A5043005537- Advanced Malware Detection Techniques
- Network Security and Intrusion Detection
- Security and Verification in Computing
- Anomaly Detection Techniques and Applications
- Adversarial Robustness in Machine Learning
- Cloud Data Security Solutions
- Internet Traffic Analysis and Secure E-voting
- Access Control and Trust
- Blockchain Technology Applications and Security
- Acute Ischemic Stroke Management
- Digital Media Forensic Detection
- Intracerebral and Subarachnoid Hemorrhage Research
- Generative Adversarial Networks and Image Synthesis
- Brain Tumor Detection and Classification
- Cerebrovascular and Carotid Artery Diseases
- Advanced Image Processing Techniques
- Neurological Disorders and Treatments
- Wireless Signal Modulation Classification
- Radiomics and Machine Learning in Medical Imaging
- User Authentication and Security Systems
- Image Processing Techniques and Applications
- Advanced Vision and Imaging
- Advanced X-ray and CT Imaging
- Stroke Rehabilitation and Recovery
- Software Testing and Debugging Techniques
Westlake University
2024-2025
Hangzhou First People's Hospital
2022-2025
Beijing Institute of Technology
2021-2024
Zhejiang Chinese Medical University
2024
Zhejiang University
2022
Nankai University
2019-2020
Machine learning has become an important method in malware detection. However, due to the weakness of machine models, a large number researches related adversarial emerged. At present, about mainly focus on image and speech recognition. In field detection, because feature modification can easily damage integrity functionality code, it is usually through adding noise such as garbage instructions achieve fooling detection model. this paper, we propose model based OpCode n-grams feature. We...
Android as an operating system is now increasingly being adopted in industrial information systems, especially with cyber-physical systems (CPS). This also puts devices onto the front line of handling security-related data and conducting sensitive behaviors, which could be misused by increasing number polymorphic metamorphic malicious applications targeting platform. The existence such malware threats, therefore, call for more accurate identification surveillance app essential to security...
Microservices architecture is a new paradigm for application development. The problem of optimising the performance microservice architectures from non-functional perspective typical Nondeterministic Polynomial (NP) problem. Therefore, aiming to quantify requirements computing systems, while solving latency in best combination services with maximum QoS objective function value, this paper proposes approach based on model and CGWO algorithm optimisation computation model. experimental results...
Deep map prediction plays a crucial role in comprehending the three-dimensional structure of scene, which is essential for enabling mobile robots to navigate autonomously and avoid obstacles complex environments. However, most existing depth estimation algorithms based on deep neural networks rely heavily specific datasets, resulting poor resistance model interference. To address this issue, paper proposes implements an optimized monocular image algorithm conditional generative adversarial...
Botnet is one of the most significant threats to Internet so that many botnet detection approaches have been proposed based on machine learning techniques. But botnets evolve more and rapidly over 70% malware created today uses or evasion techniques avoid detection. Consequently, models static threshold facing concept drift challenge. In this paper, we introduced Venn-Abers algorithm into model mitigate problem. We selected KNN KDE as scoring classifier build a predictor. The experiments...
Fifth-generation (5G) wireless systems provide an opportunity for improving the existing Voice over Internet Protocol communication service's user experience. To mitigate security risk of 5G data leakage, building covert channel is alternative approach providing confidential transmission. Due to high transmission rate 5G, interpacket intervals become small and derandomized, this caused encoding phase timing imports relatively large modulation errors. rearranging a widespread phenomenon that...
Abstract Objective Granger causal analysis (GCA) and amplitude of low‐frequency fluctuation (ALFF) are commonly used to evaluate functional alterations in brain disorders. By combining the GCA ALFF, this study aimed investigate effective connectivity (EC) changes patients with acute ischemic stroke (AIS) anterior circulation occlusion after mechanical thrombectomy (MT). Methods Resting‐state magnetic resonance imaging (rs‐fMRI) data were collected from 43 AIS within 1 week post‐MT 37 healthy...
Remote attestation (RA) is an essential feature in many security protocols to verify the memory integrity of remote embedded devices susceptible malware infections. The process needs be consecutive and atomic prevent a self-relocating from evading detection. Most prior techniques disable interrupts during execution another interrupting check. This paper investigates shortcomings existing software-based stresses threat debug exceptions attestation. We present Debug Register-based...
<title>Abstract</title> <bold>Background:</bold> The poor prognosis of patients with acute ischemic stroke (AIS) after bridging therapy (BT) imposes a heavy burden on their families. This study decided to investigate the risk factors for and establish predictive model.<bold>Objective:</bold> To explore in AIS BT.<bold>Methods:</bold> included treated BT (intravenous thrombolysis alteplase prior endovascular thrombectomy) from January 2020 December 2023 Hangzhou First People's Hospital....
Objectives: This study aimed to explore the risk factors for stroke-associated pneumonia (SAP) and assess predictive value of Serum Amyloid A (SAA) combined with neutrophil-to-lymphocyte ratio (NLR) on SAP. Methods: The included acute ischemic stroke (AIS) patients from January 2021 June 2022 in our hospital. patients’ history chronic diseases, clinical characteristics, laboratory testing data were recorded. SPSS 22 was used statistical analysis. Receiver operating characteristics (ROC)...
Deep neural networks (DNNs) have made tremendous progress in the past ten years and been applied various critical applications. However, recent studies shown that deep are vulnerable to backdoor attacks. By injecting malicious data into training set, an adversary can plant original model. The remain hidden indefinitely until activated by a sample with specific trigger, which is hugely concealed, bringing serious security risks one main limitation of current attacks trigger often visible...
Deep neural networks (DNNs) have gain its popularity in various scenarios recent years. However, excellent ability of fitting complex functions also makes it vulnerable to backdoor attacks. Specifically, a can remain hidden indefinitely until activated by sample with specific trigger, which is hugely concealed. Nevertheless, existing attacks operate backdoors spatial domain, i.e., the poisoned images are generated adding additional perturbations original images, easy detect. To bring...
With recent cyber security attacks, the "border defense" protection mechanism has often penetrated and broken through, "borderless" defense idea—Zero Trust was proposed. The device application sandbox deployment model is one of four essential Zero architecture models. isolation directly affects trusted applications. Given risks, such as escape in application, we propose a hybrid based on access behavior give formal definition characteristics model. dynamically determines identity subject...
For malware detection, current state-of-the-art research concentrates on machine learning techniques. Binary <math xmlns="http://www.w3.org/1998/Math/MathML" id="M1"><mi>n</mi></math> -gram OpCode features are commonly used for malicious code identification and classification with high accuracy. modification is much more difficult than of image pixels. Traditional adversarial perturbation methods could not be applied directly. In this paper, we propose a bidirectional universal method...
The Unified Extensible Firmware Interface (UEFI) provides a specification of the software interface between an OS and its underlying platform firmware. UEFI UI is interactive that allows users to configure manage settings, which closely related HII (Human Infrastructure). In practice, mechanism developers create elements with HII-related protocols. this paper, we provide comprehensive analysis combined case study. We proposed protocol-centered static method obtain UEFI’s password policy,...