Wei Zhou

Jialun Zhong, Wei Shen, Yanzeng Li et al.

Reward Model (RM) has demonstrated impressive potential for enhancing Large Language Models (LLM), as RM can serve as a proxy for human preferences, providing signals to guide LLMs' behavior in various tasks. In this paper, we provide a comprehensive overview of relevant research, exploring RMs from the perspectives of preference collection, reward modeling, and usage. Next, we introduce the applications of RMs and discuss the benchmarks for evaluation. Furthermore, we conduct an in-depth analysis of the challenges existing in the field and dive into the potential research directions. This paper is dedicated to providing beginners with a comprehensive introduction to RMs and facilitating future studies. The resources are publicly available at github\footnote{https://github.com/JLZhong23/awesome-reward-models}.

Jiun Tian Hoe, Weipeng Hu, Wei Zhou et al.

This paper presents InteractEdit, a novel framework for zero-shot Human-Object Interaction (HOI) editing, addressing the challenging task of transforming an existing interaction in an image into a new, desired interaction while preserving the identities of the subject and object. Unlike simpler image editing scenarios such as attribute manipulation, object replacement or style transfer, HOI editing involves complex spatial, contextual, and relational dependencies inherent in humans-objects interactions. Existing methods often overfit to the source image structure, limiting their ability to adapt to the substantial structural modifications demanded by new interactions. To address this, InteractEdit decomposes each scene into subject, object, and background components, then employs Low-Rank Adaptation (LoRA) and selective fine-tuning to preserve pretrained interaction priors while learning the visual identity of the source image. This regularization strategy effectively balances interaction edits with identity consistency. We further introduce IEBench, the most comprehensive benchmark for HOI editing, which evaluates both interaction editing and identity preservation. Our extensive experiments show that InteractEdit significantly outperforms existing methods, establishing a strong baseline for future HOI editing research and unlocking new possibilities for creative and practical applications. Code will be released upon publication.

Wei Zhou, Le Guan, Peng Liu et al.

Emulating firmware for microcontrollers is challenging due to the tight coupling between the hardware and firmware. This has greatly impeded the application of dynamic analysis tools to firmware analysis. The state-of-the-art work automatically models unknown peripherals by observing their access patterns, and then leverages heuristics to calculate the appropriate responses when unknown peripheral registers are accessed. However, we empirically found that this approach and the corresponding heuristics are frequently insufficient to emulate firmware. In this work, we propose a new approach called uEmu to emulate firmware with unknown peripherals. Unlike existing work that attempts to build a general model for each peripheral, our approach learns how to correctly emulate firmware execution at individual peripheral access points. It takes the image as input and symbolically executes it by representing unknown peripheral registers as symbols. During symbolic execution, it infers the rules to respond to unknown peripheral accesses. These rules are stored in a knowledge base, which is referred to during the dynamic firmware analysis. uEmu achieved a passing rate of 95% in a set of unit tests for peripheral drivers without any manual assistance. We also evaluated uEmu with real-world firmware samples and new bugs were discovered.

Wei Zhou, Chen Cao, Dongdong Huo et al.

In recent years, IoT platforms and systems have been rapidly emerging. Although IoT is a new technology, new does not mean simpler (than existing networked systems). Contrarily, the complexity (of IoT platforms and systems) is actually being increased in terms of the interactions between the physical world and cyberspace. The increased complexity indeed results in new vulnerabilities. This paper seeks to provide a review of the recently discovered logic bugs that are specific to IoT platforms and systems. In particular, 17 logic bugs and one weakness falling into seven categories of vulnerabilities are reviewed in this survey.

Wei Zhou, Le Guan, Peng Liu et al.

As more and more embedded devices are connected to the Internet, leading to the emergence of Internet-of-Things (IoT), previously less tested (and insecure) devices are exposed to miscreants. To prevent them from being compromised, the memory protection unit (MPU), which is readily available on many devices, has the potential to become a free lunch for the defenders. To our surprise, the MPU is seldom used by real-world products. The reasons are multi-fold. While there are non-technical reasons such as compatibility issues, more importantly, we found that MPU brings virtually no security enhancement at the expense of decreased performance and responsiveness. In this work, we investigate the MPU adoption in major real-time operating systems (RTOSs), in particular, the FreeRTOS, and try to pinpoint the fundamental reasons to explain why MPU is not favored. We hope our findings can inspire new remedial solutions to change the situation. We also review the latest MPU design and provide technical suggestions to build more secure embedded systems.

Wei Zhou, Yan Jia, Yao Yao et al.

A smart home connects tens of home devices to the Internet, where an IoT cloud runs various home automation applications. While bringing unprecedented convenience and accessibility, it also introduces various security hazards to users. Prior research studied smart home security from several aspects. However, we found that the complexity of the interactions among the participating entities (i.e., devices, IoT clouds, and mobile apps) has not yet been systematically investigated. In this work, we conducted an in-depth analysis of five widely-used smart home platforms. Combining firmware analysis, network traffic interception, and blackbox testing, we reverse-engineered the details of the interactions among the participating entities. Based on the details, we inferred three legitimate state transition diagrams for the three entities, respectively. Using these state machines as a reference model, we identified a set of unexpected state transitions. To confirm and trigger the unexpected state transitions, we implemented a set of phantom devices to mimic a real device. By instructing the phantom devices to intervene in the normal entity-entity interactions, we have discovered several new vulnerabilities and a spectrum of attacks against real-world smart home platforms.

Wei Zhou, Yuqing Zhang, Peng Liu

The future of Internet of Things (IoT) is already upon us. IoT applications have been widely used in many field of social production and social living such as healthcare, energy and industrial automation. While enjoying the convenience and efficiency that IoT brings to us, new threats from IoT also have emerged. There are increasing research works to ease these threats, but many problems remain open. To better understand the essential reasons of new threats and the challenges in current research, this survey first proposes the concept of "IoT features". Then, the security and privacy effects of eight IoT new features were discussed including the threats they cause, existing solutions and challenges yet to be solved. To help researchers follow the up-to-date works in this field, this paper finally illustrates the developing trend of IoT security research and reveals how IoT features affect existing security research by investigating most existing research works related to IoT security from 2013 to 2017.