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IEEE International Conference on Information Communication and Signal Processing (ICICSP)

作者： Zhiwei Jin Siyuan Zhou Yunquan Dong Bin Tang Guoping Tan College of Information Science and Engineering Hohai University Nanjing China Key Laboratory of Water Big Data Technology of Ministry of Water Resources Hohai University Nanjing China College of Computer Science and Software Engineering Hohai University Nanjing China School of Electronic and Information Engineering Nanjing University of Information Science and Technology Nanjing China

ISBN: (数字)9798350355895

ISBN: (纸本)9798350355901

The Internet of Things (IoT) has the capability to support the synchronous transmission of dynamically sensed environmental status information to base stations. To improve transmission timeliness, previous studies have commonly utilized Age of Information (AoI) as a metric for network performance. However, AoI falls short in capturing status synchronicity, as synchronization requires knowledge of updates from both the transmitter and the receiver, which AoI cannot reflect due to its inability to track changes at the transmitter. In this work, we adopt the Age of Synchronization (AoS) as a metric to quantify the time elapsed since the freshest information at the receiver becomes desynchronized. Specifically, we develop a model for an IoT communication network to derive closed-form expressions for the average peak AoS (PAoS) and average AoS, considering discrete geometric and uniformly distributed packet arrivals. Ad-ditionally, the analysis has been carried out for both first-come-first-served (FCFS) and last-come-first-served with preemptive resume (LCFS-PR) service disciplines. Within these results, we prove that network's synchronization performance worsens with longer packet arrival intervals but improves with higher arrival rates. LCFS-PR strategy makes synchronization independent of packet arrival, solely influenced by service rate. Additionally, AoS consistently remains lower than AoI in the same system, with both tending to converge as packet arrival rate rises.

关键词： Measurement Closed-form solutions Transmitters Processor scheduling Wireless networks Receivers Signal processing Synchronization Internet of Things Queueing analysis

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Malicious Clients and Contribution Co-Aware Federated Unlearning

IEEE Transactions on Artificial Intelligence

引用

IEEE Transactions on Artificial Intelligence 2025年

作者： Wang, Yang Li, Xue Chen, Siguang Nanjing University of Posts and Telecommunications Jiangsu Engineering Research Center of Communication and Network Technology Nanjing China Women’s Hospital of Nanjing Medical University Nanjing Women and Children’s Healthcare Hospital Department of Dermatology Nanjing China Hohai University College of Computer Science and Software Engineering Nanjing China

Existing federated unlearning methods to eliminate the negative impact of malicious clients on the global model are influenced by unreasonable assumptions (e.g., an auxiliary dataset) or fail to balance model performance and efficiency. To overcome these shortcomings, we propose a malicious clients and contribution co-aware federated unlearning (MCC-Fed) method. Specifically, we introduce a method for detecting malicious clients to reduce their impact on the global model. Next, we design a contribution-aware metric, which accurately quantifies the negative impact of malicious clients on the global calculating their historical contribution ratio. Then, based on this metric, we propose a novel federated unlearning method in which benign clients use the contribution-aware metric as a regularization term to unlearn the influence of malicious clients, and restoring model performance. Experimental results demonstrate that our method effectively addresses the issue of excessive unlearning during the unlearning process, improves the efficiency of performance recovery, and enhances robustness against malicious clients. © 2020 IEEE.

关键词： Federated learning federated unlearning malicious clients

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zsLLMCode: An Effective Approach for Code Embedding via LLM with Zero-Shot Learning

arXiv

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arXiv 2024年

作者： Xian, Zixiang Huang, Rubing Cui, Chenhui Fang, Chunrong Chen, Zhenyu School of Computer Science and Engineering Macau University of Science and Technology Macau Taipa999078 China Macau University of Science and Technology Zhuhai MUST Science and Technology Research Institute Guangdong Zhuhai519099 China State Key Laboratory for Novel Software Technology Nanjing University Nanjing210093 China

The advent of large language models (LLMs) has greatly advanced artificial intelligence (AI) in software engineering (SE), with code embeddings playing a critical role in tasks like code-clone detection and code clustering. However, existing methods for code embedding, including those based on LLMs, often depend on costly supervised training or fine-tuning for domain adaptation. This paper proposes a novel zero-shot approach, zsLLMCode, to generate code embeddings by using LLMs and sentence embedding models. This approach attempts to eliminate the need for task-specific training or fine-tuning, and to effectively address the issue of erroneous information commonly found in LLM-generated outputs. We conducted a series of experiments to evaluate the performance of the proposed approach by considering various LLMs and embedding models. The results have demonstrated the effectiveness and superiority of our method zsLLMCode over state-of-the-art unsupervised approaches such as SourcererCC, Code2vec, InferCode, and TransformCode. Our findings highlight the potential of zsLLMCode to advance the field of SE by providing robust and efficient solutions for code embedding tasks. © 2024, CC BY.

