相关论文: Finding Safety in Numbers with Secure Allegation E…

Face recognition systems have become increasingly vulnerable to security threats in recent years, prompting the use of Face Anti-spoofing (FAS) to protect against various types of attacks, such as phone unlocking, face payment, and…

In the context of prediction-as-a-service, concerns about the privacy of the data and the model have been brought up and tackled via secure inference protocols. These protocols are built up by using single or multiple cryptographic tools…

Performing searches over encrypted data is a very current and active area. Several efficient solutions have been provided for the single-writer scenario in which all sensitive data originates with one party (the Data Owner) that encrypts it…

The SEAR Dataset is a novel multimodal resource designed to study the emerging threat of social engineering (SE) attacks orchestrated through augmented reality (AR) and multimodal large language models (LLMs). This dataset captures 180…

Secure outsourced computation (SOC) provides secure computing services by taking advantage of the computation power of cloud computing and the technology of privacy computing (e.g., homomorphic encryption). Expanding computational…

We study the problem of remote state estimation, in the presence of an eavesdropper. An authorized user estimates the state of a linear plant, based on the data received from a sensor, while the data may also be intercepted by the…

Conflicting explanations, arising from different attribution methods or model internals, limit the adoption of machine learning models in safety-critical domains. We turn this disagreement into an advantage and introduce EXplanation…

Frontier artificial intelligence (AI) systems pose increasing risks to society, making it essential for developers to provide assurances about their safety. One approach to offering such assurances is through a safety case: a structured,…

Searchable symmetric encryption (SSE) enables a client to perform searches over its outsourced encrypted files while preserving privacy of the files and queries. Dynamic schemes, where files can be added or removed, leak more information…

We present SAFE, an integrated system for managing trust using a logic-based declarative language. Logical trust systems authorize each request by constructing a proof from a context---a set of authenticated logic statements representing…

Although Retrieval-Augmented Generation (RAG) systems have been widely applied, the privacy and security risks they face, such as data leakage and data poisoning, have not been systematically addressed yet. Existing defense strategies…

We propose a framework for threshold cryptosystems under a permissionless-economic model in which the participants are rational profit-maximizing entities. To date, threshold cryptosystems have been considered under permissioned settings…

Confidential services running in hardware-protected Trusted Execution Environments (TEEs) can provide higher security assurance, but this requires custom clients and protocols to distribute, update, and verify their attestation evidence.…

Many organizations stand to benefit from pooling their data together in order to draw mutually beneficial insights -- e.g., for fraud detection across banks, better medical studies across hospitals, etc. However, such organizations are…

Accountability is a recent paradigm in security protocol design which aims to eliminate traditional trust assumptions on parties and hold them accountable for their misbehavior. It is meant to establish trust in the first place and to…

Secure aggregation (SA) is fundamental to privacy preservation in federated learning (FL), enabling model aggregation while preventing disclosure of individual user updates. This paper addresses hierarchical secure aggregation (HSA) against…

We provide enhanced security against insider attacks in services that manage extremely sensitive data. One example is a #MeToo use case where sexual harassment complaints are reported but only revealed when another complaint is filed…

Companies have increasingly turned to application service providers (ASPs) or Software as a Service (SaaS) vendors to offer specialized web-based services that will cut costs and provide specific and focused applications to users. The…

In many applications, an anomaly detection system presents the most anomalous data instance to a human analyst, who then must determine whether the instance is truly of interest (e.g. a threat in a security setting). Unfortunately, most…

Anonymous Identity-Based Encryption can protect privacy of the receiver. However, there are some situations that we need to recover the identity of the receiver, for example a dispute occurs or the privacy mechanism is abused. In this…