Jiming Chen

Jiming Chen
University of Electronic Science and Technology of China | UESTC · Communication and information system

PhD

About

442
Publications
94,925
Reads
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15,687
Citations
Citations since 2016
166 Research Items
12093 Citations
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Introduction
Skills and Expertise

Publications

Publications (442)
Preprint
Differentiable architecture search (DARTS) has been a mainstream direction in automatic machine learning. Since the discovery that original DARTS will inevitably converge to poor architectures, recent works alleviate this by either designing rule-based architecture selection techniques or incorporating complex regularization techniques, abandoning...
Article
Full-text available
Digital contact tracing has been recently advocated by China and many countries as part of digital prevention measures on COVID-19. Controversies have been raised about their effectiveness in practice as it remains open how they can be fully utilized to control COVID-19. In this article, we show that an abundance of information can be extracted fro...
Article
Recent years have witnessed the fast proliferation of camera sensors networks (CSNs) in numerous Internet of Things (IoT) applications. In order to a capture distinct image of targets from interesting directions, we leverage a special type of coverage called full-view coverage. Full-view coverage guarantees to obtain the images of a point from ever...
Preprint
3D human reconstruction from RGB images achieves decent results in good weather conditions but degrades dramatically in rough weather. Complementary, mmWave radars have been employed to reconstruct 3D human joints and meshes in rough weather. However, combining RGB and mmWave signals for robust all-weather 3D human reconstruction is still an open c...
Preprint
Publishing trajectory data (individual's movement information) is very useful, but it also raises privacy concerns. To handle the privacy concern, in this paper, we apply differential privacy, the standard technique for data privacy, together with Markov chain model, to generate synthetic trajectories. We notice that existing studies all use Markov...
Article
Full-text available
近年来,我国积极参与全球气候治理进程,战略性地提出了2030 年“碳达峰”与2060 年“碳中和”这一具有紧迫性与挑战性的目标。碳排放的精准、快速与可靠监测是实现碳排放态势感知、整体布局优化的核心基础,目前该方向的研究仍缺乏系统性梳理。首先,调研了碳排放监测的发展进程,归纳了国内外的现行标准。然后,分别探究了基于终端设备与基于物联网的碳排放监测方法,总结出基于物联网的监测方法具有结构清晰、设 计灵活、传输可靠等优势。最后,基于“云−管−边−端”物联网架构提出一种工业碳排放监测体系,并总结了实现“云−管−边−端”4 个方面的潜在关键技术,旨在对未来碳排放监测相关研究提供一定参考。
Conference Paper
Full-text available
Backboned by smart meter networks, Advanced Metering Infrastructures (AMIs) play a critical role in smart grids. This paper studies a new False Data Injection Attack (FDIA) scenario targeting AMIs, in which the attacker injects and propagates computer worms (i.e., false data codes) to maliciously increase the readings of networked smart meters and...
Preprint
Multivariate time series anomaly detection has been extensively studied under the semi-supervised setting, where a training dataset with all normal instances is required. However, preparing such a dataset is very laborious since each single data instance should be fully guaranteed to be normal. It is, therefore, desired to explore multivariate time...
Article
Full-text available
An excellent method for predicting links in multiplex networks is reflected in its ability to reconstruct them accurately. Although link prediction methods perform well on estimating the existence probability of each potential link in monoplex networks by the set of partially observed links, we lack a mathematical tool to reconstruct the multiplex...
Article
Programmable logic controllers (PLCs), i.e., the core of control systems, are well-known to be vulnerable to a variety of cyber attacks. To mitigate this issue, we design PLC-Sleuth , a novel noninvasive intrusion detection/localization system for PLCs, which is built on a set of control invariants—i.e., the correlations between sensor readings a...
Article
Persistent packet loss in the cloud-scale overlay network severely compromises tenant experiences. Cloud providers are keen to diagnose such problems efficiently. However, existing work is either designed for the physical network or insufficient to present the concrete reason of packet loss. We propose to record and analyze the on-site forwarding c...
