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Gabriele Gianini

Publications and source records attributed to Gabriele Gianini.

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After Theft: From Revocation to Neutralization in the Custody of Quantum Clones

Encrypted quantum cloning enables the creation of multiple encrypted clones of an unknown quantum state while allowing only one effective decryption, with the decryption resource being intrinsically consumed in the process. In this paper, we argue that this property supports a distinctive custodial security primitive for post-compromise response. We consider a threat model in which an adversary steals an encrypted quantum clone but does not yet possess the corresponding decryption key. In such a scenario, a legitimate custodian may unseal a different trusted clone, thereby exhausting the sole available unsealing opportunity and rendering the stolen clone permanently useless. We argue that this mechanism is not adequately described as mere revocation. Rather, it realizes a stronger form of post-theft response, which we call neutralization. We formalize this distinction, locate it within a broader post-theft response space, and introduce a temporal threat model. We compare the mechanism with its closest classical analogue, showing that the classical case can reproduce the policy outcome only through external procedural composition. We finally interpret encrypted quantum cloning as a primitive for post-compromise quantum custody in distributed preservation settings, with prospective relevance for Cyber-Humanities-oriented preservation architectures.

quant-ph

Encrypted clones can leak: Classification of informative subsets in Quantum Encrypted Cloning

Encrypted cloning enables the redundant storage of an unknown qubit while remaining compatible with the no-cloning theorem, since only one clone can later be recovered through key-consuming decryption. Because encryption in this protocol is introduced to enable cloning-compatible redundancy rather than to guarantee confidentiality by design, its secrecy properties must be assessed explicitly. Here we classify the subsets of the encrypted-clone storage register into authorized, completely non-informative, and partially informative sets. We show that intermediate non-authorized subsets may retain only a restricted residual dependence on the input state, and we characterize exactly when this dependence occurs. The resulting leakage pattern is parity-dependent, revealing a structural confidentiality limitation of encrypted cloning.

quant-ph

Full characterization of informative subsets in Quantum Encrypted Cloning

Quantum encrypted cloning, introduced by Yamaguchi and Kempf, is a Pauli-based protocol that distributes an unknown input qubit into multiple encrypted signal-noise pairs in such a way that redundancy is created without violating the no-cloning theorem, since at most one clone can later be perfectly recovered through an appropriate decoding procedure. In previous work we showed that unauthorized subsets of the storage register are not, in general, completely uninformative, and we identified a parity-dependent leakage pattern. In the present work we extend the analysis to subsets that also include the transformed source qubit A. Exploiting the purity of the global encoded state and the complementarity between storage-only subsets and subsets containing A, we derive a full classification of the informativeness of all sets of the form $H=\{A\}\cup C$. We show that these subsets are fully informative in the generic case. Two exceptions arise. First, if all pairs are incomplete and |C|<n, then the reduced state is completely uninformative. Second, if |C|=n, n is odd, and the number q of signal qubits in C is even, then the reduced state is partially informative. In this latter case, the residual dependence on the input state is confined to the y-component of the Bloch vector. These results provide a complete parity-based characterization of leakage for subsets containing the transformed input qubit.

quant-ph

Beyond the Canonical Protocol: Quantum Encrypted Cloning from Secret-Sharing Access Structures

