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Article
Computer Science, Information Systems
Yongxin Liu et al.
Summary: The Internet of Things (IoT) has become an essential part of everyday life, but the presence of rogue devices poses significant risks. This article explores noncryptographic approaches and machine learning technologies for identifying and detecting compromised IoT devices, providing a comprehensive survey and classification of different methods.
IEEE INTERNET OF THINGS JOURNAL
(2022)
Article
Computer Science, Information Systems
Shuodi Hui et al.
Summary: This article successfully distinguishes Internet of Things (IoT) devices from smartphones by characterizing their network traffic. The study reveals the network traffic behavior characteristics for IoT devices and provides a foundation for better network design, resource allocation, pricing scheme, and security defense mechanisms.
IEEE INTERNET OF THINGS JOURNAL
(2022)
Article
Computer Science, Information Systems
Kapal Dev et al.
Summary: This article proposes a device detection and identification architecture for joint active user detection (AUD) and IoT device identification. The architecture improves the detection and identification process by extracting Fourier patterns as the representative feature vector. Experimental results demonstrate that this architecture outperforms conventional schemes and deep neural network-based approaches in terms of success probability for the AUD task, while also having lower computational complexity.
IEEE INTERNET OF THINGS JOURNAL
(2022)
Article
Computer Science, Artificial Intelligence
Wenguan Wang et al.
Summary: This paper provides a comprehensive survey on deep salient object detection (SOD), covering algorithm taxonomy, unsolved issues, and dataset evaluation. The research shows that deep learning algorithms have made significant progress in SOD, and investigates the performance under different attribute settings, the robustness to random input perturbations and adversarial attacks, and the generalization of existing datasets.
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
(2022)
Article
Computer Science, Information Systems
Tong Jian et al.
Summary: The study successfully conducts radio frequency fingerprinting tasks on edge devices, achieving significant performance improvements through structured pruning.
IEEE TRANSACTIONS ON MOBILE COMPUTING
(2022)
Article
Computer Science, Information Systems
Ali Dorri et al.
Summary: This article explores the impact of user deanonymization on IoT-based blockchain and demonstrates that machine learning algorithms can successfully classify transactions. To enhance user anonymity, the article proposes multiple obfuscation methods.
IEEE INTERNET OF THINGS JOURNAL
(2022)
Article
Computer Science, Information Systems
Batyr Charyyev et al.
Summary: Engineered systems are becoming smarter thanks to computing capabilities and the increasing number of IoT devices. However, IoT devices are vulnerable to compromise due to their limited resources, making them prime targets for malicious activities. This article introduces a novel approach using locality-sensitive hash to identify IoT devices based on their traffic flow, achieving high precision and recall without the need for feature extraction or model retraining. The evaluation results demonstrate that this approach performs on par with state-of-the-art machine learning-based methods.
IEEE INTERNET OF THINGS JOURNAL
(2021)
Review
Computer Science, Theory & Methods
Guansong Pang et al.
Summary: Deep anomaly detection has emerged as a critical direction in the research field of anomaly detection, covering advancements in multiple categories of methods. Reviewing them can help us understand their advantages, disadvantages, and how they address challenges.
ACM COMPUTING SURVEYS
(2021)
Proceedings Paper
Computer Science, Information Systems
Yilin Zhao et al.
Summary: With the addition of more external interfaces in intelligent and connected vehicles, the in-vehicle network is no longer a closed environment, making it vulnerable to attacks. To counter this, a vehicle IDS system like VehicleCIDS, based on clock behavior, is proposed for intrusion detection and attacker identification, showing high recognition rates in real vehicle experiments.
2021 IEEE GLOBAL COMMUNICATIONS CONFERENCE (GLOBECOM)
(2021)
Proceedings Paper
Engineering, Electrical & Electronic
P. M. Lavanya et al.
Summary: The study focuses on investigating the application of deep learning techniques in social media healthcare networks, aiming to enhance the performance of the text classifier by training and analyzing the data.
ICSPC'21: 2021 3RD INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING AND COMMUNICATION (ICPSC)
(2021)
Article
Computer Science, Information Systems
Yong Luo et al.
IEEE INTERNET OF THINGS JOURNAL
(2020)
Article
Computer Science, Information Systems
Arunan Sivanathan et al.
IEEE TRANSACTIONS ON NETWORK AND SERVICE MANAGEMENT
(2020)
Article
Computer Science, Hardware & Architecture
Ian Goodfellow et al.
COMMUNICATIONS OF THE ACM
(2020)
Article
Computer Science, Information Systems
Arunan Sivanathan et al.
IEEE TRANSACTIONS ON MOBILE COMPUTING
(2019)
Article
Engineering, Electrical & Electronic
Samuel Marchal et al.
IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS
(2019)
Article
Computer Science, Hardware & Architecture
Constantinos Kolias et al.
Article
Computer Science, Hardware & Architecture
Alberto Dainotti et al.