Preprint
In an asynchronous federated learning framework, the server updates the global model once it receives an update from a client instead of waiting for all the updates to arrive as in the synchronous setting. This allows heterogeneous devices with varied computing power to train the local models without pausing, thereby speeding up the training proces...
Preprint
Full-text available
Federated learning (FL) is a collaborative learning paradigm where participants jointly train a powerful model without sharing their private data. One desirable property for FL is the implementation of the right to be forgotten (RTBF), i.e., a leaving participant has the right to request to delete its private data from the global model. However, un...
Article
Full-text available
Understanding how human mobility pattern changes during the COVID-19 is of great importance in controlling the transmission of the pandemic. This pattern seems unpredictable due to the complex social contexts, individual behaviors, and limited data. We analyze the human mobility data of over 10 million smart devices in three major cities in China f...
Article
Full-text available
In this paper, we consider a hierarchical control based DC microgrid (DCmG) equipped with unknown input observer (UIO) based detectors, where the potential false data injection (FDI) attacks and the distributed countermeasure are investigated. First, we find that the vulnerability of the UIO-based detector originates from the lack of knowledge of t...
Preprint
We consider the range-based localization problem, which involves estimating an object's position by using $m$ sensors, hoping that as the number $m$ of sensors increases, the estimate converges to the true position with the minimum variance. We show that under some conditions on the sensor deployment and measurement noises, the LS estimator is stro...
Article
Understanding how human mobility pattern changes during the COVID-19 is of great importance in controlling the transmission of the pandemic. This pattern seems unpredictable due to the complex social contexts, individual behaviors, and limited data. We analyze the human mobility data of over 10 million smart devices in three major cities in China f...
Preprint
Full-text available
Semantic-oriented communication has been considered as a promising to boost the bandwidth efficiency by only transmitting the semantics of the data. In this paper, we propose a multi-level semantic aware communication system for wireless image transmission, named MLSC-image, which is based on the deep learning techniques and trained in an end to en...
Article
We consider the range-based localization problem, which involves estimating an object's position by using $m$ sensors, hoping that as the number $m$ of sensors increases, the estimate converges to the true position with the minimum variance. We show that under some conditions on the sensor deployment and measurement noises, the LS estimator is stro...
Article
In response to the repeated outbreaks of the COVID-19, many countries implement the region-specific, multilevel epidemic prevention and control policies. To fully understand the impact of these interventions on urban mobility, it is urgent to analyze spatial–temporal mobility pattern at the neighborhood level and structural changes in urban mobilit...
Article
Time-Sensitive Networking (TSN), an emerging network technology, requires high-performance scheduling mechanisms to deliver deterministic service in Industry 5.0. Cyclic Queuing and Forwarding (CQF) is launched to simplify the configuration complexity of the early-stage mechanism Time-Aware Shaper (TAS) in TSN flow scheduling. Previous CQF studies...
Article
Recently, much attention has been paid to segmenting subtle unknown defect regions by knowledge distillation in an unsupervised setting. Most previous studies concentrated on guiding the student network to learn the same representations on the normality, neglecting the different behaviors of the abnormality. This leads to a high probability of fals...
Article
Effectively predicting the evolution of COVID-19 is of great significance to contain the pandemic. Extensive previous studies proposed a great number of SIR variants, which are efficient to capture the transmission characteristics of COVID-19. However, the parameter estimation methods in previous studies are based on data from epidemiological inves...
Article
Modeling and predicting the radio spectrum is important for spectrum management such as spectrum sharing and anomaly detection. Nevertheless, the precise spectrum prediction is challenging due to the interference from both intra-spectrum and external factors. To tackle these complex internal and external correlations, we develop a model named TF2AN...
Article
Radio map, serving as an efficient indicator of wireless environments, has been widely used in many applications such as network monitoring, anomaly signal detection, and localization. It is hard to maintain an update-to-date fine-grained radio map within a large area since the radio map changes rapidly due to internal and external factors. In this...
Article
Full-text available
Prediction of drug-target interactions (DTI) plays a vital role in drug development in various areas, such as virtual screening, drug repurposing and identification of potential drug side effects. Despite extensive efforts have been invested in perfecting DTI prediction, existing methods still suffer from the high sparsity of DTI datasets and the c...
