Article
Computer Science, Hardware & Architecture
Haijiang Wang, Jianting Ning, Xinyi Huang, Guiyi Wei, Geong Sen Poh, Ximeng Liu
Summary: The popularity of e-Healthcare systems has been increasing with the introduction of wearable healthcare devices and sensors, which collect personal health records stored in a remote cloud. To ensure privacy and secure access control, attributes based encryption (ABE) and searchable encryption are being utilized. This efficient hidden policy ABE scheme with keyword search enables efficient keyword search with constant computational overhead and storage overhead, while also enhancing recipient's privacy by hiding the access policy. Additionally, a trapdoor malleability attack is presented, revealing potential vulnerabilities in previous schemes.
IEEE TRANSACTIONS ON DEPENDABLE AND SECURE COMPUTING
(2021)
Article
Computer Science, Information Systems
Payal Chaudhari, Manik Lal Das
Summary: Searchable encryption allows cloud servers to search encrypted data without decryption. Single keyword-based encryption enables users to access subsets of documents containing specific keywords. The scheme presented in this paper uses attribute-based encryption to grant access to selective data subsets while maintaining user privacy.
IEEE TRANSACTIONS ON CLOUD COMPUTING
(2021)
Article
Computer Science, Information Systems
Yangyang Bao, Weidong Qiu, Peng Tang, Xiaochun Cheng
Summary: This paper proposes an ERPF-DS-KS scheme to address the data security and privacy issues in cloud-assisted MIoT, realizing efficient and fine-grained access control and ciphertext keyword search. It provides data authenticity through a pseudo identity-based signature mechanism and enables flexible indirect revocation of malicious data users.
IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS
(2022)
Article
Computer Science, Information Systems
Qinlong Huang, Guanyu Yan, Yixian Yang
Summary: In this article, the TABKS scheme is introduced to provide privacy-preserving and traceable attribute-based keyword search in multi-authority medical cloud. It proposes an anonymous EMR access control framework with multiple authorities and achieves traceable attribute-based Boolean keyword search.
IEEE TRANSACTIONS ON CLOUD COMPUTING
(2023)
Article
Computer Science, Information Systems
Payal Chaudhari, Manik Lal Das
Summary: This article presents a scheme called KeySea for privacy-preserving search over encrypted data in public cloud storage. The KeySea scheme uses a hidden access policy in attribute-based searchable encryption to maintain receiver anonymity and data privacy.
IEEE TRANSACTIONS ON SERVICES COMPUTING
(2022)
Article
Biochemical Research Methods
Qinlong Huang, Wei Yue, Yixian Yang, Lixuan Chen
Summary: With the development of bioinformatics and genetic sequencing technologies, genomic data is widely used in personalized medicine. Cloud computing provides a cost-effective and efficient solution for the challenges brought by massive genomic data. This paper proposes P2GT and P2GT+ schemes that utilize encryption techniques and equality tests to protect and authorize genetic testing in cloud computing, and experimental results demonstrate their practicality and scalability.
IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS
(2022)
Article
Computer Science, Information Systems
Qinlong Huang, Qinglin Wei, Guanyu Yan, Lin Zou, Yixian Yang
Summary: This article proposes FAKS, a fast and privacy-preserving attribute-based keyword search system for cloud document services. FAKS utilizes a Bloom filter tree structure and an attribute-based authenticated index retrieval scheme to perform keyword matching operations in a sublinear time.
IEEE TRANSACTIONS ON SERVICES COMPUTING
(2023)
Article
Engineering, Civil
Yangyang Bao, Weidong Qiu, Xiaochun Cheng, Jianfei Sun
Summary: The Internet of Vehicles (IoV) has revolutionized the driving experience and urban traffic management. This paper proposes an efficient access control scheme and an indirect revocation mechanism to address data leakage and personal privacy concerns in the publicly accessible IoV environment. Through detailed comparisons and simulation evaluations, the superiority of the proposed solutions in terms of functionality and performance is demonstrated.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2023)
Article
Automation & Control Systems
Yang Lu, Jiguo Li, Fen Wang
Summary: Industrial IoT (IIoT) is an practical application of the Internet of Things (IoT) in modern industry that accelerates industrial development. The recent certificate-based encryption with keyword search (CBEKS) scheme aims to address data privacy protection in the cloud, showing advantages in computation performance and security against keyword guessing attacks.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2021)
Article
Computer Science, Hardware & Architecture
Chunpeng Ge, Willy Susilo, Zhe Liu, Jinyue Xia, Pawel Szalachowski, Fang Liming
Summary: The emergence of cloud infrastructure has reduced the costs of computing infrastructure, with data usually encrypted before being outsourced to the cloud. Searching and sharing data after encryption poses challenges, but it is a critical task for cloud service providers. The CPAB-KSDS mechanism supports keyword search and data sharing for encrypted cloud data to address these challenges.