Quantum encrypted cloning shows that an unknown quantum state can be distributed into multiple encrypted copies without contradicting the no-cloning theorem: each copy is unusable on its own, but can be redeemed together with a suitable quantum key. Recent work has related canonical encrypted-cloning protocols to particular forms of quantum secret sharing. Here we take the converse perspective: instead of mapping a given encrypted-cloning protocol into QSS, we use QSS access structures as a design library from which encrypted-cloning schemes can be extracted. The criterion is access-structural. A QSS scheme supports a quantum encrypted-cloning structure whenever it contains a family of qualified sets with a non-qualified common intersection. The common subsystem is interpreted as the key, while the non-common parts are interpreted as encrypted clones relative to that key. Thus quantum encrypted cloning does not require a new notion of recoverability beyond QSS; what changes is the operational reading of QSS constituents as a mechanism for delayed and alternative redemption opportunities. This viewpoint separates redemption from perfect secrecy. Perfect QSS yields encrypted-cloning schemes with forbidden non-qualified subsystems, whereas ramp QSS naturally allows intermediate, partially informative non-redeeming subsystems. The resulting framework broadens quantum encrypted cloning from a specific protocol to a general access-structure primitive. We illustrate the extraction principle with threshold-like, ramp, hierarchical, and compartmented architectures, showing how encrypted clones may be symmetric or asymmetric, individual or composite, perfectly hidden or leaky. Equivalently, these constructions can be viewed as overlapping erasure-recovery regions of an isometric quantum code. This establishes secret sharing as a systematic design language for encrypted quantum redundancy.

quant-ph

The Need for a Green ICT Reference Framework

The sustainability impacts of ICT systems are difficult to assess and govern due to structural complexity, fragmented measurement practices, and unclear responsibilities across system layers. We argue that these challenges cannot be addressed solely by metrics and motivate the need for a shared Green ICT reference framework that integrates sustainability across multiple perspectives and domains, lifecycle phases, and governance contexts. We present an initial framework developed within the Informatics Europe Green ICT Working Group as a first step towards a comprehensive reference framework.

cs.SE

Geometry-Aware Physics-Informed PointNets for Modeling Flows Across Porous Structures

Predicting flows that occur both through and around porous bodies is challenging due to coupled physics across fluid and porous regions and the need to generalize across diverse geometries and boundary conditions. We address this problem using two Physics Informed learning approaches: Physics Informed PointNets (PIPN) and Physics Informed Geometry Aware Neural Operator (P-IGANO). We enforce the incompressible Navier Stokes equations in the free-flow region and a Darcy Forchheimer extension in the porous region within a unified loss and condition the networks on geometry and material parameters. Datasets are generated with OpenFOAM on 2D ducts containing porous obstacles and on 3D windbreak scenarios with tree canopies and buildings. We first verify the pipeline via the method of manufactured solutions, then assess generalization to unseen shapes, and for PI-GANO, to variable boundary conditions and parameter settings. The results show consistently low velocity and pressure errors in both seen and unseen cases, with accurate reproduction of the wake structures. Performance degrades primarily near sharp interfaces and in regions with large gradients. Overall, the study provides a first systematic evaluation of PIPN/PI-GANO for simultaneous through-and-around porous flows and shows their potential to accelerate design studies without retraining per geometry.

cs.LG

Analysing Neural Network Topologies: a Game Theoretic Approach

Artificial Neural Networks have shown impressive success in very different application cases. Choosing a proper network architecture is a critical decision for a network's success, usually done in a manual manner. As a straightforward strategy, large, mostly fully connected architectures are selected, thereby relying on a good optimization strategy to find proper weights while at the same time avoiding overfitting. However, large parts of the final network are redundant. In the best case, large parts of the network become simply irrelevant for later inferencing. In the worst case, highly parameterized architectures hinder proper optimization and allow the easy creation of adverserial examples fooling the network. A first step in removing irrelevant architectural parts lies in identifying those parts, which requires measuring the contribution of individual components such as neurons. In previous work, heuristics based on using the weight distribution of a neuron as contribution measure have shown some success, but do not provide a proper theoretical understanding. Therefore, in our work we investigate game theoretic measures, namely the Shapley value (SV), in order to separate relevant from irrelevant parts of an artificial neural network. We begin by designing a coalitional game for an artificial neural network, where neurons form coalitions and the average contributions of neurons to coalitions yield to the Shapley value. In order to measure how well the Shapley value measures the contribution of individual neurons, we remove low-contributing neurons and measure its impact on the network performance. In our experiments we show that the Shapley value outperforms other heuristics for measuring the contribution of neurons.

cs.AI