Article
Full-text available
With the rapid development of information and communications technology in DC microgrids (DCmGs), the deception attacks, which typically include false data injection and replay attacks, have been widely recognized as a significant threat. However, existing literature ignores the possibility of the intelligent attacker, who could launch deception at...
Conference Paper
Full-text available
For protecting users’ private data, local differential privacy (LDP) has been leveraged to provide the privacy-preserving range query, thus supporting further statistical analysis. However, existing LDPbased range query approaches are limited by their properties, i.e., collecting user data according to a pre-defined structure. These static framewor...
Preprint
For protecting users' private data, local differential privacy (LDP) has been leveraged to provide the privacy-preserving range query, thus supporting further statistical analysis. However, existing LDP-based range query approaches are limited by their properties, i.e., collecting user data according to a pre-defined structure. These static framewo...
Preprint
With the increased penetration and proliferation of Internet of Things (IoT) devices, there is a growing trend towards distributing the power of deep learning (DL) across edge devices rather than centralizing it in the cloud. This development enables better privacy preservation, real-time responses, and user-specific models. To deploy deep and comp...
Article
Incentive mechanism design and quality control are two key challenges in data crowdsourcing, because of the need for recruitment of crowd users and their limited capabilities. Without considering users' social influences, existing mechanisms often result in low efficiency in terms of the platform's cost. In this paper, we exploit social influences...
Article
Recently, cloud computing has become a vital part that supports people’s normal lives and production. However, accompanied by the increasing complexity of the cloud network, failures constantly keep coming up and cause huge economic losses. Thus, to guarantee the cloud network performance and prevent execrable effects caused by failures, cloud netw...
Article
Information barrier coverage has been widely adopted to prevent unauthorized invasion of important areas in Internet of Things. As sensors are typically placed outdoors, they are susceptible to getting faulty. Previous works assumed that faulty sensors are easy to recognize, e.g., they may stop functioning or output apparently deviant sensory data....
Article
Detecting small low-contrast targets in the airspace is an essential and challenging task. This article proposes a simple and effective data-driven support vector machine (SVM)-based spatiotemporal feature fusion detection method for small low-contrast targets. We design a novel pixel-level feature, called a spatiotemporal profile, to depict the di...
Article
Nowadays, accurate and real-time vehicle tracking is critical to ensure the safety of intelligent vehicles. However, tracking in the complex traffic environments still remains a challenging issue. In this paper, we present a Road-map Aided Gaussian Mixture Probability Hypothesis Density (RA-GMPHD) filter for multi-vehicle tracking with automotive r...
Preprint
Outlier ensemble methods have shown outstanding performance on the discovery of instances that are significantly different from the majority of the data. However, without the awareness of fairness, their applicability in the ethical scenarios, such as fraud detection and judiciary judgement system, could be degraded. In this paper, we propose to re...
Article
Running at a fast speed, the high-speed train is prone to be interrupted by the surrounding strong wind. To ensure the safety of the trains, an effective approach is to deploy anemometers alongside the railway, such that the real-time and short-term predicted wind speed can be reported, and be further used by dispatchers to take protective actions...
Article
Industrial robots are prototypical cyber-physical systems widely deployed in (smart) manufacturing, which operate according to the operation code uploaded by the human operator and are monitored in real-time based on their movement data. However, industrial robots suffer from replay attacks, via which attackers can manipulate the robot operation wi...
Preprint
Full-text available
Currently, the global situation of COVID-19 is aggravating, pressingly calling for efficient control and prevention measures. Understanding spreading pattern of COVID-19 has been widely recognized as a vital step for implementing non-pharmaceutical measures. Previous studies investigated such an issue in large-scale (e.g., inter-country or inter-st...
Preprint
In differential privacy (DP), a challenging problem is to generate synthetic datasets that efficiently capture the useful information in the private data. The synthetic dataset enables any task to be done without privacy concern and modification to existing algorithms. In this paper, we present PrivSyn, the first automatic synthetic data generation...