IEEE TRANSACTIONS ON DEPENDABLE AND SECURE COMPUTING
(2021)
Article
Computer Science, Information Systems
Xiangyu Wang, Jianfeng Ma, Yinbin Miao, Ximeng Liu, Ruikang Yang
Summary: This article presents techniques for encrypted data search and online pre-diagnosis in the context of Mobile Healthcare Monitoring Network. It proposes a new DKSE scheme and a framework called PRIDO to protect patients' personal data while enabling efficient and accurate data mining and disease pre-diagnosis.
IEEE TRANSACTIONS ON SERVICES COMPUTING
(2022)
Article
Computer Science, Hardware & Architecture
Yinbin Miao, Robert H. Deng, Kim-Kwang Raymond Choo, Ximeng Liu, Jianting Ning, Hongwei Li
Summary: The paper presents an optimized Verifiable Fine-grained Keyword Search scheme and extends it to support multi-keyword search and multi-owner update. Evaluation shows that both the basic VFKSM and the extended VFKSM can resist Chosen-Keyword Attack and external Keyword-Guessing Attack.
IEEE TRANSACTIONS ON DEPENDABLE AND SECURE COMPUTING
(2021)
Article
Multidisciplinary Sciences
Tao Feng, Sirui Miao, Chunyan Liu, Rong Ma
Summary: This paper proposes a verifiable attribute-based searchable encryption scheme that supports attribute revocation to address the issues in existing schemes in cloud storage environments. By introducing an attribute authorization center and a third-party auditor, it achieves fine-grained ciphertext search of dynamically changing user attributes and ensures reliable and honest search process by third-party servers while minimizing computation and storage costs.
Article
Computer Science, Information Systems
Shengmin Xu, Yingjiu Li, Robert H. Deng, Yinghui Zhang, Xiangyang Luo, Ximeng Liu
Summary: Healthcare Internet-of-Things (IoT) is a new paradigm that connects embedded devices to the cloud for monitoring patient vital signals and data aggregation. However, there are security concerns with the cloud due to untrusted network environments and limited resources. To address this, this paper proposes a novel healthcare IoT system that combines attribute-based encryption, cloud and edge computing to provide efficient, flexible, secure fine-grained access control and data verification, without the need for a secure channel.
IEEE TRANSACTIONS ON CLOUD COMPUTING
(2022)
Article
Computer Science, Information Systems
Fuyuan Song, Zheng Qin, Liang Xue, Jixin Zhang, Xiaodong Lin, Xuemin Shen
Summary: This article introduces a scheme for encrypted spatial keyword search in a cloud computing environment. By designing a geometric range query scheme and a multidimensional spatial keyword similarity search scheme, the privacy of data owners and search users is protected while improving query efficiency.
IEEE INTERNET OF THINGS JOURNAL
(2022)
Article
Computer Science, Theory & Methods
Jingwei Li, Adam Bowers, Dan Lin, Peng Jiang, Wei Jiang
Article
Computer Science, Hardware & Architecture
Jingwei Li, Jin Li, Dongqing Xie, Zhang Cai
IEEE TRANSACTIONS ON COMPUTERS
(2016)
Article
Computer Science, Hardware & Architecture
Jingwei Li, Anna Cinzia Squicciarini, Dan Lin, Smitha Sundareswaran, Chunfu Jia
IEEE TRANSACTIONS ON DEPENDABLE AND SECURE COMPUTING
(2017)
Article
Computer Science, Hardware & Architecture
Chuan Qin, Jingwei Li, Patrick P. C. Lee
ACM TRANSACTIONS ON STORAGE
(2017)
Article
Computer Science, Information Systems
Jingwei Li, Dan Lin, Anna Cinzia Squicciarini, Jin Li, Chunfu Jia
IEEE TRANSACTIONS ON CLOUD COMPUTING
(2017)
Article
Computer Science, Hardware & Architecture
Jingwei Li, Patrick P. C. Lee, Chufeng Tan, Chuan Qin, Xiaosong Zhang
ACM TRANSACTIONS ON STORAGE
(2020)
Article
Computer Science, Hardware & Architecture
Jingwei Li, Suyu Huang, Yanjing Ren, Zuoru Yang, Patrick P. C. Lee, Xiaosong Zhang, Yao Hao
Summary: Metadedup is an encrypted deduplication storage system that reduces metadata storage overhead by applying deduplication to metadata. It achieves fault-tolerant storage and security guarantees through distributed key management. Extensive evaluations show high throughput and significant metadata storage savings.
