Article
Computer Science, Information Systems
Zhang Yukun, Wei Wenxue
Summary: Mobile Edge Computing (MEC) is an edge computing form in 5G technology that utilizes base stations as edge servers to bring cloud computing services to the network edge. This paper proposes a lightweight authentication and key agreement scheme that achieves secure and efficient identity authentication and key agreement in MEC environment.
PEER-TO-PEER NETWORKING AND APPLICATIONS
(2022)
Article
Computer Science, Information Systems
Yanrong Lu, Dawei Zhao
Summary: This paper proposes a biometric-based authentication scheme in an MCC environment to resist impersonation attacks, using hashing and symmetric parameter functions. The scheme strikes a balance between functionality and performance, making it suitable for MCC services.
COMPUTER COMMUNICATIONS
(2022)
Article
Computer Science, Information Systems
P. Vasudeva Reddy, A. Ramesh Babu, N. B. Gayathri
Summary: Public Key Cryptosystem (PKC) relies on the security of the user's private key, and exposure of the private key can lead to disastrous situations. To address this issue, a key-insulation mechanism was introduced. Identity-based cryptosystems alleviate certificate management issues in traditional PKC and a pairing-free key insulated signature scheme in identity-based setting has been proposed to improve efficiency and resist private key exposure.
JOURNAL OF KING SAUD UNIVERSITY-COMPUTER AND INFORMATION SCIENCES
(2021)
Article
Computer Science, Information Systems
Mingping Qi, Jianhua Chen
Summary: This article presents a new efficient anonymous one-way AKE protocol, which has strong anonymity and security properties guarantee, and efficiency advantages. The protocol is formally proved secure in the random oracle model under the Gap-DH and XCR signature security assumptions.
IEEE SYSTEMS JOURNAL
(2021)
Article
Computer Science, Information Systems
Prabath Abeysekara, Hai Dong, A. K. Qin
Summary: Mobile Edge Computing (MEC)-based Internet of Things (IoT) systems generate trust information in a real-time and distributed manner. Predicting trustworthiness of IoT services in such an MEC environment requires new prediction strategies that cater for the aforementioned characteristics of trust information. More importantly, it is imperative to investigate how the real-time trust information could be effectively integrated into trust prediction strategies in order to capture the ever-evolving nature of trustworthiness of IoT services.
IEEE TRANSACTIONS ON SERVICES COMPUTING
(2023)
Article
Mathematics
Javier de la Cruz, Edgar Martinez-Moro, Ricardo Villanueva-Polanco
Summary: This paper introduces skew dihedral group rings and their applications in public-key cryptography. It presents a specific skew group ring as the underlying algebraic platform for cryptographic constructions, and builds a two-party key exchange protocol with security analysis. In addition, it derives a group key agreement protocol, a probabilistic public-key scheme, and a key encapsulation mechanism. Furthermore, a proof-of-concept implementation is provided.
Article
Engineering, Mechanical
Bo Hu, Tian Gao, Jinjun Zhao, Zhiyong Liu
Summary: This paper investigates the inverse kinematics problem of lower mobility serial mechanisms. By establishing pose coupling equations, the feasible pose of the end-effector is determined, and an improved inverse kinematic modeling process is proposed. The applicability of the proposed inverse kinematics producer is demonstrated.
MECHANISM AND MACHINE THEORY
(2022)
Article
Chemistry, Analytical
Sana Farooq, Ayesha Altaf, Faiza Iqbal, Ernesto Bautista Thompson, Debora Libertad Ramirez Vargas, Isabel de la Torre Diez, Imran Ashraf
Summary: Recent developments in quantum computing have raised concerns about the security of conventional public encryption systems. The National Institute of Standards and Technology (NIST) is actively seeking post-quantum encryption algorithms that can resist quantum computer attacks. This study evaluates the performance of two post-quantum cryptography algorithms and provides insights for researchers and practitioners in selecting appropriate algorithms.
Article
Computer Science, Artificial Intelligence
Kuebra Seyhan, Sedat Akleylek
Summary: In this article, a double-NTRU-based key encapsulation mechanism (KEM) is proposed for the key agreement requirement in the post-quantum world. The KEM combines one-way D-NTRU encryption and Dent's KEM design method to construct a D-NTRU-based KEM that provides IND-CCA2 security. The article examines the IND-CCA2 analysis and attack resistance of the proposed D-NTRU KEM and compares it with similar protocols in terms of parameters, public/secret keys, and ciphertext sizes. The proposed scheme offers arithmetic simplicity and IND-CCA2 security without the need for any padding mechanism.
PEERJ COMPUTER SCIENCE
(2023)
Article
Computer Science, Information Systems
Vivek Dabra, Anju Bala, Saru Kumari
Summary: The recent advancement in quantum computers poses a threat to traditional key exchange protocols, leading to the development of secure protocols for the postquantum era. Existing protocols, while simple and efficient, are vulnerable to various attacks, prompting the proposal of lattice-based anonymous password authenticated key exchange protocol to address these issues.
