Review
Computer Science, Artificial Intelligence
Bruhadeshwar Bezawada, Indrakshi Ray, Indrajit Ray
Summary: The rapid advancement in the Internet of Things (IoT) domain has led to the development of various useful devices that have enhanced home living and industrial automation. However, the vulnerabilities in IoT devices have made them susceptible to compromise and forgery, raising concerns about device authentication. Behavioral fingerprinting emerges as a promising direction for fingerprinting IoT devices due to their resource constraints and heterogeneity.
WILEY INTERDISCIPLINARY REVIEWS-DATA MINING AND KNOWLEDGE DISCOVERY
(2021)
Article
Chemistry, Analytical
Fartein Lemjan Faeroy, Muhammad Mudassar Yamin, Ankur Shukla, Basel Katt
Summary: The security of IoT devices is a major concern, and we have conducted automated penetration testing to investigate their vulnerabilities. Our study reveals that well-known vulnerabilities still exist in IoT devices.
Article
Computer Science, Information Systems
Ramyapandian Vijayakanthan, Irfan Ahmed, Aisha Ali-Gombe
Summary: The increasing sophistication in computing capability and sensing technologies have led to the development and growth of smart technologies, also known as the IoTs. However, the spread of malware in this ecosystem is a pressing concern. In this paper, a technique called SWMAT is proposed for fingerprinting IoT devices using sound wave signals generated from their dynamic memory traces. The results show that MFCC features can effectively distinguish IoT processes and detect abnormal changes, with a similarity detection accuracy of over 95%.
COMPUTERS & SECURITY
(2023)
Article
Computer Science, Information Systems
Alberto Gutierrez-Torre, Kiyana Bahadori, Shuja-ur-Rehman Baig, Waheed Iqbal, Tullio Vardanega, Josep Lluis Berral, David Carrera
Summary: This work focuses on efficient predictive analytics for urban traffic on edge devices with limited computational resources. The proposed solution utilizes distributed GRU model learning and low-power edge devices to achieve good prediction accuracy and computational performance.
IEEE INTERNET OF THINGS JOURNAL
(2022)
Article
Chemistry, Analytical
Luca De Nardis, Giuseppe Caso, Ozgu Alay, Marco Neri, Anna Brunstrom, Maria-Gabriella Di Benedetto
Summary: Narrowband Internet of Things (NB-IoT) has become a leading technology in IoT deployment due to its coverage, energy efficiency, and compatibility. However, NB-IoT still lacks reliable positioning methods. This investigation proposes a fingerprinting-based positioning strategy using coverage and radio information from multiple cells. Experimental results show that the proposed strategy outperforms current approaches, with a minimum average positioning error of about 20 m.
Article
Computer Science, Information Systems
Girish Vaidya, Akshay Nambi, T. Prabhakar, Vasanth T. Kumar, Suhas Sudhakara
Summary: This research introduces a device-specific identifier IoT-ID based on physically unclonable functions for device identification, which utilizes novel PUFs design to capture device characteristics without the need for additional hardware, achieving high accuracy in device identification.
PERVASIVE AND MOBILE COMPUTING
(2021)
Article
Computer Science, Theory & Methods
Abdullah Qasem, Paria Shirani, Mourad Debbabi, Lingyu Wang, Bernard Lebel, Basile L. Agba
Summary: In the era of IoT, ensuring the security of embedded systems and firmware has become increasingly important. Various methods exist to detect vulnerabilities in embedded devices and firmware, using analysis techniques such as static analysis, dynamic analysis, symbolic execution, and hybrid approaches. Quantitative and qualitative comparisons have been made among these approaches, and taxonomies have been devised based on application, features, and analysis type for future research directions.
ACM COMPUTING SURVEYS
(2021)
Article
Computer Science, Information Systems
Adnan Sabovic, Michiel Aernouts, Dragan Subotic, Jaron Fontaine, Eli De Poorter, Jeroen Famaey
Summary: With the rise of tinyML, deploying optimized ML models on battery-less IoT devices with limited energy is becoming increasingly feasible. However, running tinyML on these devices is still challenging due to unpredictable and dynamic harvesting environments. This paper proposes an energy-aware deployment and management approach for tinyML algorithms on battery-less IoT devices, considering trade-offs between local and cloud-based inference and respecting energy, accuracy, and time constraints. Real experiments with a prototype for battery-less person detection show that local inference performs better in controllable environments, while remote inference is favored under high light conditions in realistic harvesting scenarios.
INTERNET OF THINGS
(2023)
Article
Computer Science, Information Systems
Shangfeng Wan, Qiang Li, Haining Wang, Hong Li, Limi Sun
Summary: In this work, we developed a benchmark called DevTag for accurately fingerprinting IoT devices. DevTag supports retrieving packet-level features from IoT devices through passive monitoring and active probing. It integrates model-based and rule-based fingerprinting methods and underwent a systematic analysis to explore their advantages and limitations. Finally, we implemented and distributed a prototype of DevTag as the first benchmark for detecting IoT devices in the network community.
