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FedPHE: A Secure and Efficient Federated Learning via Packed Homomorphic Encryption

IEEE Transactions on Dependable and Secure Computing 2025年

作者： Li, Yuqing Yan, Nan Chen, Jing Wang, Xiong Hong, Jianan He, Kun Wang, Wei Li, Bo Wuhan University Key Laboratory of Aerospace Information Security and Trusted Computing Ministry of Education School of Cyber Science and Engineering Wuhan430072 China Wuhan University RiZhao Information Technology Institute Rizhao276800 China Huazhong University of Science and Technology National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab/Cluster and Grid Computing Lab School of Computer Science and Technology Wuhan430074 China Shanghai Jiao Tong University School of Cyber Science and Engineering Shanghai200240 China Hong Kong University of Science and Technology Department of Computer Science and Engineering Hong Kong

Cross-silo federated learning (FL) enables multiple institutions (clients) to collaboratively build a global model without sharing private data. To prevent privacy leakage during aggregation, homomorphic encryption (HE) is widely used to encrypt model updates, yet incurs high computation and communication overheads. To reduce these overheads, packed HE (PHE) has been proposed to encrypt multiple plaintexts into a single ciphertext. However, the original design of PHE assumes all clients share a single private key, making the system vulnerable to security threats of ciphertexts being intercepted and decrypted by honest-but-curious clients. Also, it does not consider the heterogeneity among different clients, resulting in undermined training efficiency with slow convergence and stragglers. To address these challenges, we propose FedPHE, a secure and efficient FL framework with PHE by jointly exploiting contribution-aware secure aggregation and straggler-resistant client selection. Using CKKS with sparsification and blinding, FedPHE achieves efficient secure aggregation that allows clients to only provide obscured encrypted updates while the server can perform aggregation by accounting for contributions of local updates. To mitigate the straggler effect, we devise a perturbed sketch-based selection to cherry-pick representative clients with heterogeneous models and computing capabilities in a communication-efficient and privacy-preserving manner. We show, through rigorous security analysis and extensive experiments, that FedPHE can efficiently safeguard clients' privacy, achieve 2.45-6.56× training speedup, cut the communication overhead by 1.32-24.85×, and reduce straggler effects by 1.89-2.78×. © 2004-2012 IEEE.

关键词： Privacy by design

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Change Bit-Depth Procedure for Data Measured Preprocessing before Compression

Change Bit-Depth Procedure for Data Measured Preprocessing b...

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2022 IEEE International Multi-Conference on Engineering, computer and information Sciences, SIBIRCON 2022

作者： Levenets, Alexey V. Bondarenko, Vladislav V. Bahenov, Ruslan I. Belozerov, Oleg I. Belozerova, Svetlana I. Bogatenkov, Sergey A. Pacific National University Dept. Automation and System Engineering Khabarovsk Russia Sholom-Aleichem Priamursky State University Dept. Information Systems and Mathematics Birobidzhan Russia Far Eastern State Transport University Dept. Computer Technology and Computer Graphics Khabarovsk Russia South Ural State University Dept. Information Technology in Economics Chelyabinsk Russia

ISBN: (纸本)9781665464802

The paper proposes to change the bit-depth of the original data sequence as a preprocessing of the measuring data, which is carried out before the compression procedure. In this case the digit capacity conversion is performed without accounting for the primary data sample boundaries. The simulation was carried out in the Matlab software environment. The findings of the authors' research are presented. They prove to be a promising approach for some types of the studied data at least and several digit capacity values. The analysis of autocorrelation function values showing the data correlation revealed by the conversion is used as an assessment of perspective of the active conversion. In this article the authors review the values of secondary maximums of autocorrelation function. Their occurrence shows the demonstration of the implied correlative correspondence. Such correlations can potentially allow the converted data to be compressed more effectively than the original data using the known compression methods. © 2022 IEEE.

关键词： Data compression

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Improving Brain MRI Image Segmentation Quality: A Hybrid Technique for Intensity Inhomogeneity Correction 34

Improving Brain MRI Image Segmentation Quality: A Hybrid Tec...

