Kaiqi Xiong
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View article: Non-Markovian two-time correlation functions for optomechanical systems
Non-Markovian two-time correlation functions for optomechanical systems Open
In this paper, we focus on the two-time correlation function (TTCF) of the cavity optomechanical system, which serves as the most popular tool in precision detection technologies. We utilize the stochastic Schrodinger equation approach to …
View article: Blockchain-Based Security Architecture for Uncrewed Aerial Systems in B5G/6G Services and Beyond: A Comprehensive Approach
Blockchain-Based Security Architecture for Uncrewed Aerial Systems in B5G/6G Services and Beyond: A Comprehensive Approach Open
Uncrewed aerial systems (UASs) were popularly used by hobbyists in the past, but they have now become critical enablers for managing disasters, handling emergencies, and so on. For example, one of their most critical applications is to pro…
View article: Exploring Feature Importance and Explainability Towards Enhanced ML-Based DoS Detection in AI Systems
Exploring Feature Importance and Explainability Towards Enhanced ML-Based DoS Detection in AI Systems Open
Denial of Service (DoS) attacks pose a significant threat in the realm of AI systems security, causing substantial financial losses and downtime. However, AI systems' high computational demands, dynamic behavior, and data variability make …
View article: Online Network DoS/DDoS Detection: Sampling, Change Point Detection, and Machine Learning Methods
Online Network DoS/DDoS Detection: Sampling, Change Point Detection, and Machine Learning Methods Open
View article: Nonlinear Transformations Against Unlearnable Datasets
Nonlinear Transformations Against Unlearnable Datasets Open
Automated scraping stands out as a common method for collecting data in deep learning models without the authorization of data owners. Recent studies have begun to tackle the privacy concerns associated with this data collection method. No…
View article: Redefining DDoS Attack Detection Using A Dual-Space Prototypical Network-Based Approach
Redefining DDoS Attack Detection Using A Dual-Space Prototypical Network-Based Approach Open
Distributed Denial of Service (DDoS) attacks pose an increasingly substantial cybersecurity threat to organizations across the globe. In this paper, we introduce a new deep learning-based technique for detecting DDoS attacks, a paramount c…
View article: Advancing DDoS Attack Detection: A Synergistic Approach Using Deep Residual Neural Networks and Synthetic Oversampling
Advancing DDoS Attack Detection: A Synergistic Approach Using Deep Residual Neural Networks and Synthetic Oversampling Open
Distributed Denial of Service (DDoS) attacks pose a significant threat to the stability and reliability of online systems. Effective and early detection of such attacks is pivotal for safeguarding the integrity of networks. In this work, w…
View article: Blockchain-Based Security Architecture for Unmanned Aerial Vehicles in B5G/6G Services and Beyond: A Comprehensive Approach
Blockchain-Based Security Architecture for Unmanned Aerial Vehicles in B5G/6G Services and Beyond: A Comprehensive Approach Open
Unmanned Aerial Vehicles (UAVs), previously favored by enthusiasts, have evolved into indispensable tools for effectively managing disasters and responding to emergencies. For example, one of their most critical applications is to provide …
View article: Enhancing ML-Based DoS Attack Detection Through Combinatorial Fusion Analysis
Enhancing ML-Based DoS Attack Detection Through Combinatorial Fusion Analysis Open
Mitigating Denial-of-Service (DoS) attacks is vital for online service security and availability. While machine learning (ML) models are used for DoS attack detection, new strategies are needed to enhance their performance. We suggest an i…
View article: A Decentralized Cooperative Navigation Approach for Visual Homing Networks
A Decentralized Cooperative Navigation Approach for Visual Homing Networks Open
Visual homing is a lightweight approach to visual navigation. Given the stored information of an initial 'home' location, the navigation task back to this location is achieved from any other location by comparing the stored home informatio…
View article: Improving Machine Learning Robustness via Adversarial Training
Improving Machine Learning Robustness via Adversarial Training Open
As Machine Learning (ML) is increasingly used in solving various tasks in real-world applications, it is crucial to ensure that ML algorithms are robust to any potential worst-case noises, adversarial attacks, and highly unusual situations…
View article: High-quality development of virtual reality industry from the perspective of environmental regulation
High-quality development of virtual reality industry from the perspective of environmental regulation Open
From the perspective of environmental regulation, this paper constructed a high-quality development evaluation system for the virtual reality industry (hereinafter referred to as VRI), calculated the high-quality development level of the V…
View article: Factors influencing innovation performance of China’s high-end manufacturing clusters: Dual-perspective from the digital economy and the innovation networks
Factors influencing innovation performance of China’s high-end manufacturing clusters: Dual-perspective from the digital economy and the innovation networks Open
In the era of digital economy, the impact of innovation resources on high-quality economic growth has become increasingly prominent. There are many researches on the influencing factors of innovation performance. The purpose of this study …
View article: Blockchain in Financial Services: Current Status, Adaptation Challenges, and Future Vision
Blockchain in Financial Services: Current Status, Adaptation Challenges, and Future Vision Open