IEEE INTERNET OF THINGS JOURNAL
(2023)
Article
Computer Science, Information Systems
Kahraman Kostas, Mike Just, Michael A. Lones
Summary: This study presents a machine-learning-based method, IoTDevID, for device identification in IoT networks. By analyzing the characteristics of network packets, the method is able to accurately model device behavior and generalize to unseen data. It can also detect devices using non-IP and low-energy protocols.
IEEE INTERNET OF THINGS JOURNAL
(2022)
Article
Computer Science, Hardware & Architecture
Hongcheng Zou, Jinshu Su, Ziling Wei, Shuhui Chen, Baokang Zhao
Summary: This article introduces a new cross-domain low-data WF attack method, namely WFBDC, which can use a historical gathered dataset as an auxiliary dataset. WFBDC measures sample similarity by introducing the BDC metric and adopts transfer learning and multi-similarity loss techniques to mitigate domain deviation. Experimental results show that WFBDC can improve the performance of existing LDWF attacks by 9% and 19% in closed-world and open-world scenarios respectively, and significantly reduce the pre-training time.
Article
Computer Science, Hardware & Architecture
Jian Qu, Xiaobo Ma, Wenmao Liu, Hongqing Sang, Jianfeng Li, Lei Xue, Xiapu Luo, Zhenhua Li, Li Feng, Xiaohong Guan
Summary: Cyber search engines like Shodan and Censys have become popular for their ability to index the Internet of Things (IoT). They scan and identify IoT devices to uncover IP-device mapping. Tracking the evolution of IP-device mapping with limited scans is crucial for timely cyber search engines. This paper takes the first step in demystifying this problem by applying reinforcement learning to smartly scan IoT devices.
IEEE-ACM TRANSACTIONS ON NETWORKING
(2023)
Article
Chemistry, Multidisciplinary
Abdelkader Magdy Shaaban, Sebastian Chlup, Nahla El-Araby, Christoph Schmittner
Summary: Implementing applicable security measures into system engineering applications is a challenging process that requires considering various security attributes. This paper proposes a novel algorithm to optimize the implementation of security mechanisms in IoT applications for the agricultural domain. The algorithm helps ensure the effectiveness of the applied mechanisms against potential threats.
APPLIED SCIENCES-BASEL
(2022)
Article
Engineering, Electrical & Electronic
Di Lu, Ruidong Han, Yulong Shen, Xuewen Dong, Jianfeng Ma, Xiaojiang Du, Mohsen Guizani
Summary: IoT based eHealth system enables real-time monitoring and precise treatment plans, but lacks security considerations due to hardware limitations. To address this issue, a TPM extension scheme is proposed, including a shadow TPM as the trust base for N-TSED and three protocols for integrity verification and inter-SED authentication.
IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS
(2021)
Article
Computer Science, Information Systems
Biao Dong, Yuchao Liu, Guan Gui, Xue Fu, Heng Dong, Bamidele Adebisi, Haris Gacanin, Hikmet Sari
Summary: This article presents an efficient lightweight decentralized-learning-based AMC method for edge devices. The proposed method uses a spatiotemporal hybrid deep neural network based on multichannels and multifunction blocks to balance the trade-off between lightweight and classification performance. It also utilizes a cooperative approach for model updates and aggregation to enhance classification accuracy while reducing computational pressure.
IEEE INTERNET OF THINGS JOURNAL
(2022)
Article
Engineering, Electrical & Electronic
Hongtao Wang, Qiang Li, Feng Yi, Zhi Li, Limin Sun
EURASIP JOURNAL ON WIRELESS COMMUNICATIONS AND NETWORKING
(2016)
Article
Computer Science, Hardware & Architecture
Qiang Li, Xuan Feng, Lian Zhao, Limin Sun
Article
Computer Science, Information Systems
Qiang Li, Xuan Feng, Haining Wang, Limin Sun
IEEE INTERNET OF THINGS JOURNAL
(2018)
Article
Computer Science, Information Systems
Yuxuan Jia, Bing Han, Qiang Li, Hong Li, Limin Sun
INTERNATIONAL JOURNAL OF DISTRIBUTED SENSOR NETWORKS
(2018)
Article
Engineering, Electrical & Electronic
Kai Yang, Qiang Li, Xiaodong Lin, Xin Chen, Limin Sun
IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS
(2020)
Article
Computer Science, Hardware & Architecture
Qiang Li, Zhihao Wang, Dawei Tan, Jinke Song, Haining Wang, Limin Sun, Jiqiang Liu
Summary: IP-based geolocation is crucial for location-aware Internet applications, and GeoCAM leverages online webcams to automatically generate high-quality landmarks, enhancing geolocation accuracy and coverage.
IEEE-ACM TRANSACTIONS ON NETWORKING
(2021)
Article
Computer Science, Hardware & Architecture
Qiang Li, Dawei Tan, Xin Ge, Haining Wang, Zhi Li, Jiqiang Liu
Summary: This article conducts a systematic study on device vulnerabilities using firmware fingerprints, revealing that many embedded devices are still using outdated firmware with known vulnerabilities, posing significant security risks.
