Rongxing Lu

• PhD (Waterloo'12, SJTU'06)
• Professor (Full) at University of New Brunswick

Sparse inner product (SIP) has the attractive property of overhead being dominated by the intersection of inputs between parties, independent of the actual input size. It has intriguing prospects, especially for boosting machine learning on large-scale data, which are tangled with sparse data. In this paper, we investigate privacy-preserving SIP pr...

In the modern digital landscape, integrating geographic locations and textual descriptions within a geo-textual dataset enhances location-based services (LBS) via spatial keyword queries, as these queries combine spatial and textual information to deliver more precise and personalized results. Additionally, the advent of cloud computing allows data...

Local differential privacy (LDP) provides lightweight and provable privacy protection and has wide applications in private data collection. Key-value data, as a popular NoSQL structure, requires simultaneous frequency and mean estimations of each key, which poses a challenge to traditional LDP-based collection methods. Despite many schemes proposed...

In vehicular digital twin networks (VDTNs), digital twin (DT) can assist the vehicle in data handling and report traffic data to the management server, thereby providing enhanced and scalable services for intelligent transport systems. However, the reported data may suffer from forgery and eavesdropping attacks due to the transmission on the open c...

As the Internet of Things (IoT) landscape expands, new devices with various functionalities are continuously being integrated into the IoT ecosystem. When traditional systems, which involve human interaction, are replaced by devices, it becomes crucial to upgrade the conventional authorization and authentication systems. This is essential to establ...

The flourishing of intelligent connected vehicles (ICVs) has fostered the emergence of vehicular crowdsourcing (VCS) applications, in which ICVs function as workers to execute diverse spatio-temporal critical tasks. As a vital service of VCS, task scheduling aims to assign tasks to the most suitable workers. To cope with the escalation of service s...

As one of the most popular queries in big data era, the $k$ nearest neighbors ( $k$ NN) query plays a significant role in various applications, such as medical diagnosis, signal processing, and recommendation systems. Meanwhile, driven by the advancement of the cloud service, an emerging trend among applications is to outsource the dataset and t...

Vehicular social networks (VSNs), as the convergence of social networks and vehicular ad hoc networks, have brought many useful services to vehicle communication by collecting and sharing data between vehicles. In order to efficiently share data and satisfy the growing requirement of privacy protection, data owners typically encrypt and outsource t...

While online medical diagnosis provides significant convenience to users, it also incurs the risk of privacy breaches, which inspired the emergence of various privacy-preserving online medical schemes. Nonetheless, existing schemes either compromise partial privacy to third parties or rely on cryptographic methods with high computational complexity...

In this paper, we propose a privacy-preserving range-based positioning scheme, named PPRP, which can preserve the location privacy of both user equipment (UE) and anchors (ACs) in mobile networks. Specifically, PPRP is established on a decentralized trust-based framework that divides trust between two location management function (LMF) servers. Wit...

The ever-growing data scale and increasingly strict privacy restraint have recently drawn extensive attention to federated learning (FL) as a multi-party machine learning paradigm for achieving high-quality model construction without data collection. Nevertheless, uploading local models in FL can still be exploited by adversaries to infer participa...

The proliferation of intelligent connected vehicles (ICVs) has catalyzed the emergence of vehicular crowdsensing (VCS) applications, wherein sensing tasks are assigned to ICVs with abundant sensing resources and high mobility. To select workers whose future trajectories have sufficient spatio-temporal similarity with the target sensing area, worker...

The rapid development of blockchain technology has led to a constant increase in its financial and technological value. However, this has also led to malicious attacks. Distributed denial-of-service attacks pose a considerable threat to blockchain technology out of many attacks due to its effectiveness and distributed nature. To protect the blockch...

Recently, deep learning-based Image-to-Image (I2I) networks have become the predominant choice for I2I tasks such as image super-resolution and denoising. Despite their remarkable performance, the backdoor vulnerability of I2I networks has not been explored. To fill this research gap, we conduct a comprehensive investigation on the susceptibility o...

Geographic information system (GIS) enables operations for capturing, manipulating, analyzing, and displaying the spatial characteristics of objects on Earth's surface. As the objects in GISs are mostly location-dependent, various location privacy-preserving schemes are proposed to support the secure spatial query and analysis. However, existing lo...

