Article
Computer Science, Artificial Intelligence
Ziwei Zhang, Peng Cui, Wenwu Zhu
Summary: This survey comprehensively reviews the application of deep learning methods on graph data. The existing methods are categorized into five types, and their development history, differences, and compositions are covered in a systematic manner. Potential future research directions are also discussed.
IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING
(2022)
Article
Computer Science, Information Systems
Ahmed Imteaj, Urmish Thakker, Shiqiang Wang, Jian Li, M. Hadi Amini
Summary: This article investigates the methods and challenges of training distributed machine learning models in resource-constrained IoT environments, discusses the limitations of existing research, and identifies future research directions.
IEEE INTERNET OF THINGS JOURNAL
(2022)
Article
Computer Science, Artificial Intelligence
Senzhang Wang, Jiannong Cao, Philip S. Yu
Summary: This paper provides a comprehensive review of recent progress in applying deep learning techniques for spatial-temporal data mining (STDM). It categorizes the types of spatial-temporal data and introduces widely used deep learning models in STDM. The paper classifies existing literature based on the types of spatial-temporal data, data mining tasks, and deep learning models, and discusses the applications of deep learning for STDM in different domains. The limitations of current research and future research directions are also summarized.
IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING
(2022)
Article
Computer Science, Information Systems
Xiaorui Zhang, Xun Sun, Xingming Sun, Wei Sun, Sunil Kumar Jha
Summary: This paper proposes a two-stage reversible robust audio watermarking algorithm for protecting medical audio data. By decomposing the audio into two independent embedding domains and embedding different watermarks, the algorithm ensures both watermark robustness and audio quality. Experimental results demonstrate that the proposed scheme has strong robustness against various signal processing operations.
CMC-COMPUTERS MATERIALS & CONTINUA
(2022)
Article
Computer Science, Information Systems
J. Andrew Zhang, Md Lushanur Rahman, Kai Wu, Xiaojing Huang, Y. Jay Guo, Shanzhi Chen, Jinhong Yuan
Summary: This paper presents a comprehensive survey of the motivation, methodologies, challenges, and research opportunities in realizing a perceptive mobile network (PMN), which integrates sensing and communication capabilities. The PMN aims to provide a ubiquitous radio sensing platform and enable novel smart applications without compromising communication services. The paper discusses the JCAS technology, different types of JCAS systems, the framework of PMN, required system modifications, and stimulating research problems and potential solutions.
IEEE COMMUNICATIONS SURVEYS AND TUTORIALS
(2022)
Review
Computer Science, Information Systems
Sukhpal Singh Gill, Minxian Xu, Carlo Ottaviani, Panos Patros, Rami Bahsoon, Arash Shaghaghi, Muhammed Golec, Vlado Stankovski, Huaming Wu, Ajith Abraham, Manmeet Singh, Harshit Mehta, Soumya K. Ghosh, Thar Baker, Ajith Kumar Parlikad, Hanan Lutfiyya, Salil S. Kanhere, Rizos Sakellariou, Schahram Dustdar, Omer Rana, Ivona Brandic, Steve Uhlig
Summary: Autonomic computing investigates how systems can achieve specified control outcomes on their own. Integrating AI/ML to improve resource autonomy and performance remains a fundamental challenge. Experts in the field discuss current research, potential future directions, and challenges and opportunities for leveraging AI and ML in emerging computing paradigms.
INTERNET OF THINGS
(2022)
Article
Computer Science, Artificial Intelligence
Taotao Cai, Jianxin Li, Ajmal S. Mian, Ronghua li, Timos Sellis, Jeffrey Xu Yu
Summary: In this study, we address the issue of scheduling online campaigns or advertisements on social network platforms by proposing a novel holistic influence diffusion model that considers both cyber and physical user interactions. We also develop algorithms and solutions to solve the problem of holistic influence maximization. Experimental results demonstrate the efficiency and effectiveness of the proposed model and algorithms.
IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING
(2022)
Article
Computer Science, Information Systems
Mensah Kwabena Patrick, Adebayo Felix Adekoya, Ayidzoe Abra Mighty, Baagyire Y. Edward
Summary: Capsule Networks, as a new sensation in Deep Learning, show better performance in image recognition and other areas compared to Convolutional Neural Networks. However, researchers still need to address the lack of architectural knowledge and inner workings of Capsules.
JOURNAL OF KING SAUD UNIVERSITY-COMPUTER AND INFORMATION SCIENCES
(2022)
Article
Computer Science, Hardware & Architecture
Zhen Li, Deqing Zou, Shouhuai Xu, Hai Jin, Yawei Zhu, Zhaoxuan Chen
Summary: This article introduces a systematic framework for using deep learning to detect vulnerabilities in C/C++ programs. Through experiments, the practicality of the framework is demonstrated, and several previously unreported vulnerabilities are successfully detected.
IEEE TRANSACTIONS ON DEPENDABLE AND SECURE COMPUTING
(2022)
Article
Computer Science, Information Systems
Yun Li, Hui Ma, Lei Wang, Shiwen Mao, Guoyin Wang
Summary: This paper investigates the problem of content caching and user association for edge computing, and proposes an optimization problem and algorithm to reduce content download latency. Simulation results demonstrate that the proposed algorithm effectively reduces latency and improves cache hit rates at base stations.