IEEE TRANSACTIONS ON DEPENDABLE AND SECURE COMPUTING
(2022)
Article
Computer Science, Information Systems
Shangfeng Wan, Qiang Li, Haining Wang, Hong Li, Limi Sun
Summary: In this work, we developed a benchmark called DevTag for accurately fingerprinting IoT devices. DevTag supports retrieving packet-level features from IoT devices through passive monitoring and active probing. It integrates model-based and rule-based fingerprinting methods and underwent a systematic analysis to explore their advantages and limitations. Finally, we implemented and distributed a prototype of DevTag as the first benchmark for detecting IoT devices in the network community.
IEEE INTERNET OF THINGS JOURNAL
(2023)
Proceedings Paper
Computer Science, Hardware & Architecture
Qiang Li, Jinke Song, Dawei Tan, Haining Wang, Jiqiang Liu
Summary: This study is the first large-scale empirical research on the relationship between project dependencies and security vulnerabilities. By utilizing the innovative approach PDGraph, a large number of project dependencies with publicly known security vulnerabilities were discovered, revealing existing security risks.
51ST ANNUAL IEEE/IFIP INTERNATIONAL CONFERENCE ON DEPENDABLE SYSTEMS AND NETWORKS (DSN 2021)
(2021)
Proceedings Paper
Computer Science, Information Systems
Zhihao Wang, Qiang Li, Jinke Song, Haining Wang, Limin Sun
WEB CONFERENCE 2020: PROCEEDINGS OF THE WORLD WIDE WEB CONFERENCE (WWW 2020)
(2020)
Proceedings Paper
Computer Science, Information Systems
Xuan Feng, Xiaojing Liao, XiaoFeng Wang, Haining Wang, Qiang Li, Kai Yang, Hongsong Zhu, Limin Sun
PROCEEDINGS OF THE 28TH USENIX SECURITY SYMPOSIUM
(2019)
Proceedings Paper
Computer Science, Theory & Methods
Kai Cheng, Qiang Li, Lei Wang, Qian Chen, Yaowen Zheng, Limin Sun, Zhenkai Liang
2018 48TH ANNUAL IEEE/IFIP INTERNATIONAL CONFERENCE ON DEPENDABLE SYSTEMS AND NETWORKS (DSN)
(2018)
Proceedings Paper
Computer Science, Information Systems
Xuan Feng, Qiang Li, Haining Wang, Limin Sun
PROCEEDINGS OF THE 27TH USENIX SECURITY SYMPOSIUM
(2018)
Article
Computer Science, Hardware & Architecture
Jinke Song, Qiang Li, Haining Wang, Limin Sun
PROCEEDINGS OF THE ACM ON MEASUREMENT AND ANALYSIS OF COMPUTING SYSTEMS
(2020)
Article
Computer Science, Hardware & Architecture
Xiaolin Gu, Wenjia Wu, Yusen Zhou, Aibo Song, Ming Yang, Zhen Ling, Junzhou Luo
Summary: This study proposes a radio frequency fingerprint identification solution based on crystal oscillator temperature adjustment, which enhances the differences between Wi-Fi device fingerprints and mitigates collision. Experimental results demonstrate the effectiveness of the system in identifying smartphones under different scenarios.
Article
Computer Science, Hardware & Architecture
Yutong Wu, Jianyue Zhu, Xiao Chen, Yu Zhang, Yao Shi, Yaqin Xie
Summary: This paper proposes a quality-of-service-based SIC order method and optimizes power allocation for maximizing the rate in the uplink NOMA system. The simulation results demonstrate the superiority of the proposed method compared to traditional orthogonal multiple access and exhaustive search.
Article
Computer Science, Hardware & Architecture
Songshi Dou, Li Qi, Zehua Guo
Summary: Emerging cloud services and applications have different QoS requirements for the network. SD-WANs play a crucial role in QoS provisioning by introducing network programmability, dynamic flow routing, and low data transmission latency. However, controller failures may degrade QoS. To address this, we propose PREDATOR, a QoS-aware network programmability recovery scheme that achieves fine-grained per-flow remapping without introducing extra delays, ensuring QoS robustness for high-priority flows.
Article
Computer Science, Hardware & Architecture
Ke Wang, Xiaojuan Ma, Heng Kang, Zheng Lyu, Baorui Feng, Wenliang Lin, Zhongliang Deng, Yun Zou
Summary: This paper proposes a method based on a parallel network simulation architecture to improve the simulation efficiency of satellite networks. By effectively partitioning the network topology and using algorithms such as resource assessment and load balancing, the simulation performance is enhanced. Experimental results demonstrate the effectiveness of this method.
Article
Computer Science, Hardware & Architecture
Sijin Yang, Lei Zhuang, Julong Lan, Jianhui Zhang, Bingkui Li
Summary: This paper proposes a reuse-based online scheduling mechanism that achieves deterministic transmission of dynamic flows through dynamic path planning and coordinated scheduling of time slots. Experimental results show that the proposed mechanism improves the scheduling success rate by 37.3% and reduces time costs by up to 66.6% compared to existing online scheduling algorithms.