Crowdsourcing, which is regarded as one of the most important data collection techniques in Internet of Things (IoT) and Big Data era, has received significant attention in recent years. However, privacy concerns persist across various crowdsourcing scenarios. In this article, aiming to address users’ privacy issues in crowdsourcing scenarios, we p...

The conflict between data privacy and sharing among healthcare institutions creates data silos, causing wasteful duplication, incomplete information, and potential hindrances to scientific research. In this paper, we present a privacy-preserving medical data sharing scheme based on cloud-assisted private set intersection (PSI) and aggregate signatu...

Privacy preservation in federated learning (FL) has received considerable attention and many approaches have been proposed. However, these approaches rendered the uploaded gradients invisible to the server, which poses a significant challenge in defending against poisoning attacks. In poisoning attacks, malicious or compromised participants use poi...

Set similarity query is a fundamental query type in various applications, such as clinical diagnosis, online shopping, and mobile crowdsensing. Meanwhile, as the prevalence of outsourced query services, privacy-preserving set similarity query has been considerablely studied. However, to the best of our knowledge, most previously reported solutions...

Federated learning (FL) is a distributed machine learning technique that guarantees the privacy of user data. However, FL has been shown to be vulnerable to gradient leakage attacks (GLA), which have the ability to reconstruct private training data from public gradients with high probability. These attacks are either analytic-based, requiring modif...

The increasing prevalence of cloud computing drives the exploration of various secure query schemes over encrypted data, among which secure spatial keyword query has drawn a great deal of attention due to its broad application in location-based services. However, most existing schemes are either limited to the boolean keyword test or incapable of p...

Spatial crowdsourcing is a distributed computing paradigm that utilizes the collective intelligence of workers to perform complex tasks. How to achieve privacy-preserving task assignment in spatial crowdsourcing applications has been a popular research area. However, most of the existing task assignment schemes may reveal private and sensitive info...

Weighted set sampling has been proven essential for generating discrete numbers based on their weights and found broad applications in recommendation systems. The extension of this method, known as weighted range set sampling (WRSS), specifies a query range and applies weighted set sampling to the data within that range. With the proliferation of c...

Outsourcing big data to cloud servers has gained prominence, and growing concerns about privacy, alongside privacy-related regulations, underscore the need to encrypt data before sending them to the cloud. Nevertheless, encryption significantly hampers the query capabilities of data, particularly in the case of vertically distributed data. This pap...

The cloud-edge computing model has been expected to play a revolutionary role in promoting the quality of future generation large-scale Internet of Things (IoT) services. However, security and privacy in data sharing remain crucial issues hindering the success of cloud-edge IoT services. While some solutions based on attribute-based encryption (ABE...

Fueled by its successful commercialization, the recommender system (RS) has gained widespread attention. However, as the training data fed into the RS models are often highly sensitive, it ultimately leads to severe privacy concerns, especially when data are shared among different platforms. In this paper, we follow the tune of existing works to in...

As the Internet of Things (IoT) landscape continues to expand, a diverse range of devices with various functionalities is being integrated into the IoT ecosystem. When traditional systems, which involve human interaction, are replaced by devices, it becomes crucial to upgrade the conventional authorization and authentication mechanisms. Traditional...

The DNS privacy protection mechanisms, DNS over TLS (DoT) and DNS over HTTPS (DoH), only work correctly if both the server and client support the Strict Privacy profile and no vulnerability exists in the implemented TLS/HTTPS. A natural question then arises: what is the landscape of DNS Strict Privacy? To this end, we provide the first longitudinal...

Autonomous vehicle platoons are emerging as a promising solution to modern urban governance challenges, such as traffic congestion, air pollution, and fuel waste. As a data-driven paradigm, ensuring secure data sharing is a key challenge for autonomous vehicle platoon applications. However, existing research on secure data sharing of autonomous veh...

Considerable attention has been paid to dynamic searchable symmetric encryption (DSSE) which allows users to search on dynamically updated encrypted databases. To improve the performance of real-world applications, recent non-interactive multi-client DSSE schemes are targeted at avoiding per-query interaction between data owners and data users. How...

