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Today's mobile devices sense, collect, and store huge amounts of personal information, which users share with family and friends through a wide range of applications. Once users give applications access to their data, they must implicitly…
As Automated Driving Systems (ADS) technology advances, ensuring safety and public trust requires robust assurance frameworks, with safety cases emerging as a critical tool toward such a goal. This paper explores an approach to assess how a…
The secret keys of critical network authorities - such as time, name, certificate, and software update services - represent high-value targets for hackers, criminals, and spy agencies wishing to use these keys secretly to compromise other…
In todays scenario, various organizations store their sensitive data in the cloud environment. Multiple problems are present while retrieving and storing vast amounts of data, such as the frequency of data requests (increasing the…
While sparse autoencoders (SAEs) have generated significant excitement, a series of negative results have added to skepticism about their usefulness. Here, we establish a conceptual distinction that reconciles competing narratives…
Sparse autoencoders (SAEs) enable interpretability research by decomposing entangled model activations into monosemantic features. However, under what circumstances SAEs derive most fine-grained latent features for safety, a low-frequency…
Security issues are the most challenging problems in cloud computing environments as an emerging technology. Regarding to this importance, an efficient and reliable user authentication and data protection model has been presented in this…
The development of privacy-preserving automatic speaker verification systems has been the focus of a number of studies with the intent of allowing users to authenticate themselves without risking the privacy of their voice. However, current…
Transferable adversarial examples cause practical security risks since they can mislead a target model without knowing its internal knowledge. A conventional recipe for maximizing transferability is to keep only the optimal adversarial…
A symmetric searchable encryption (SSE) scheme allows a client (data owner) to search on encrypted data outsourced to an untrusted cloud server. The search may either be a single keyword search or a complex query search like conjunctive or…
Attestation means providing evidence that a remote target system is worthy of trust for some sensitive interaction. Although attestation is already used in network access control, security management, and trusted execution environments, it…
The growing scalability demand of public Blockchains led to the rise of Layer-2 solutions, such as Rollups. Rollups improve transaction throughput by processing operations off-chain and posting the results on-chain. A critical component in…
Substring-searchable symmetric encryption (substring-SSE) has become increasingly critical for privacy-preserving applications in cloud systems. However, existing schemes remain vulnerable to information leakage during search operations,…
Privacy leakage in AI-based decision processes poses significant risks, particularly when sensitive information can be inferred. We propose a formal framework to audit privacy leakage using abductive explanations, which identifies minimal…
At present, the cloud storage used in searchable symmetric encryption schemes (SSE) is provided in a private way, which cannot be seen as a true cloud. Moreover, the cloud server is thought to be credible, because it always returns the…
With the advent of cloud computing, a number of cloud providers have arisen to provide Storage-as-a-Service (SaaS) offerings to both regular consumers and business organizations. SaaS (different than Software-as-a-Service in this context)…
Safety-critical software systems are those whose failure or malfunction could result in casualty and/or serious financial loss. In such systems, safety assurance cases (SACs) are an emerging approach that adopts a proactive strategy to…
Recent attacks on federated learning demonstrate that keeping the training data on clients' devices does not provide sufficient privacy, as the model parameters shared by clients can leak information about their training data. A 'secure…
Trusted Execution Environments (TEEs) are designed to protect the privacy and integrity of data in use. They enable secure data processing and sharing in peer-to-peer networks, such as vehicular ad hoc networks of autonomous vehicles,…
Fake news detection becomes particularly challenging in real-time scenarios, where emerging events often lack sufficient supporting evidence. Existing approaches often rely heavily on external evidence and therefore struggle to generalize…