A5084076598- Advanced Malware Detection Techniques
- Blockchain Technology Applications and Security
- User Authentication and Security Systems
- Network Security and Intrusion Detection
- Security and Verification in Computing
- Software Testing and Debugging Techniques
- Speech and Audio Processing
- Indoor and Outdoor Localization Technologies
- Security in Wireless Sensor Networks
- Caching and Content Delivery
- Cryptography and Data Security
- Complex Network Analysis Techniques
- Digital and Cyber Forensics
- Physical Unclonable Functions (PUFs) and Hardware Security
- FinTech, Crowdfunding, Digital Finance
- Advanced Graph Neural Networks
- Topic Modeling
- Spam and Phishing Detection
- Distributed systems and fault tolerance
- Privacy-Preserving Technologies in Data
- Cloud Data Security Solutions
- Explainable Artificial Intelligence (XAI)
- Emotion and Mood Recognition
- Digital Media Forensic Detection
- Access Control and Trust
Michigan State University
2020-2024
Michigan United
2021
With recent advances in artificial intelligence and natural language processing, voice has become a primary method for human-computer interaction.It enabled game-changing new technologies both commercial sectors military sectors, such as Siri, Alexa, Google Assistant, voice-controlled naval warships.Recently, researchers have demonstrated that these assistant systems are susceptible to signal injection at the inaudible frequencies.To date, most of existing works focus primarily on delivering...
Ethereum is a permissionless blockchain ecosystem that supports execution of smart contracts, the key enablers decentralized finance (DeFi) and non-fungible tokens (NFT). However, expressiveness contracts double-edged sword: while it enables programmability, also introduces security vulnerabilities, i.e., exploitable discrepancies between expected actual behaviors contract code. To address these increase vulnerability coverage, we propose new testing approach called transaction...
With the emergence of low-cost smart and connected IoT devices, area cyber-physical security is becoming increasingly important. Past research has demonstrated new threat vectors targeting transition process between cyber physical domains, where attacker exploits sensing system as an attack surface for signal injection or extraction private information. Recently, there have been attempts to characterize abstracted model injection, but they primarily focus on path processing. This paper aims...
Inaudible voice command injection is one of the most threatening attacks towards assistants. Existing aim at injecting attack signals over air, but they require access to authorized user's for activating Moreover, effectiveness can be greatly deteriorated in a noisy environment. In this paper, we explore new type channel, power line side-channel, launch inaudible injection. By audio through modified charging cable, becomes more resilient against various environmental factors and liveness...
Malware detection and classification are crucial for protecting digital devices information systems. Accurate identification of malware enables researchers incident responders to take prompt measures against mitigate its damage. With the development attention mechanisms in field computer vision, mechanism-based techniques also rapidly evolving. The essence mechanism is focus on interest suppress useless information. In this paper, we develop different plug-and-play based ResNeXt tagging...
As many real-world networks evolve over time, such as social networks, user-item and IP-IP anomaly detection for dynamic graphs has attracted growing attention. Most existing studies focus on detecting anomalous nodes or edges but fail to detect motif instances. In this paper, we propose MADG, a general Motif-level Anomaly Detection framework Graphs, which can identify the in different motifs. Motifs are specific subgraph structures that frequently occur network have been widely used...
With the explosive increase in wireless devices, physical-layer signal analysis has become critically beneficial across distinctive domains including interference minimization network planning, security and privacy (e.g., drone spycam detection), mobile health with remote sensing. While SDR is known to be highly effective realizing such services, they are rarely deployed or used by end-users due costly hardware ~1K USD USRP). Low-cost SDRs RTL-SDR) available, but their bandwidth limited 2-3...
Due to the growing presence of Internet Things (IoT) apps and devices in smart homes cities, there are more concerns about their security privacy risks. IoT normally interact with each other physical world offer utility users. In this paper, we investigate safety risks brought by interactive behaviors apps. Two major challenges ensue identifying interaction threats: i) how discover threats across both cyber channels; ii) ensure scalability detection approach. To address these challenges,...
