages. We then consider a network with layered secrecy, where three users with different security ranks communicate over the same broadcast network. We derive an achievable layered-secrecy region for a pure-loss bosonic channel that is formed by the concatenation of two beam splitters.

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arXiv2020

Performance Analysis of Identification Codes

In this paper we analyse the construction of identification codes. Identification codes are based on the question "Is the message I have just received the one I am interested in?", as opposed to Shannon's transmission, where the receiver is interested in not only one, but any message. The advantage of identification is that it allows rates growing double exponentially in the blocklength at the cost of not being able to decode every message, which might be beneficial in certain applications. We focus on a special identification code construction based on two concatenated Reed-Solomon codes and have a closer look at its implementation, analyzing the trade-offs of identification with respect to transmission and the trade-offs introduced by the computational cost of identification codes.

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arXiv2020

Upper bounds on device-independent quantum key distribution

Quantum key distribution (QKD) is a method that distributes a secret key to a sender and a receiver by the transmission of quantum particles (e.g. photons). Device-independent quantum key distribution (DIQKD) is a version of QKD with a stronger notion of security, in that the sender and receiver base their protocol only on the statistics of input and outputs of their devices as inspired by Bell's theorem. We study the rate at which DIQKD can be carried out for a given bipartite quantum state distributed between the sender and receiver or a quantum channel connecting them. We provide upper bounds on the achievable rate going beyond upper bounds possible for QKD. In particular, we construct states and channels where the QKD rate is significant while the DIQKD rate is negligible. This gap is illustrated for a practical case arising when using standard post-processing techniques for entangled two-qubit states.

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arXiv2020

Semantic Security for Quantum Wiretap Channels

We consider the problem of semantic security via classical-quantum and quantum wiretap channels and use explicit constructions to transform a non-secure code into a semantically secure code, achieving capacity by means of biregular irreducible functions. Explicit parameters in finite regimes can be extracted from theorems. We also generalize the semantic security capacity theorem, which shows that a strongly secure code guarantees a semantically secure code with the same secrecy rate, to any quantum channel, including the infinite-dimensional and non-Gaussian ones.

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