IEEE TRANSACTIONS ON COMPUTERS
(2022)
Proceedings Paper
Computer Science, Hardware & Architecture
Jingwei Li, Guoli Wei, Jiacheng Liang, Yanjing Ren, Patrick P. C. Lee, Xiaosong Zhang
Summary: Encrypted deduplication provides security and storage efficiency in large-scale storage systems, but its deterministic nature allows attackers to conduct frequency analysis. This paper proposes a distribution-based attack that models the relative frequency distributions of plaintexts and ciphertexts, improving the inference precision and evaluating the actual damage.
IEEE CONFERENCE ON COMPUTER COMMUNICATIONS (IEEE INFOCOM 2022)
(2022)
Proceedings Paper
Computer Science, Hardware & Architecture
Yanjing Ren, Jingwei Li, Zuoru Yang, Patrick P. C. Lee, Xiaosong Zhang
Summary: SGXDedup leverages Intel SGX to enhance the speed of encrypted deduplication while preserving security through secure interfaces and efficient enclave operations, achieving significant speedups and maintaining high bandwidth and storage savings in both synthetic and real-world workloads.
PROCEEDINGS OF THE 2021 USENIX ANNUAL TECHNICAL CONFERENCE
(2021)
Proceedings Paper
Computer Science, Theory & Methods
Jingwei Li, Zuoru Yang, Yanjing Ren, Patrick P. C. Lee, Xiaosong Zhang
PROCEEDINGS OF THE FIFTEENTH EUROPEAN CONFERENCE ON COMPUTER SYSTEMS (EUROSYS'20)
(2020)
Proceedings Paper
Computer Science, Hardware & Architecture
Jingwei Li, Chuan Qin, Patrick P. C. Lee, Xiaosong Zhang
2017 47TH ANNUAL IEEE/IFIP INTERNATIONAL CONFERENCE ON DEPENDABLE SYSTEMS AND NETWORKS (DSN)
(2017)
Proceedings Paper
Computer Science, Information Systems
Sushama Karumanchi, Jingwei Li, Anna Squicciarini
CODASPY'16: PROCEEDINGS OF THE SIXTH ACM CONFERENCE ON DATA AND APPLICATION SECURITY AND PRIVACY
(2016)
Article
Computer Science, Software Engineering
Mingqiang Li, Chuan Qin, Jingwei Li, Patrick P. C. Lee
IEEE INTERNET COMPUTING
(2016)
Proceedings Paper
Computer Science, Theory & Methods
Anna C. Squicciarini, Dan Lin, Smitha Sundareswaran, Jingwei Li
INTERNATIONAL CONFERENCE ON SECURITY AND PRIVACY IN COMMUNICATION NETWORKS, SECURECOMM 2014, PT I
(2015)
Proceedings Paper
Computer Science, Theory & Methods
Sushama Karumanchi, Jingwei Li, Anna Squicciarini
INTERNATIONAL CONFERENCE ON SECURITY AND PRIVACY IN COMMUNICATION NETWORKS, SECURECOMM 2014, PT I
(2015)
Editorial Material
Computer Science, Theory & Methods
Kiho Lim, Christian Esposito, Tian Wang, Chang Choi
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2024)
Editorial Material
Computer Science, Theory & Methods
Jesus Carretero, Dagmar Krefting
Summary: Computational methods play a crucial role in bioinformatics and biomedicine, especially in managing large-scale data and simulating complex models. This special issue focuses on security and performance aspects in infrastructure, optimization for popular applications, and the integration of machine learning and data processing platforms to improve the efficiency and accuracy of bioinformatics.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2024)
Article
Computer Science, Theory & Methods
Renhao Lu, Weizhe Zhang, Qiong Li, Hui He, Xiaoxiong Zhong, Hongwei Yang, Desheng Wang, Zenglin Xu, Mamoun Alazab
Summary: Federated Learning allows collaborative training of AI models with local data, and our proposed FedAAM scheme improves convergence speed and training efficiency through an adaptive weight allocation strategy and asynchronous global update rules.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2024)
Article
Computer Science, Theory & Methods
Qiangqiang Jiang, Xu Xin, Libo Yao, Bo Chen
Summary: This paper proposes a multi-objective energy-efficient task scheduling technique (METSM) for edge heterogeneous multiprocessor systems. A mathematical model is established for the task scheduling problem, and a problem-specific algorithm (IMO) is designed for optimizing task scheduling and resource allocation. Experimental results show that the proposed algorithm can achieve optimal Pareto fronts and significantly save time and power consumption.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2024)
Editorial Material
Computer Science, Theory & Methods
Weimin Li, Lu Liu, Kevin I. K. Wang, Qun Jin
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2024)
Article
Computer Science, Theory & Methods
Mohammed Riyadh Abdmeziem, Amina Ahmed Nacer, Nawfel Moundji Deroues
Summary: Internet of Things (IoT) devices have become ubiquitous and brought the need for group communications. However, security in group communications is challenging due to the asynchronous nature of IoT devices. This paper introduces an innovative approach using blockchain technology and smart contracts to ensure secure and scalable group communications.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2024)