关键词： Zero-shot learning

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openCAESAR: Balancing Agility and Rigor in Model-Based Systems engineering

openCAESAR: Balancing Agility and Rigor in Model-Based Syste...

引用

Conference on Model Driven engineering Languages and Systems Companion (MODELS-C)

作者： Maged Elaasar Nicolas Rouquette David Wagner Bentley James Oakes Abdelwahab Hamou-Lhadj Mohammad Hamdaqa NASA Jet Propulsion Lab California Institute of Technology Pasadena USA DIRO Université de Montréal Montreal Canada Computer and Software Engineering Polytechnique Montréal Montreal Canada Electrical and Computer Engineering Concordia University Montreal Canada

Model-Based System engineering (MBSE) employs models and formal languages to support development of complex (systems-of-) systems. NASA Jet Propulsion Laboratory (JPL) sees MBSE as a key approach to managing the complexity of system development. However, balancing agility and rigor in MBSE has been reported as a challenging task not yet addressed by modeling tools and frameworks. This is because existing MBSE approaches may enable agility but compromise rigor, or enhance rigor but impede agility. We discuss the challenges of balancing agility and rigor in MBSE across seven systems engineering architectural functions defined by the JPL Integrated Model-Centric engineering (IMCE) initiative. We demonstrate how openCAESAR, an open-source MBSE methodology and framework created at JPL, can strike a balance between agility and rigor through a case study of the Kepler16b project and discussion of lessons learned from past projects.

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A Secure Authentication Framework for Consumer Mobile Crowdsourcing Networks

引用

IEEE Transactions on Consumer Electronics 2024年

作者： Aldosary, Abdallah Tanveer, Muhammad Ahmad, Musheer Maghrabi, Louai A. Ahmed, Emad A. Hussain, Amir El-Latif, Ahmed A. Abd Department of Computer Engineering Prince Sattam bin Abdulaziz University Riyadh Wadi Addwasir11991 Saudi Arabia University of Management and Technology Department of Computer Science Lahore54770 Pakistan Jamia Millia Islamia Department of Computer Engineering New Delhi110025 India University of Business and Technology College of Engineering Department of Software Engineering Jeddah Saudi Arabia South Valley University Faculty of Computers and Information Department of Computer Science Qena Egypt Edinburgh Napier University United Kingdom Prince Sultan University EIAS Data Science Lab College of Computer and Information Sciences Center of Excellence in Quantum and Intelligent Computing Riyadh11586 Saudi Arabia Menoufia University Faculty of Science Department of Mathematics and Computer Science Shebin El-Koom32511 Egypt

The Mobile crowdsourcing network (MCN) leverages collaborative intelligence to solve complex tasks through group cooperation. It comprises three main components: the end-user, the service provider, and the mobile user. The end-user requests crowd-sensing and computing services from the service provider, who handles task decomposition, distribution, re-composition, and recommendation. Mobile users perform the crowd sensing and computing tasks. Despite its benefits, MCN faces significant security and privacy challenges. Communications between the service provider and the end-user involve sensitive data, and mobile users and service providers communicate over open channels, making them vulnerable to security threats. To address these concerns, we propose a secure authentication framework for MCN, called SAF-MCN. This framework combines the lightweight cryptographic primitive ' ASCON' with elliptic curve cryptography. SAF-MCN allows the service provider to authenticate mobile users before they join the MCN. Once authenticated, a secure channel is established for encrypted communication over the public Internet. The security of SAFMCN is validated using both formal and informal methods, demonstrating its resilience against potential attacks. The use of Scyther further ensures the security of SAF-MCN. Comparative analysis shows that SAF-MCN is superior in terms of security features, computational efficiency, and communication cost. © 1975-2011 IEEE.