Mobile crowdsensing has empowered the Industrial Internet of Things (IIoT) in many ways, such as vehicle-aided traffic flow scheduling and drone-aided visual inspections, etc. However, dynamic perception and cooperative decision-making among these heterogeneous and resource-constrained mobile clients in IIoT remains a big challenge. In this paper,...

With the explosive growth of data volume and computing capability, federated learning, which involves constructing global models over multiple data islands, has demonstrated its advantages and vast prospects in the field of machine learning. However, due to commonly vertically partitioned data, coupled with privacy concerns about data leakage, ther...

In medical cloud computing, more medical data owners are preferred to outsource their sensitive data to the cloud after encryption. Meanwhile, dynamic searchable symmetric encryption (DSSE) provides the capability for data users to query over the dynamically-updated encrypted database. To reduce update leakage, a secure DSSE scheme usually requires...

The Internet of Things (IoT) boom has enabled Internet Service Providers (ISPs) to collect an enormous amount of high-dimensional data. Performing range queries on such data can effectively reuse them to help ISPs offer better services. Owing to the low cost and high resource utilization of cloud computing, an increasing number of ISPs are inclined...

Secure queries are fundamental to data security, particularly in cloud databases. In data analytics, one of the common and practical queries is the iceberg query that can find aggregate values above a specified threshold. However, existing secure aggregate query schemes: i) are unable to support secure iceberg queries equipped with the HAVING claus...

The optimal location selection is one type of the location-based services (LBS) that aims to find the best location for a new facility from some candidate facilities given a set of existing facilities and a set of customers. Due to reliable and flexible cloud services, outsourcing such heavy-computation tasks has been a popular trend. However, sinc...

With the application of the Internet of Things (IoT) and cloud computing, the eHealthcare industry has developed markedly, attracting many patients to seek medical treatment in an eHealthcare system. However, for patients who first register in the system, due to lack of experience, an important aspect is to choose appropriate medical services. Cons...

Nowadays, the Internet of Things (IoT) concept plays a pivotal role in society and brings new capabilities to different industries. The number of IoT solutions in areas such as transportation and healthcare is increasing and new services are under development. In the last decade, society has experienced a drastic increase in IoT connections. In fac...

During the past decade, the Internet of Things (IoT) has paved the way for the ongoing digitization of society in unique ways. Its penetration into enterprise and day-to-day lives improved the supply chain in numerous ways. Unfortunately, the profuse diversity of IoT devices has become an attractive target for malware authors who take advantage of...

Nowadays, the Internet of Things (IoT) concept plays a pivotal role in society and brings new capabilities to different industries. The number IoT solutions in areas such as transportation and healthcare is increasing and new services are under development. In the last decade, society has experienced a drastic increase in IoT connections. In fact,...

In recent years, the vehicular ad hoc network (VANET), recognized as the fundamental infrastructure of the intelligent transportation system (ITS), has played an increasingly momentous role in advancing real-time vehicular communications. With the purpose of achieving seamless and reliable connectivity, lots of research efforts have been witnessed....

Webmail, protected by the HTTPS protocol, only works correctly if both the server and client implement HTTPS-related features without vulnerability. Nevertheless, the deployment situation of these features in the webmail world is still unclear. To this end, we perform the first end-to-end and large-scale measurement of webmail service. For the serv...

As a promising service, Machine Learning as a Service (MLaaS) provides personalized inference functions for clients through paid APIs. Nevertheless, it is vulnerable to model extraction attacks, in which an attacker can extract a functionally-equivalent model by repeatedly querying the APIs with crafted samples. While numerous works have been propo...

The boom of cloud computing has stimulated the prevalence of outsourced query services, and privacy concerns further motivate extensive studies on privacy-preserving queries in the cloud. Graph similarity query is one critical query type, in which the similarity between two graphs is usually measured by graph edit distance (GED). Although many sche...

Payment Channel Networks (PCNs) have flourished as one of the most promising solutions to the blockchain scalability problem. Unfortunately, the existing PCN solutions either fail to provide path privacy guarantees or require the not-always-true All-Anonymous-Connected assumption (i.e., an anonymous communication channel always exists for any two p...