Article
Computer Science, Theory & Methods
Robert Sajina, Nikola Tankovic, Ivo Ipsic
Summary: This paper presents and evaluates a novel approach that utilizes an encoder-only transformer model to enable collaboration between agents learning two distinct NLP tasks. The evaluation results demonstrate that collaboration among agents, even when working towards separate objectives, can result in mutual benefits.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2024)
Article
Computer Science, Theory & Methods
Hebert Cabane, Kleinner Farias
Summary: Event-driven architecture has been widely adopted in the software industry for its benefits in software modularity and performance. However, there is a lack of empirical evidence to support its impact on performance. This study compares the performance of an event-driven application with a monolithic application and finds that the monolithic architecture consumes fewer computational resources and has better response times.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2024)
Article
Computer Science, Theory & Methods
Haroon Wahab, Irfan Mehmood, Hassan Ugail, Javier Del Ser, Khan Muhammad
Summary: Wireless capsule endoscopy (WCE) is a revolutionary diagnostic method for small bowel pathology. However, the manual analysis of WCE videos is cumbersome and the privacy concerns of WCE data hinder the adoption of AI-based diagnoses. This study proposes a federated learning framework for collaborative learning from multiple data centers, demonstrating improved anomaly classification performance while preserving data privacy.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2024)
Article
Computer Science, Theory & Methods
Maruf Monem, Md Tamjid Hossain, Md. Golam Rabiul Alam, Md. Shirajum Munir, Md. Mahbubur Rahman, Salman A. AlQahtani, Samah Almutlaq, Mohammad Mehedi Hassan
Summary: Bitcoin, the largest cryptocurrency, faces challenges in broader adaption due to long verification times and high transaction fees. To tackle these issues, researchers propose a learning framework that uses machine learning to predict the ideal block size in each block generation cycle. This model significantly improves the block size, transaction fees, and transaction approval rate of Bitcoin, addressing the long wait time and broader adaption problem.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2024)
Article
Computer Science, Theory & Methods
Rafael Duque, Crescencio Bravo, Santos Bringas, Daniel Postigo
Summary: This paper introduces the importance of user interfaces for digital twins and presents a technique called ADD for modeling requirements of Human-DT interaction. A study is conducted to assess the feasibility and utility of ADD in designing user interfaces, using the virtualization of a natural space as a case study.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2024)
Article
Computer Science, Theory & Methods
Xiulin Li, Li Pan, Wei Song, Shijun Liu, Xiangxu Meng
Summary: This article proposes a novel multiclass multi-pool analytical model for optimizing the quality of composite service applications deployed in the cloud. By considering embarrassingly parallel services and using differentiated parallel processing mechanisms, the model provides accurate prediction results and significantly reduces job response time.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2024)
Article
Computer Science, Theory & Methods
Seongwan Park, Woojin Jeong, Yunyoung Lee, Bumho Son, Huisu Jang, Jaewook Lee
Summary: In this paper, a novel MEV detection model called ArbiNet is proposed, which offers a low-cost and accurate solution for MEV detection without requiring knowledge of smart contract code or ABIs.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2024)
Article
Computer Science, Theory & Methods
Sacheendra Talluri, Nikolas Herbst, Cristina Abad, Tiziano De Matteis, Alexandru Iosup
Summary: Serverless computing is increasingly used in data-processing applications. This paper presents ExDe, a framework for systematically exploring the design space of scheduling architectures and mechanisms, to help system designers tackle complexity.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2024)
Article
Computer Science, Theory & Methods
Chao Wang, Hui Xia, Shuo Xu, Hao Chi, Rui Zhang, Chunqiang Hu
Summary: This paper introduces a Federated Learning framework called FedBnR to address the issue of potential data heterogeneity in distributed entities. By breaking up the original task into multiple subtasks and reconstructing the representation using feature extractors, the framework improves the learning performance on heterogeneous datasets.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2024)