关键词： ASCON Authenticated Encryption Authentication Mobile Crowdsourcing Network Scyther Security

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An Interpretable Mechanical Fault Diagnosis Approach Based on Dynamics Embedding Neural Network and Contrastive Learning for Label-Free Vibration Signals

SSRN

引用

SSRN 2023年

作者： Sun, Shilong Peng, Tengyi Zhou, Yu Zhang, Xiao School of Mechanical Engineering and Automation Harbin Institute of Technology Guangdong Shenzhen518055 China College of Computer Science and Software Engineering Shenzhen University Shenzhen China College of Computer Science South-Central Minzu University Hubei Wuhan430074 China

The industrial vibration signals usually have no labels, and the intelligent fault diagnosis has low interpretability for the results. The supervised learning algorithm, for example, deep neural networks, cannot be directly applied to distinguish different vibration faults. This study proposes an automatic fault diagnosis method based on the Bootstrap Your Own Latent contrastive learning and dynamical systems model discovery algorithm (BYOLDIS), which can deal with the unlabeled signals and explain the diagnosis results. Firstly, deriving the differential equations matrix to develop the faulty bearing dynamical systems. Secondly, investigating the contrastive learning network with a time-delay embedding matrix to reconstruct the coordinates of the fault-dynamical system. Finally, constructing a library of fault machine dynamic polynomial equations can offer physical model-based prior constraints to reduce the dependence of neural networks on data. Therefore, the above three steps can make BYOLDIS achieve effective label-free and explainable mechanical fault automatic diagnosis. The simulated and experimental studies are conducted to verify the validity and robustness of the proposed method. The case studies demonstrate that BYOLDIS can achieve an accurate bearing fault diagnosis and provide a dynamic explanation for the diagnostic results. Therefore, the proposed BYOLDIS is a promising diagnostic method for processing unlabeled vibrational data. © 2023, The Authors. All rights reserved.

关键词： Failure analysis

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Enhancing Healthcare Data Security in Cloud Computing Systems through Advanced Homomorphic Encryption Techniques Integrated with Cuckoo Search Optimization Algorithm

Enhancing Healthcare Data Security in Cloud Computing System...

引用

Recent Advances in Science and engineering technology (ICRASET), International Conference on

作者： I. Sudha P.S. Ramesh A. Ponmalar J. Jagannathan Rajkumar Pandiarajan Department of Computer Science and Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences SIMATS University Chennai Tamil Nadu India Department of Computer Science and Engineering Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology Chennai Tamilnadu India R.M.K. Engineering College Chennai Tamilnadu India Department of Software and Systems Engineering School of Computer Science Engineering and Information Systems Vellore Institute of Technology Katpadi Vellore India Department of Information and Technology School of Computing Kalasalingam Academy of Research and Education Krishnankoil Virudhunagar India

ISBN: (数字)9798350388602

ISBN: (纸本)9798350388619

The studies in this research are focused on the mix of homomorphic encryption mechanisms and the Cuckoo Search Optimization Algorithm to promote the security of the healthcare data in the cloud computing system. I have observed that cloud solutions are now at the center of the contemporary health care systems, and security of patient’s data remains a top priority. Earlier used encryption techniques, though secure if implemented, have problems in the way that data is to be processed first it has to be decrypted and then made ready for use - it is in this phase that data can be easily hacked into. Homomorphic encryption provides solution to this issue since it enables one to perform computations on encrypted data while maintaining its confidentiality. However, it takes a lot of computation which presents a lot of problems even in terms of simple performance. The Cuckoo Search Algorithm, a new nature-inspired metaheuristic, is incorporated into the encryption process to provide further optimization, whilst preserving the security benefits of the algorithm. The use of the proposed methodology takes place employing Python and its deployment at the cloud platform with elaborated dataset containing anonymized records extracted from electronic health records. The outcome proves that there are great enhancements in encryption and decryption time, computational complexity, and capacity, and thereby making the system appropriate for real-world healthcare solutions. This research offers a strong base for protection of healthcare data in cloud and is useful for the enhancement of adaptive, comprehensive and secure cloud computing systems.