IEEE TRANSACTIONS ON MOBILE COMPUTING
(2022)
Article
Computer Science, Information Systems
Xiaojie Wang, Zhaolong Ning, Song Guo, Lei Wang
Summary: The paper proposes an imitation learning enabled online task scheduling algorithm with near-optimal performance from the initial stage. An expert can obtain the optimal scheduling policy by solving the formulated optimization problem with a few samples offline. In theory, agent policies are trained by following the expert's demonstration with an acceptable performance gap.
IEEE TRANSACTIONS ON MOBILE COMPUTING
(2022)
Article
Computer Science, Information Systems
Yao Liu, Tanping Zhou, Zelun Yue, Wenchao Liu, Yiliang Han, Qi Li, Xiaoyuan Yang
Summary: Privacy protection of biometrics-based on cloud computing is attracting attention. An efficient and privacy-preserving online fingerprint authentication scheme called e-Finga was proposed. However, the temporary fingerprint in this scheme was found to have the risk of leaking the user's fingerprint characteristics. To counter this, a temporary fingerprint attack method was proposed and a secure e-finger scheme was developed. Experiments showed that the secure e-finger scheme can resist the temporary fingerprint attack.
IEEE TRANSACTIONS ON CLOUD COMPUTING
(2023)
Article
Computer Science, Hardware & Architecture
Shuming Qiu, Ding Wang, Guoai Xu, Saru Kumari
Summary: This article proposes a provably secure three-factor AKA protocol based on extended chaotic-maps for mobile lightweight devices. By utilizing Fuzzy-Verifiers and Honeywords techniques, the protocol achieves a good balance between security and usability.
IEEE TRANSACTIONS ON DEPENDABLE AND SECURE COMPUTING
(2022)
Review
Computer Science, Information Systems
Weijian Liu, Jun Liu, Chengpeng Hao, Yongchan Gao, Yong-Liang Wang
Summary: Multichannel adaptive signal detection uses test and training data jointly to form an adaptive detector to determine the presence or absence of a target. These adaptive detectors possess constant false alarm rate properties and do not require additional processing. Compared to the filtering-then-CFAR technique, adaptive detection typically exhibits better performance. However, there are few overview articles on this topic, hence this study provides a tutorial overview specifically focusing on Gaussian background and covers various aspects.
SCIENCE CHINA-INFORMATION SCIENCES
(2022)
Review
Computer Science, Information Systems
Elvira Ismagilova, Laurie Hughes, Nripendra P. Rana, Yogesh K. Dwivedi
Summary: The complex and interdependent nature of smart cities poses significant challenges for designers, integrators, and administrators. Research on security, privacy, and risks in smart cities has increased, providing valuable insights and guidance for future studies.
INFORMATION SYSTEMS FRONTIERS
(2022)
Article
Computer Science, Information Systems
Piera Centobelli, Roberto Cerchione, Pasquale Del Vecchio, Eugenio Oropallo, Giustina Secundo
Summary: Trust, traceability, and transparency are critical factors in designing circular blockchain platforms in supply chains. This paper proposes the integrated Triple Retry framework for designing circular blockchain platforms to bridge the three circular supply chain reverse processes and the three factors affecting blockchain technologies. The results highlight the role of blockchain as a technological capability for improving control in waste transportation and product return management activities.
INFORMATION & MANAGEMENT
(2022)
Article
Computer Science, Information Systems
Viraaji Mothukuri, Prachi Khare, Reza M. Parizi, Seyedamin Pouriyeh, Ali Dehghantanha, Gautam Srivastava
Summary: The Internet of Things (IoT) consists of billions of physical devices connected to the Internet, performing tasks independently with less human intervention. However, IoT networks are vulnerable to malicious attacks that aim to steal and manipulate personal data. In order to address this issue, the paper proposes a federated-learning (FL)-based approach that uses decentralized on-device data for anomaly detection in IoT networks. Experimental results demonstrate that this approach outperforms traditional centralized machine learning methods in securing user data privacy and achieving optimal accuracy in attack detection.
IEEE INTERNET OF THINGS JOURNAL
(2022)
Article
Computer Science, Information Systems
Keping Yu, Zhiwei Guo, Yu Shen, Wei Wang, Jerry Chun-Wei Lin, Takuro Sato
Summary: The emergence of Artificial Intelligence of Things (AIoT) has provided new opportunities for social computing applications. This article proposes a secure AIoT architecture for implicit group recommendations, which effectively captures group preference features and provides personalized services through hardware and software modules.
IEEE INTERNET OF THINGS JOURNAL
(2022)
Article
Computer Science, Information Systems
Weizheng Wang, Qiu Chen, Zhimeng Yin, Gautam Srivastava, Thippa Reddy Gadekallu, Fawaz Alsolami, Chunhua Su
Summary: This article introduces a lightweight and reliable authentication protocol for WMSN, based on blockchain technology and physically unclonable functions (PUFs). A fuzzy extractor scheme is used to handle biometric information, and two security evaluation methods are employed to prove the high reliability of the proposed scheme. Performance evaluation experiments demonstrate that the proposed mutual authentication protocol has the least computation and communication cost among the compared schemes.
IEEE INTERNET OF THINGS JOURNAL
(2022)
Article
Computer Science, Information Systems
Ming Tang, Vincent W. S. Wong
Summary: In this paper, a model-free deep reinforcement learning-based distributed algorithm is proposed to address the load problem in mobile edge computing systems. The algorithm can effectively reduce the ratio of dropped tasks and average delay.
IEEE TRANSACTIONS ON MOBILE COMPUTING
(2022)