Article
Full-text available
Deploying machine learning (ML)-based intrusion detection systems (IDS) is an effective way to improve the security of industrial control systems (ICS). However, ML models themselves are vulnerable to adversarial examples, generated by deliberately adding subtle perturbation to the input sample that some people are not aware of, causing the model t...
Conference Paper
Full-text available
Spatial channel hardening is one of the key properties of a massive MIMO system. In this paper, we investigate the spatial channel hardening based on ray tracing channel simulations with different array antenna topologies deployed in different radio wave propagation conditions. Investigated are 9 different indoor deployment scenarios of massive MIM...
Conference Paper
Programmable Logic Controllers (PLCs) are the ground of control systems, which are however, vulnerable to a variety of cyber attacks, especially for networked control systems. To mitigate this issue, we design PLC-Sleuth, a novel non-invasive intrusion detection/localization system for PLCs, grounding on a set of control invariants — i.e., the corr...
Article
Recently, the security of state estimation has attracted significant research attention due to the need for trustworthy situation awareness in emerging cyber-physical systems. In this paper, we design an encryption-based state estimation (ESE) using partially homomorphi-cally encrypted data. The encryption will enhance the confidentiality not only...
Article
Imagine when you line up in a store, the person in front of you can make you pay her bill by using a passive wearable device that forces a scan of your credit card or mobile phones without your awareness. An important assumption of today’s near-field communication (NFC)-enabled cards is the limited communication range between the commercial reader...
Article
Hybrid LoRa network is a promising approach to overcoming the half-duplex issue in traditional LoRa networks, increasing the network efficiency and confidence for today’s fast-developing smart city services. Gateways (GWs) in hybrid LoRa networks link the end-devices (EDs) and the Netserver, and have great impact on the system performance. Previous...
Article
With the proliferation of training data, distributed machine learning (DML) is becoming more competent for large scale learning tasks. However, privacy concerns have to be given priority in DML, since training data may contain sensitive information of users. In this paper, we propose a privacy-preserving ADMM-based DML framework with two novel feat...
Preprint
Full-text available
Contact tracing APPs have been recently advocated by many countries (e.g., the United Kingdom, Australia, etc.) as part of control measures on COVID-19. Controversies have been raised about their effectiveness in practice as it still remains unclear how they can be fully utilized to fuel the fight against COVID-19. In this article, we show that an...
Preprint
Full-text available
Digital contact tracing has been recently advocated by China and many countries as part of digital prevention measures on COVID-19. Controversies have been raised about their effectiveness in practice as it remains open how they can be fully utilized to control COVID-19. In this article, we show that an abundance of information can be extracted fro...
Article
RF power transfer is becoming a reliable solution to energy supplement of Internet of Things recent years. However, sensor nodes mounted with these platforms can not work and harvest energy simultaneously, due to the low-manufacture-cost requirement. This leads to a new design challenge of scheduling sensor nodes' operation states: working or recha...
Article
Drone has been applied in various areas due to its small size, high mobility and low price. However, illegal use of drones has posed great threats to both public safety and personal privacy. There is an urgent demand for technologies which can timely detect and counter the drones. In this paper, we propose an adaptive switching spatial-temporal fus...
Article
Controllability is a fundamental issue in complex networks. It is still an open issue to optimize the controllability of complex networks based solely on the network structure for a given number of driver nodes. In this paper, we try to address this problem from the perspective of temporal segmentation. With the advantage of temporal network, the c...
Article
As key sensors of the ADAS, mmWave radars have been widely used for fulfilling tasks including adaptive cruise control, lane-changing assistance and collision avoidance. However, the interference generated by mmWave radars mounted on close-by vehicles, if not managed well, could seriously degrade the radars' performance, giving rise to a safety haz...
Article
Full-text available
Recent studies have exploited moving target defense (MTD) for thwarting false data injection (FDI) attacks against the state estimation (SE) by actively perturbing branch parameters (i.e., impedance or admittance) in power grids. To hide the activation of MTD from attackers, a new strategy named hidden MTD has been proposed by the latest literature...