关键词： Cloud computing Machine learning algorithms Metaheuristics Distributed databases Medical services Organizations Machine learning Homomorphic encryption Protection Electronic medical records

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Enhancing ASIC technology Mapping via Parallel Supergate Computing

arXiv

引用

arXiv 2024年

作者： Cai, Ye Yang, Zonglin Ni, Liwei Xie, Biwei Li, Xingquan College of Computer Science and Software Engineering Shenzhen University Shenzhen China Peng Cheng Laboratory Shenzhen China State Key Lab of Processors Institute of Computing Technology Chinese Academy of Sciences Beijing China

With the development of large-scale integrated circuits, electronic design automation (EDA) tools are increasingly emphasizing efficiency, with parallel algorithms becoming a trend. The optimization of delay reduction is a crucial factor for ASIC technology mapping, and supergate technology proves to be an effective method for achieving this in EDA tools flow. However, we have observed that increasing the number of generated supergates can reduce delay, but this comes at the cost of an exponential increase in computation time. In this paper, we propose a parallel supergate computing method that addresses the tradeoff between time-consuming and delay optimization. The proposed method utilizes the input-constrained supergate pattern to parallelly generate the supergate candidates, and then filter the valid supergates as the results. Experiment results show the efficiency of the proposed method, for example, it can attain the improvement of 4× speedup in computation time and 10.1 in delay reduction with 32 threads. Copyright © 2024, The Authors. All rights reserved.

关键词： Efficiency

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Securing Multi-Tenant Cloud Environments with Fully Homomorphically Encrypted Secure Multiparty Computation

Securing Multi-Tenant Cloud Environments with Fully Homomorp...

引用

Recent Advances in Science and engineering technology (ICRASET), International Conference on

作者： A. Ponmalar Rajkumar Pandiarajan I. Sudha P.S. Ramesh J. Jagannathan R.M.K. Engineering College Chennai Tamilnadu India Department of Information and Technology School of Computing Kalasalingam Academy Of Research and Education Krishnankoil Virudhunagar India Department of Computer Science and Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences SIMATS University Chennai Tamil Nadu India Department of Computer Science and Engineering Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology Chennai Tamil Nadu India Department of Software and Systems Engineering School of Computer Science Engineering and Information Systems Vellore Institute of Technology Katpadi Vellore India

ISBN: (数字)9798350388602

ISBN: (纸本)9798350388619

The aim of this work is to examine the application of FHE-SMPC as a viable security model for protecting the tenant isolation in multi-tenant cloud model. In multi-tenant environments, where various customers use the same cloud system, controlling the data leakage and protecting privacy is a major issue. Actual safeguards fail to meet the needs of data protection during processing, therefore, the introduction of highly elaborate encryption processes must happen. This research work focuses on the use of FHE technique and SMPC such that data can undergo processing while the plaintext remains unknown to any party. A kind of approach is based on the acquisition of synthetic and real data sets, system-level architecture, and cryptographic algorithms using open-source libraries with cloud service providers. The results of such implementation indicate that despite the fact that the FHE-SMPC system has a considerable computational overhead in comparison with classical schemes it is very secure and protected against different types of cryptographic attacks. The problem of scalability is still an open issue, but the complex is quite efficient with various data types that is why it can be used in various cloud applications. This paper offers a pertinent solution for security of data that is housed in multitenant environment and will go along way in creating fertile ground for research and innovation in secure clouding.

关键词： Resistance Technological innovation Scalability Data protection Libraries Service-oriented architecture Encryption Cryptography Time complexity Secure storage

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New Ontology structure for intelligent controlling of traffic signals 26

New Ontology structure for intelligent controlling of traffi...

引用

26th International Conference on Knowledge-Based and Intelligent Information and engineering Systems, KES 2022

作者： Mohammad, Mahmud Abdulla Manguri, Kamaran H. Abdulsamad, Taib Shamsadin Faeq Al-Talabani, Abdulbasit K. Abdulrahman, Akam Aziz Computer Science Department College of Basic Education University of Raparin Kurdistan Region Ranya Iraq College of Science and Technology University of Human Development Kurdistan Region Sulaymaniyah Iraq Department of Software Engineering Koya University Kurdistan Region Koya Iraq

This article proposes a novel ontology design for intelligent controlling of traffic signals, considering the investigated factors, crowded factors, road factors, visibility conditions, and emergency situations. Essentially, the proposed method uses video-based knowledge and key feature from a monocular video camera only, capturing footage from either a traffic signals perspective or the top of the road lane. The key factors and entities in the traffic scene are formed into an ontology, which has been evaluated using synthetic datasets to interpret challenging cases. Semantic features related to the key factors in the scene are obtained and fed to the ontology. The experimental results indicate that the proposed method is capable of controlling traffic signals more efficiently than the fixed intervals protocol. © 2022 The Authors. Published by Elsevier B.V.

关键词： Semantics

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