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We present UMI-3D, a multimodal extension of the Universal Manipulation Interface (UMI) for robust and scalable data collection in embodied manipulation. While UMI enables portable, wrist-mounted data acquisition, its reliance on monocular…
Honeypots are a deceptive technology used to capture malicious activity. The technology is useful for studying attacker behavior, tools, and techniques but can be difficult to implement and maintain. Historically, a lack of measures of…
In this paper, we describe an open source Python toolkit named Uncertainty Quantification 360 (UQ360) for the uncertainty quantification of AI models. The goal of this toolkit is twofold: first, to provide a broad range of capabilities to…
Universal machine learning interatomic potentials (uMLIPs) are reshaping atomistic simulation as foundation models, delivering near \textit{ab initio} accuracy at a fraction of the cost. Yet the lack of reliable, general uncertainty…
Nowadays most of the malware applications are either packed or protected. This techniques are applied especially to evade signature based detectors and also to complicate the job of reverse engineers or security analysts. The time one must…
This paper presents pragmatic solutions for verifying complex mathematical algorithms implemented in hardware in an efficient and effective manner. Maximizing leverage of a known-answer-test strategy, based on predefined data scenarios…
With the rapid advancement of information technology, the complexity of applications continues to increase, and the cybersecurity challenges we face are also escalating. This paper aims to investigate the methods and practices of system…
Machine-learned interatomic potentials (MLIPs) are deployed for high-throughput materials screening without formal reliability guarantees. We show that a single MLIP used as a stability filter misses 93% of density functional theory…
In this demonstration, we present an open source toolkit for evaluating non-intrusive load monitoring research; a field which aims to disaggregate a household's total electricity consumption into individual appliances. The toolkit contains:…
Software integrity measurement and attestation (M&A) are critical technologies for evaluating the trustworthiness of software platforms. To best support these technologies, next generation systems must provide a centralized service for…
Nowadays, IoT devices integrate a wealth of third-party components (TPCs) in firmware to shorten the development cycle. TPCs usually have strict usage specifications, e.g., checking the return value of the function. Violating the usage…
Realm Management Monitor (RMM) is an essential firmware component within the recent Arm Confidential Computing Architecture (Arm CCA). Previous work applies formal techniques to verify the specification and prototype reference…
Most of today's security solutions, such as security information and event management (SIEM) and signature based IDS, require the operator to evaluate potential attack vectors and update detection signatures and rules in a timely manner.…
We present VERIFAI, a software toolkit for the formal design and analysis of systems that include artificial intelligence (AI) and machine learning (ML) components. VERIFAI particularly seeks to address challenges with applying formal…
Ensuring usability is crucial for the success of mobile apps. Usability issues can compromise user experience and negatively impact the perceived app quality. This paper presents UX-LLM, a novel tool powered by a Large Vision-Language Model…
The proliferation of Internet of Things (IoT) devices has introduced significant security challenges, primarily due to the opacity of firmware components and the complexity of supply chain dependencies. IoT firmware frequently relies on…
Robust and accurate pose estimation is crucial for many applications in mobile robotics. Extending visual Simultaneous Localization and Mapping (SLAM) with other modalities such as an inertial measurement unit (IMU) can boost robustness and…
As neural networks are increasingly used for critical decision-making tasks, the threat of integrity attacks, where an adversary maliciously alters a model, has become a significant security and safety concern. These concerns are compounded…
As the development of Large Models (LMs) progresses rapidly, their safety is also a priority. In current Large Language Models (LLMs) and Multimodal Large Language Models (MLLMs) safety workflow, evaluation, diagnosis, and alignment are…
User simulators are increasingly central to interactive information retrieval, yet the community lacks standardized evaluation tools. Simulators serve two objectives, behavioral realism (matching real user behavior) and tester reliability…