A5101925343- Network Security and Intrusion Detection
- Internet Traffic Analysis and Secure E-voting
- Advanced Malware Detection Techniques
- Smart Grid Security and Resilience
- Quantum Information and Cryptography
- Cloud Computing and Resource Management
- Quantum Mechanics and Applications
- Cold Atom Physics and Bose-Einstein Condensates
- Software-Defined Networks and 5G
- Security in Wireless Sensor Networks
- Interconnection Networks and Systems
- Anomaly Detection Techniques and Applications
- Adversarial Robustness in Machine Learning
- Security and Verification in Computing
- Tribology and Lubrication Engineering
- Advanced Data Processing Techniques
- Access Control and Trust
- Diamond and Carbon-based Materials Research
- Electricity Theft Detection Techniques
- Advanced Authentication Protocols Security
- Iterative Learning Control Systems
- Molecular Communication and Nanonetworks
- Gear and Bearing Dynamics Analysis
- Sparse and Compressive Sensing Techniques
- Spectroscopy and Quantum Chemical Studies
Xi'an Jiaotong University
2025
Shanghai University
2010-2023
Jinan University
2022-2023
Guizhou University
2022
Nanyang Technological University
2015
Queen's University Belfast
1995-2005
École Nationale des Greffes
1992
Watchdog technique is a fundamental building block to many trust systems that are designed for securing wireless sensor networks (WSNs). Unfortunately, this kind of consumes much energy and hence largely limits the lifespan WSN. Although state-of-the-art studies have realized importance systems' efficiency in WSNs proposed several preliminary solutions, they overlooked optimize watchdog technique, which perhaps among top energy-consuming units. In paper, we reveal inefficient use existing...
Abstract The usual definition of squeezing, based on the Heisenberg uncertainty principle, measures in terms standard deviation. It can run into difficulties when applied to squeezing two-level atom. An alternative is presented for this system, information entropy theory, which overcomes disadvantages relation. utility illustrated by examining a atom Jaynes-Cummings model, and resonance fluorescence.
Power systems usually employ bad data detection (BDD) to avoid faulty measurements caused by their anomalies, and hence can ensure the security of state estimation power systems. However, recently BDD has been found vulnerable malicious deception attacks submerged in big data. Such purposely craft sparse measurement values (i.e. attack vectors) mislead estimates, while not posing any anomalies BDD. Some related work proposed emphasize this attack. In paper, a new considering practical...
Payload-based anomaly detection (PAD) model is commonly built upon a big data of normal payload samples, and hence able to discover zero-day attacks unknown faults without the need any negative samples in training phase. But such encounters new challenges adapt well emerging Industrial Internet Things (IIoT). That is, modern industrial processes are usually running very high complexity, resulting payloads much more complex diverse. Further, likely too sensitive be shared public, thus induces...
Abstract The general time evolution of operators in the multiphoton Jaynes-Cummings model without rotating-wave approximation is obtained. contributions counter-rotating terms to atomic dynamics and field squeezing are examined processes.
Bandwidth measurement is important for many network applications and services, such as peer-to-peer networks, video caching anonymity services. To win a bandwidth-based competition some malicious purpose, adversarial Internet hosts may falsely announce larger bandwidth. Some preliminary solutions have been proposed to this problem. They can either evade the bandwidth inflation by consensus view (i.e., opportunistic measurements) or detect frauds via forgeable tricks detection through...
Payload classification is a kind of powerful deep packet inspection model built on the raw payloads network traffic, and hence can remove need any configuration assumptions for management intrusion detection. While in emerging industrial Internet, majority local industry owners are not willing to share their private that possibly contain sensitive information thus cause always well trained due lack sufficient training samples. In this paper, we address privacy concern propose federated...
Payload-based anomaly detection has been proved effective in discovering Internet misbehavior and potential intrusions, but highly relies on the unstructured feature engineering to generalize distribution of normal payloads. This kind generalization may not adapt well emerging industrial Internet, where behaviors are more diverse usually embedded raw payloads' local structures. In this paper, we tackle problem propose a very different solution payload-based without need engineering. Our...
A novel method, aiming at solving the problem that ultra-high-speed electric spindle tends to vibrate as its stiffness is small, using repulsion of permanent magnets based on theory increased while two come close, provided in this paper design a within additional support bearing system consist radial magnet rings against each other. This also analyses dynamic performance bearings supporting for ultra-high speed rotor system, result shows magnetic designed improving critical reducing...