With the emergence of countless independent blockchain systems in recent years, cross-chain transactions have attracted considerable attention, and lots of solutions have been put forth by both industry and academia. However, most of the existing solutions suffer from either centralization or scalability issues. To mitigate these issues, in this pa...

Location-based services (LBSs) provide enhanced functionality of mobile applications and convenience for mobile users, which plays a more and more remarkable role in people’s daily life. In LBSs, spatial range query is an essential tool for users to find interesting points in a specific region. However, during spatial range query, it is necessary f...

The novel sensing paradigm known as crowdsensing leverages ubiquitous smart devices to collect data in Internet of Things (IoT) applications. Traditional crowdsensing schemes assume a central framework to execute truth discovery algorithm to assure data quality, which may introduce reliability and privacy issues. Blockchain is a promising technolog...

The prevalence of mobile Internet, smart terminal devices, and GPS positioning technology has generated a vast number of trajectory data that location-based applications can utilize. However, delivering LBSs based on trajectories without extra protection may expose the personal information of users and even their social ties. Despite the fact that...

Big data and bursting cloud computing technologies have facilitated an increasing trend of outsourcing data-driven services to the cloud, where the reverse kNN (RkNN) query is a popularly outsourced query service. The RkNN query aims to retrieve objects having the query object as kNN and widely applied in the product recommendation. Considering pri...

The lack of appropriate cyber security measures deployed on IoT makes these devices prone to security issues. Consequently, the timely identification and detection of these compromised devices become crucial. Machine learning (ML) models which are used to monitor devices in a network have made tremendous strides. However, most of the research in pr...

Extensive research has been conducted on efficient and privacy-preserving similarity queries in eHealthcare, aiming at disease diagnosis based on similar patients while protecting the outsourced sensitive healthcare data. In this paper, a new secure similarity query scheme named keyword-oriented multidimensional similarity query (KMSQ) is proposed...

The low Earth orbit (LEO) satellite edge computing paradigm provides remote sites with flexible, reliable, and scalable edge computing capabilities. Characterized by the orbital motion patterns and harsh space environments, the LEO satellite edge computing faces unique security challenges in terms of the secure collaboration of multiple satellites...

Vehicular crowdsensing (VCS) has emerged as a promising paradigm, in which spatio-temporal-based sensing tasks are outsourced to intelligent connected vehicles (ICVs) carrying sensor-equipped devices. A critical issue of VCS is to guarantee the spatio-temporal sensing coverage by assigning tasks to appropriate vehicles, which inevitably requires ve...

Digital Twin (DT) technology, by performing simulation, analysis, and prediction over the data mapped to digital space, can create a digital replica of the physical object. It can be combined with edge computing or cloud computing to provide broad vehicle-to-everything applications and improve the service quality of vehicular ad-hoc networks (VANET...

With the intensification of mobile devices, vast amounts of spatial data have been outsourced to cloud servers to provide query services. However, existing privacy-preserving schemes for spatial data only support spatial range queries and keyword searches, and do not scale well in the scenario of multidimensional range queries. To address the above...

Low Earth orbit (LEO) satellite constellations support intelligent driving applications in areas without terrestrial network coverage. As the LEO-satellite integrated vehicular network experiences dual mobility of satellites and vehicles, the mainstream IP-based mobility management protocols may not adapt to the dynamic network topology and violate...

As a practical machine learning method, the K-nearest neighbors (KNN) classification has received widespread attention. The achievement of the KNN classification relies heavily on a large amount of labeled data. However, in the real world, data is often held by different data owners. How to realize efficient joint computing among multiple data owne...

Graph data structures' ability of representing vertex relationships has made them increasingly popular in recent years. Amid this trend, many property graph datasets have been collected and made public to facilitate a variant of queries such as the aggregate queries that will be extensively exploited in this paper. While cloud deployment of both th...

Considerable attention has been paid to dynamic searchable symmetric encryption (DSSE) which allows users to search on dynamically updated encrypted databases. To improve the performance of real-world applications, recent non-interactive multi-client DSSE schemes are targeted at avoiding per-query interaction between data owners and data users. How...