Related papers: Quantifying vulnerability of secret generation usi…
Quantum Federated Learning (QFL) promises to revolutionize distributed machine learning by combining the computational power of quantum devices with collaborative model training. Yet, privacy of both data and models remains a critical…
Quantitative theories of information flow give us an approach to relax the absolute confidentiality properties that are difficult to satisfy for many practical programs. The classical information-theoretic approaches for sequential…
Sharing of security data across organizational boundaries has often been advocated as a promising way to enhance cyber threat mitigation. However, collaborative security faces a number of important challenges, including privacy, trust, and…
Quantum key distribution protocols typically make use of a one-way quantum channel to distribute a shared secret string to two distant users. However, protocols exploiting a two-way quantum channel have been proposed as an alternative route…
Although generative AI has been successful in many areas, its ability to model geospatial data is still underexplored. Urban flow, a typical kind of geospatial data, is critical for a wide range of urban applications. Existing studies…
As quantum computers become available through multi-tenant cloud platforms, ensuring privacy against adversaries sharing the same quantum processing unit becomes critical. We introduce and explore \emph{covert quantum computing}, a new…
This paper puts a new light on secure data storage inside distributed systems. Specifically, it revisits computational secret sharing in a situation where the encryption key is exposed to an attacker. It comes with several contributions:…
We analyze the fundamental security significance of the quantitative criteria on the final generated key K in quantum key generation including the quantum criterion d, the attacker's mutual information on K, and the statistical distance…
We show that covert secret key expansion is possible using a public authenticated classical channel and a quantum channel largely under control of an adversary, which we precisely define. We also prove a converse result showing that, under…
Fair representation learning is an attractive approach that promises fairness of downstream predictors by encoding sensitive data. Unfortunately, recent work has shown that strong adversarial predictors can still exhibit unfairness by…
The vulnerability of machine learning systems to adversarial attacks questions their usage in many applications. In this paper, we propose a randomized diversification as a defense strategy. We introduce a multi-channel architecture in a…
Formal verification has emerged as a promising method to ensure the safety and reliability of neural networks. However, many relevant properties, such as fairness or global robustness, pertain to the entire input space. If one applies…
Federated Learning enables collaborative training of a global model across multiple geographically dispersed clients without the need for data sharing. However, it is susceptible to inference attacks, particularly label inference attacks.…
Graph generative diffusion models have recently emerged as a powerful paradigm for generating complex graph structures, effectively capturing intricate dependencies and relationships within graph data. However, the privacy risks associated…
This paper discusses the use of computer-aided verification as a practical means for analysing quantum information systems; specifically, the BB84 protocol for quantum key distribution is examined using this method. This protocol has been…
Quantifying uncertainty in deep regression models is important both for understanding the confidence of the model and for safe decision-making in high-risk domains. Existing approaches that yield prediction intervals overlook distributional…
Current adversarial attack research reveals the vulnerability of learning-based classifiers against carefully crafted perturbations. However, most existing attack methods have inherent limitations in cross-dataset generalization as they…
Secret-key generation exploiting the channel reciprocity between two legitimate parties is an interesting alternative solution to cryptographic primitives for key distribution in wireless systems as it does not rely on an access…
Quantum technology can enable secure communication for cryptography purposes using quantum key distribution. Quantum key distribution protocols provide a secret key between two users with security guaranteed by the laws of quantum…
Existing security proofs of quantum key distribution (QKD) suffer from two fundamental weaknesses. First, memory attacks have emerged as an important threat to the security of even device-independent quantum key distribution (DI-QKD),…