A5047378832- Digital Media Forensic Detection
- Advanced Malware Detection Techniques
- Advanced Steganography and Watermarking Techniques
- Digital and Cyber Forensics
- Network Security and Intrusion Detection
- Distributed Control Multi-Agent Systems
- Internet Traffic Analysis and Secure E-voting
- Advanced Data Storage Technologies
- Data Management and Algorithms
- Complex Network Analysis Techniques
- Privacy-Preserving Technologies in Data
- Spam and Phishing Detection
- Software Testing and Debugging Techniques
- Web Data Mining and Analysis
- Chaos-based Image/Signal Encryption
- Conducting polymers and applications
- Advanced Sensor and Energy Harvesting Materials
- Human Mobility and Location-Based Analysis
- Opportunistic and Delay-Tolerant Networks
- Cryptography and Data Security
- Caching and Content Delivery
- Advanced Database Systems and Queries
- Access Control and Trust
- Security in Wireless Sensor Networks
- Recommender Systems and Techniques
Beijing Chaoyang Emergency Medical Center
2025
Hangzhou Dianzi University
2015-2024
Shandong First Medical University
2024
Tianjin Beichen Hospital
2024
General Hospital of Central Theater Command
2023
Jining First People's Hospital
2020-2023
The University of Sydney
2023
Chinese PLA General Hospital
2023
Beijing Institute of Nanoenergy and Nanosystems
2021-2022
Chinese Academy of Sciences
2017-2022
Abstract Bioresorbable electronic stimulators are of rapidly growing interest as unusual therapeutic platforms, i.e., bioelectronic medicines, for treating disease states, accelerating wound healing processes and eliminating infections. Here, we present advanced materials that support operation in these systems over clinically relevant timeframes, ultimately bioresorbing harmlessly to benign products without residues, eliminate the need surgical extraction. Our findings overcome key...
Federated learning is a novel distributed framework, which enables thousands of participants to collaboratively construct deep model. In order protect confidentiality the training data, shared information between server and are only limited model parameters. However, this setting vulnerable poisoning attack, since have permission modify paper, we perform systematic investigation for such threats in federated propose optimization-based attack. Different from existing methods, primarily focus...
With the prevalence of adopting data-driven convolution neural network (CNN)-based algorithms into community digital image forensics, some novel supervised classifiers have indeed increasingly sprung up with nearly perfect detection rate, compared conventional mechanism. The goal this paper is to investigate a robust multi-classifier for dealing one forensic problems, referred as source camera identification. main contributions are threefold: (1) by mainly analyzing features characterizing...
With the continuous development of computer hardware equipment and deep learning technology, it is easier for people to swap faces in videos by currently-emerging multimedia tampering tools, such as most popular deepfake. It would bring a series new threats security. Although many forensic researches have focused on this type manipulation achieved high detection accuracy, which are based supervised mechanism with requiring large number labeled samples training. In paper, we first develop...
This article investigates the secure and privacy-preserving consensus problem of multiagent systems (MASs) with directed interaction topologies under multiple cyberattacks, which contain deception attacks DoS attacks. First, a unified attack model is introduced to characterize such phenomenon. Besides, considering existence eavesdroppers who can intercept data transmitted on links, fully distributed agent value reconstruction method based idea state decomposition designed prevent leakage...
Abstract. Within China's Loess Plateau there have been concerted revegetation efforts and engineering measures since the 1950s aimed at reducing soil erosion land degradation. As a result, annual streamflow, sediment yield, concentration all decreased considerably. Human-induced use/cover change (LUCC) was dominant factor, contributing over 70 % of load reduction, whereas contribution precipitation less than 30 %. In this study, we use 50-year time series data (1961–2011), showing decreasing...
Due to the booming industry of location-based services, analysis human location histories is increasingly important. Next prediction essential many services. Predicting user's next usually involves obtaining significant places from history trajectories and predicting with a certain statistic model. This paper presents new approaches deal both above problems. For former problem, hierarchical clustering algorithm proposed. We first identify specific features stay points then group GPS...
The problem of authenticating a re-sampled image has been investigated over many years. Currently, however, little research proposes statistical model-based test, resulting in that performance the resampling detector could not be completely analyzed. To fill gap, we utilize parametric model to expose traces forgery, which is described with distribution residual noise. Afterward, propose describing noise from resampled image. Then, detection cast into framework hypothesis testing theory. By...
Smart home is one of the key applications Internet Things (IoT), which allows users to control smart devices in their houses through Internet. However, a system also faces severe challenges terms privacy and confidentiality when are allowed remotely access it. Despite recent research efforts on authentication schemes improve security aspects home, there still unsolved problems. On hand, most existing focus secure communication via trusted third party without taking its leakage into...
To determine the diagnostic value of combining conventional MRI, diffusion-weighted imaging (DWI) and dynamic contrast enhanced MRI (DCE-MRI) in salivary gland tumors.45 patients with tumors were evaluated DWI DCE-MRI prior to surgery confirmed by pathologic findings. The apparent diffusion coefficient (ADC) was calculated from that obtained a factor 0 1000 s mm-2. A time-intensity curve (TIC) DCE-MRI.In benign often showed well-defined clear margins, malignant irregular margins or...
As the scale and capabilities of Large Language Models (LLMs) increase, their applications in knowledge-intensive fields such as legal domain have garnered widespread attention. However, it remains doubtful whether these LLMs make judgments based on knowledge for reasoning. If base solely specific words or patterns, rather than underlying logic language, “LLM-as-judges” paradigm poses substantial risks real-world applications. To address this question, we propose a method injection attacks...
In lung cancer treatment, understanding kinase activity, particularly tyrosine phosphorylation, is crucial but incomplete. We studied phosphoproteomics in 74 patients with non-small-cell (NSCLC) using SH2-Superbinder and data-independent acquisition mass spectrometry. identified 1,048 phosphosites, the highest number reported research. constructed a phosphorylation starmap, enabling novel intuitive analysis of tumors versus normal adjacent tissues, revealing kinases driving tumor progression...
Currently, signature-based malware scanning is still the dominant approach to identify samples in wild due its low false positive rate. However, this concentrates on programs' specific instructions, and lacks insight into high level semantics; it enduring challenges from advanced code obfuscation techniques such as polymorphism metamorphism. To overcome shortcoming, paper extracts a program's function-call graph signature. The presents method compute similarity between two binaries basis of...
Malware is an increasingly important problem that threatens the security of computer systems. The new concept cloud require rapid and automated detection classification malicious software. In this paper,we propose a behavior-based method. Depends on behavioral analysis we characterize malware profile in trace report. This report contains status change caused by executable event which are transfered from corresponding Win32 API calls their certain parameters, extract behaviour unit strings as...
Modern adaptive image steganography with minimizing a distortion function has high performance of undetectability. However, when an hidden information is attacked by JPEG compression, its robustness cannot be guaranteed, that remarkably limits extension from the lab to real world. In this paper, novel steganographic algorithm proposed robust compression. First, using sign DCT coefficients, remains unchangeable before and after we select candidate coefficients for resisting Second, designed...
In this paper, a novel distributed algorithm derived from the event-triggered strategy is proposed for achieving resilient consensus of multi-agent networks (MANs) under deception attacks. These malicious attacks are intended to interfere with communication channel causing periods in time at which sending information among nodes modified. particular, we develop an update rule can mitigate influence attackers and same reduce computing consumption. Each node chooses instances its state by...