With the rapid development of automation tools including polymorphic and metamorphic engines, generic packers, genetic programming, many variants malware have emerged, which pose a significant threat to Internet security. To effectively detect variants, researchers developed visualization-based approaches that can visualize adaptations for in-depth analysis. However, most existing visualization rely on binary image sample, fail provide an effective texture feature representation thus often...
Hardware wallets are designed to withstand malware attacks by isolating their private keys from the cyberspace, but they vulnerable that fake an address stored in a clipboard. To prevent such attacks, hardware wallet asks user verify recipient shown on display. Since crypto addresses long sequences of random symbols, manual verification becomes difficult task. Consequently, many users elect only few symbols address, and this can be exploited attacker. In work, we introduce EthClipper, attack...
Public blockchains have spurred the growing popularity of decentralized transactions and smart contracts, especially on financial market. However, public exhibit their limitations transaction throughput, storage availability, compute capacity. To avoid gridlock, impose large fees per-block resource limits, making it difficult to accommodate ever-growing high demand. Previous research endeavors improve scalability performance blockchain through various technologies, such as side-chaining,...
Being able to automatically detect the performance issues in apps can significantly improve apps' quality as well having a positive influence on user satisfaction. <underline xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">A</u> pplication xmlns:xlink="http://www.w3.org/1999/xlink">P</u> erformance xmlns:xlink="http://www.w3.org/1999/xlink">M</u> anagement (APM) libraries are used locate bottleneck, monitor their behaviors at runtime, and identify...
Current data-driven intelligent transportation systems are mainly reliant on IEEE 802.11p to collect and exchange information. Despite promising performance of in providing low-latency communications, it is still vulnerable jamming attacks due the lack a PHY-layer countermeasure technique practice. In this paper, we propose JammingBird, novel receiver design that tolerates strong constant attacks. The enablers JammingBird two MIMO-based techniques: Jamming-resistant synchronizer suppressor....
The rising popularity of the Internet-of-Things (IoT) devices has driven their increasing adoption in various settings, such as modern homes. IoT systems integrate physical with third-party apps, which can coordinate arbitrary ways. However, malicious or undesired coordination lead to serious vulnerabilities. This paper explores two different ways, i.e., a commonly-used state-based approach and holistic, rule-based approach, formally model app safety security thereof context platforms. less...
In cellular networks, multiuser multiple-input multiple-output (MU-MIMO) is a key technology and has already been deployed in many real systems. Recently, device-to-device (D2D) communication emerged as another promising it offers several advantages, such traffic offloading, low-latency transmissions, enhanced spectral efficiency. Although there are results of these two technologies, most them limited to their respective domains lack practical design combine both technologies for networks....
Autonomous vehicles (AVs), equipped with numerous sensors such as camera, LiDAR, radar, and ultrasonic sensor, are revolutionizing the transportation industry. These expected to sense reliable information from a physical environment, facilitating critical decision-making process of AVs. Ultrasonic sensors, which detect obstacles in short distance, play an important role assisted parking blind spot detection events. However, due their weak security level, particularly vulnerable signal...
Expression recognition holds great promise for applications such as content recommendation and mental healthcare by accurately detecting users' emotional states. Traditional methods often rely on cameras or wearable sensors, which raise privacy concerns add extra device burdens. In addition, existing acoustic-based struggle to maintain satisfactory performance when there is a distribution shift between the training dataset inference dataset. this paper, we introduce FacER+, an active...
Large Language Models (LLMs) have demonstrated great capabilities in natural language understanding and generation, largely attributed to the intricate alignment process using human feedback. While has become an essential training component that leverages data collected from user queries, it inadvertently opens up avenue for a new type of user-guided poisoning attacks. In this paper, we present novel exploration into latent vulnerabilities pipeline recent LLMs, revealing subtle yet effective...