Blockchain is undoubtedly considered one of the most innovative technologies in financial services from the past decade. Interests in blockchain technology continue to grow on a daily basis, while many promising blockchain-enabled applicat…
View article: Secure machine learning against adversarial samples at test time
Secure machine learning against adversarial samples at test time Open
View article: SDN Security Review: Threat Taxonomy, Implications, and Open Challenges
SDN Security Review: Threat Taxonomy, Implications, and Open Challenges Open
Software-Defined networking (SDN) is a networking paradigm to enable dynamic, flexible, and programmatically efficient configuration of networks to revolutionize network control and management via separation of the control plane and data p…
View article: ML Attack Models: Adversarial Attacks and Data Poisoning Attacks
ML Attack Models: Adversarial Attacks and Data Poisoning Attacks Open
Many state-of-the-art ML models have outperformed humans in various tasks such as image classification. With such outstanding performance, ML models are widely used today. However, the existence of adversarial attacks and data poisoning at…
View article: Leveraging a cloud‐based testbed and software‐defined networking for cybersecurity and networking education
Leveraging a cloud‐based testbed and software‐defined networking for cybersecurity and networking education Open
Nowadays, real‐world learning modules become vital components in computer science and engineering in general and cybersecurity in particular. However, as student enrollments have been dramatically increasing, it becomes more challenging fo…
View article: Mahalanobis distance-based robust approaches against false data injection attacks on dynamic power state estimation
Mahalanobis distance-based robust approaches against false data injection attacks on dynamic power state estimation Open
View article: Applying the Mahalanobis Distance to Develop Robust Approaches Against False Data Injection Attacks on Dynamic Power State Estimation.
Applying the Mahalanobis Distance to Develop Robust Approaches Against False Data Injection Attacks on Dynamic Power State Estimation. Open
Although many researchers have studied false data injection (FDI) attacks in power state estimation, current state estimation approaches are still highly vulnerable to FDI attacks. In this paper, we investigate the problem of the above thr…
View article: Author response for "Leveraging a cloud‐based testbed and software‐defined networking for cybersecurity and networking education"
Author response for "Leveraging a cloud‐based testbed and software‐defined networking for cybersecurity and networking education" Open
View article: SYNGuard: Dynamic threshold‐based SYN flood attack detection and mitigation in software‐defined networks
SYNGuard: Dynamic threshold‐based SYN flood attack detection and mitigation in software‐defined networks Open
SYN flood attacks (half‐open attacks) have been proven a serious threat to software‐defined networking (SDN)‐enabled infrastructures. A variety of intrusion detection and prevention systems (IDPS) have been introduced for identifying and p…
View article: Active Learning Under Malicious Mislabeling and Poisoning Attacks
Active Learning Under Malicious Mislabeling and Poisoning Attacks Open
Deep neural networks usually require large labeled datasets for training to achieve state-of-the-art performance in many tasks, such as image classification and natural language processing. Although a lot of data is created each day by act…
View article: Secure Software-Defined Networking Communication Systems for Smart Cities: Current Status, Challenges, and Trends
Secure Software-Defined Networking Communication Systems for Smart Cities: Current Status, Challenges, and Trends Open
Smart city is a transformative and progressive vision that aims to revolutionize infrastructure systems and public services in an urban area with modern information technologies. Its ultimate goal is to greatly improve the livability Quali…
View article: An Adversarial Attack Defending System for Securing In-Vehicle Networks
An Adversarial Attack Defending System for Securing In-Vehicle Networks Open
In a modern vehicle, there are over seventy Electronics Control Units (ECUs). For an in-vehicle network, ECUs communicate with each other by following a standard communication protocol, such as Controller Area Network (CAN). However, an at…
View article: A Survey on Security Attacks and Defense Techniques for Connected and Autonomous Vehicles
A Survey on Security Attacks and Defense Techniques for Connected and Autonomous Vehicles Open
Autonomous Vehicle has been transforming intelligent transportation systems. As telecommunication technology improves, autonomous vehicles are getting connected to each other and to infrastructures, forming Connected and Autonomous Vehicle…
View article: Deep Learning for Adversarial Attacks in Large Scale Networks (White Paper)
Deep Learning for Adversarial Attacks in Large Scale Networks (White Paper) Open
View article: Aggregation Measure Factor-Based Workflow Application Scheduling in Heterogeneous Environments
Aggregation Measure Factor-Based Workflow Application Scheduling in Heterogeneous Environments Open
With the development of heterogeneous distributed computing environment, workflow application scheduling has become an important and challenging problem while Quality of Service (QoS) guarantees are ensured for science workflows. In this p…
View article: Deep Learning for Adversarial Attacks in Large Scale Networks (Presentation)
Deep Learning for Adversarial Attacks in Large Scale Networks (Presentation) Open
View article: Applying Machine Learning Techniques to Understand User Behaviors When Phishing Attacks Occur
Applying Machine Learning Techniques to Understand User Behaviors When Phishing Attacks Occur Open
Emails have been widely used in our daily life. It is important to understand user behaviors regardingemail security situation assessments. However, there are very challenging and limited studies on email userbehaviors. To study user secur…