IEEE SYSTEMS JOURNAL
(2021)
Article
Quantum Science & Technology
Randy Kuang, Maria Perepechaenko
Summary: Kuang et al. introduced a novel quantum-safe public key scheme called MPPK, which uses multiplication and division inversion relationship. We propose extending the key construction to use a partially homomorphic operator and two hidden rings to hide the public key polynomials.
QUANTUM INFORMATION PROCESSING
(2023)
Review
Mathematics, Interdisciplinary Applications
Tingting Shao, Xuan Yang, Fan Wang, Chao Yan, Ashish Kr. Luhach
Summary: The evaluation of trusted mobile edge services faces challenges such as low trust in service quality data and lack of feedback incentives. Current research is mainly focused on addressing these issues and exploring the application of trusted service evaluation in recommender systems.
Article
Computer Science, Information Systems
Ramin Ganjavi, Ahmad R. Sharafat
Summary: Mobile crowdsensing (MCS) is an important topic in the proliferation of mobile apps, with an increasing need for participants' anonymity to ensure their safety. Privacy-preserving aggregation in MCS faces challenges from participants joining/leaving randomly and adversaries injecting fake data. This paper presents an efficient edge-assisted MCS scheme that protects participants' privacy, detects adversaries, and verifies aggregation without anomalies.
IEEE TRANSACTIONS ON SERVICES COMPUTING
(2023)
Article
Computer Science, Information Systems
Wai-Kong Lee, Seong Oun Hwang
Summary: This article proposes novel and efficient implementation techniques to accelerate post-quantum Key Encapsulation Mechanism (KEM) on a Graphics Processing Unit (GPU). The techniques, including fully parallel number theoretic transform (NTT), parallel rejection sampling, central binomial distribution, and parallel fine-grain AES-256, enable high throughput performance on an RTX2060 GPU. This implementation is significant for IoT systems as it can offer key encapsulation/decapsulation as a service to reduce the system's burden.
IEEE TRANSACTIONS ON SERVICES COMPUTING
(2022)
Article
Computer Science, Information Systems
Amiya Kumar Sahu, Suraj Sharma, Deepak Puthal
Summary: This article proposes a lightweight, multi-party authentication and key-establishment protocol for IoT-based e-healthcare applications to address security challenges in resource-constrained devices. The scheme utilizes lattice-based cryptographic constructs such as Identity-Based Encryption (IBE) for security, privacy, and efficiency. Comprehensive analysis and evaluation including security, power consumption, and practical usage are provided to demonstrate the effectiveness of the proposed protocol.
ACM TRANSACTIONS ON MULTIMEDIA COMPUTING COMMUNICATIONS AND APPLICATIONS
(2021)
Article
Automation & Control Systems
Yanchen Qiao, Weizhe Zhang, Zhicheng Tian, Laurence T. Yang, Yang Liu, Mamoun Alazab
Summary: Recent research has shown that deep learning-based malware detection models for executable and linkable format (ELF) are vulnerable to adversarial attacks. This study proposes a new method to detect adversarial ELF malware by analyzing the decision-making basis of the model and using anomaly detection techniques. The method serves as an add-on module to the existing detection model and does not require any modifications or retraining.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2023)
Article
Computer Science, Theory & Methods
Weiguang Liu, Jinhua Cui, Tiantian Li, Junwei Liu, Laurence T. Yang
Summary: This paper presents MLCache, a space-efficient shared cache management scheme for NVMe SSDs. By learning the impact of reuse distance on cache allocation and building a workload-generic neural network model, MLCache achieves efficient space allocation decisions. Additionally, MLCache proposes an efficient parallel writing back strategy to improve fairness.
IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS
(2023)
Article
Computer Science, Artificial Intelligence
Jing Yang, Laurence T. Yang, Hao Wang, Yuan Gao, Yaliang Zhao, Xia Xie, Yan Lu
Summary: This paper investigates the progress and function of representation learning models adopted in knowledge fusion and reasoning, providing new perspectives and ideas for scholars. The paper comprehensively reviews classic methods and investigates advanced and emerging works. Additionally, an integrated knowledge representation learning framework and tensor-based knowledge fusion and reasoning models are proposed.
INFORMATION FUSION
(2023)
Article
Computer Science, Artificial Intelligence
Sushil Kumar Singh, Laurence T. Yang, Jong Hyuk Park
Summary: This article proposes a scheme called FusionFedBlock to address privacy issues in Industry 5.0 by combining blockchain and federated learning. In the scheme, industry departments can perform local learning updates and communicate with a global model, with validation conducted through a blockchain network. The scheme demonstrates excellent performance in privacy preservation and accuracy improvement.
INFORMATION FUSION
(2023)
Article
Computer Science, Cybernetics
Yuan Gao, Laurence T. Yang, Jing Yang, Hao Wang, Yaliang Zhao
Summary: The proposed attention U-Net based on Bi-ConvLSTM (AUBC-Net) is a model suitable for accurate segmentation of medical images. It reduces network parameters and improves performance through the optimization of the calculation process and the lightweight feature generation strategy.
IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL SYSTEMS
(2023)
Article
Computer Science, Hardware & Architecture
Shunli Zhang, Laurence T. Yang, Yue Zhang, Xiaokang Zhou, Zongmin Cui
Summary: This article presents a data-driven system-level design framework for responsible cyber-physical-social systems (CPSS), addressing ethical and legal concerns regarding decision-making in artificial intelligence systems.
Editorial Material
Computer Science, Hardware & Architecture
Sahil Garg, Jia Hu, Giancarlo Fortino, Laurence T. Yang, Mohsen Guizani, Xianjun Deng, Danda B. Rawat
Article
Engineering, Multidisciplinary
Yunzhi Xia, Xianjun Deng, Lingzhi Yi, Laurence T. Yang, Xiao Tang, Chenlu Zhu, Zhongping Tian
Summary: This paper proposes a 6G IoT coverage hole recovery algorithm based on Mobile Edge Computing (MEC) and Artificial Intelligence (AI). The algorithm utilizes the fusion model of the disc model and the confident information model to guide the movement of mobile edge nodes and repair the coverage holes through repeated games based on Q-learning.
IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING
(2023)
Article
Engineering, Electrical & Electronic
Xiaokang Zhou, Xuzhe Zheng, Xuesong Cui, Jiashuai Shi, Wei Liang, Zheng Yan, Laurence T. Yang, Shohei Shimizu, Kevin I-Kai Wang
Summary: This paper proposes a three-layer Federated Reinforcement Learning (FRL) framework with an end-edge-cloud structure, incorporating a digital twin system. It aims to enable lightweight model training and real-time processing in high-speed mobile networks. The proposed dual-reinforcement learning scheme and model splitting scheme effectively reduce communication costs and improve the non-IID problem.
IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS
(2023)
Article
Automation & Control Systems
Huazhong Liu, Jiawei Wang, Xiaoxue Yin, Jihong Ding, Laurence T. Yang, Tong Yao, Jing Yang, Yuan Gao
Summary: This article proposes a tensor-train (TT)-based multiuser multivariate multiorder (3M) physical Markov prediction approach for multimodal industrial trajectory pattern mining. The proposed approach improves the computational efficiency up to three times compared with the original tensor-based 3M approach, while ensuring basically consistent prediction accuracy.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2023)
Article
Engineering, Civil
Zongmin Cui, Zhixing Lu, Laurence T. Yang, Jing Yu, Lianhua Chi, Yan Xiao, Shunli Zhang
Summary: There are three key roles in Intelligent Transportation Systems: driver, vehicle, and road. Existing static interactions among them are not dynamic enough, and unable to reflect changes in driver preferences, vehicle conditions, and road conditions. To address this issue, a data-driven Cloud-Fog-Edge Collaborative Driver-Vehicle-Road (CFEC-DVR) framework is proposed, which continuously adapts and evolves to provide better ITS services for humans.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2023)
Article
Engineering, Civil
Jia Zhou, Guoqi Xie, Haibo Zeng, Weizhe Zhang, Laurence T. Yang, Mamoun Alazab, Renfa Li
Summary: In this paper, a clock-skew-based approach is proposed to pinpoint the sender and detect intrusion on proprietary CAN bus. By analyzing data from real vehicles, a box-plot algorithm based on score mechanism is presented to filter and describe the hardware characteristics of ECUs accurately.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2023)
Article
Computer Science, Information Systems
Xu Li, Feilong Tang, Luoyi Fu, Jiadi Yu, Long Chen, Jiacheng Liu, Yanmin Zhu, Laurence T. Yang
Summary: The provisioning of satellite controllers has a significant impact on the performance of software-defined satellite networks. The challenge lies in achieving low control overhead throughout the operation period, despite the difficulty in predicting network load accurately. Existing methods struggle to address this issue, leading to frequent controller migrations. In this paper, we propose globally optimized strategies utilizing current network load information and introduce approximate and heuristic algorithms to solve the Controller Provisioning Problem in SDSNs.
IEEE TRANSACTIONS ON MOBILE COMPUTING
(2023)
Article
Computer Science, Artificial Intelligence
Bocheng Ren, Laurence T. Yang, Qingchen Zhang, Jun Feng, Xin Nie
Summary: Various stream learning methods are emerging to provide solutions for artificial intelligence in streaming data scenarios. However, when each data stream is oriented to a different target space, it becomes impracticable to use the previous approaches. Therefore, we propose an adaptive learning scheme using tensor and meta-learning to mitigate domain shift and improve performance for few-shot streaming tasks.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2023)
Article
Computer Science, Artificial Intelligence
Xiaokang Wang, Lei Ren, Ruixue Yuan, Laurence T. Yang, M. Jamal Deen
Summary: In this article, a cloud-edge-aided quantized tensor-train distributed long short-term memory (QTT-DLSTM) method is presented as an approach for efficiently processing CPSS big data. By decomposing the multi-attributes CPSS big data into the QTT form, and utilizing a distributed cloud-edge computing model, the proposed method effectively improves training efficiency.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2023)