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34th Conference of Open Innovations Association FRUCT, FRUCT 2023

作者： Aziz, Samah Abdel Hawbani, Ammar Wang, Xingfu Abdelhamid, Talaat Maolood, Ismail Y. Alsamhi, Saeed Ismail, A.S. School of Computer Science and Technology University of Science and Technology of China Hefei23002 China Zagazig University Zagazig44519 Egypt Menoufia University Faculty of Electronic Engineering Menoufia Egypt -System Information Ministry of Higher Education and Scientific Research Kurdistan Region Erbil Iraq National University of Ireland Insight Centre for Data Analytics Galway Ireland

ISBN: (纸本)9789526524603

Intensity inhomogeneity is a significant issue in magnetic resonance imaging (MRI), where the presence of bias field causes distortions in pixel values, resulting in inconsistent and erroneous intensities across the image. This artifact not only hampers accurate diagnosis by radiologists but also negatively impacts the performance of computer-aided diagnosis algorithms, particularly in tasks like segmentation. In our proposed approach, we use a hybrid technique called KIFCM, which integrates K-means and Fuzzy C-means to enhance brain tumor segmentation. K-means provides computational efficiency, while Fuzzy C-means improves accuracy by detecting missed tumor cells. We employ a bias correction method based on the level set framework, removing noise with a median filter and applying the hybrid KIFCM technique for optimal segmentation. Our method effectively addresses intensity variation challenges, ensuring precise brain tumor region segmentation. We compare our results with DFCM and MFFLs, and the comparison shows the efficiency of our proposed method by highlighting the superior quality and accuracy of 81% achieved, requiring less computational time. Consequently, our results demonstrate KIFCM's potential to boost both accuracy and speed in MRI-based brain tumor detection through computer-aided diagnosis. © 2023 FRUCT Oy.

关键词： Magnetic resonance imaging

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Smart Home system Based on IoT Concept Using Multi-Sensor Communication

Smart Home System Based on IoT Concept Using Multi-Sensor Co...

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computer Sciences, Engineering, and technology Innovation (ICoCSETI), International Conference on

作者： Dian Pramana I Putu Sumardika Eka Putra Komang Gede Krisna Bayu Pamungkas Dandy Pramana Hostiadi Made Liandana Gede Angga Pradipta Department of Information Technology Faculty of Informatics and Computer Institut Teknologi dan Bisnis STIKOM Bali Bali Indonesia Department of Computer System Faculty of Informatics and Computer Institut Teknologi dan Bisnis STIKOM Bali Bali Indonesia Department of Magister Information Systems Institut Teknologi dan Bisnis STIKOM Bali Bali Indonesia

ISBN: (数字)9798331508616

ISBN: (纸本)9798331508623

The smart home concept is being developed using the Internet of Things (IoT) technology. The smart home concept offers security services such as monitoring dangerous gas leaks and fires, light control, and keyless door lock systems. Previous studies introduced the idea of a smart home system based on IoT depending on security needs and determining the number of sensors. Still, the description of specific devices used needs to be detailed. Thus, a proper design model for a smart home system was required. This paper proposes a prototype design for a smart home concept by integrating multiple sensors. The sensors used in this prototype are the MQ-2 sensor, DHT-11 sensor, flame sensor, LDR sensor, and RFID. The research results show that the multi-sensor integration was successful, and each sensor could function according to its function within a time range from 0.6 seconds to 2 minutes. The prototype can be implemented through mobile-based applications and given quickly and flexibly.

关键词： Temperature sensors Technological innovation Prototypes Smart homes Sensor systems Security Internet of Things Time factors Intelligent sensors Radiofrequency identification

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Development of User Management in Ihya Digital Ecosystem Using Iterative Incremental Method 4

Development of User Management in Ihya Digital Ecosystem Usi...

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4th International Conference Advancement in Data Science, E-Learning and information systems, ICADEIS 2022

作者： Priandhika Izzulhaq, Afif Fauzi, Rahmat Suakanto, Sinung Kadir Hassan Disina, Abdul Mahdin, Hairulnizam Anka Salihu, Ibrahim Information System Telkom University Bandung Indonesia Nigeria Army University Biu Borno State Department of Cyber Security Nigeria Universiti Tun Hussein Onn Malaysia Faculty of Computer Science and Information Technology Johor Malaysia Nile University of Nigeria Abuja Nigeria

ISBN: (纸本)9781665463874

information systems have an essential role in the development of technology and information in Indonesia. information systems are employed and utilized in many facets of society and organizations. Digitizing and utilizing this information system will often form an integrated relationship between several digital sectors into an ecosystem or what is commonly called a digital ecosystem. Digital ecosystem provides benefits for users by exchanging data between systems within it since only one user account could access several systems or services in the ecosystem. The development of user management in the digital ecosystem will serve as a solution to accommodate the increasing number of users of the digital ecosystem. Iterative incremental development methods are used in the development of user management in Ihya digital ecosystem. The system was also tested using scenario tests, user acceptance tests, and load tests. Based on the results of the tests, the Ihya digital ecosystem user management module has met user needs with a User Acceptance Test value of 82.5%. Further development can be done in this research, including using APIs in the data exchange process and adding a two-factor authentication feature to improve data security. © 2022 IEEE.

关键词： information systems

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Petri net-based illegal information flow detection method for node-chain access control model 23

Petri net-based illegal information flow detection method fo...

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Proceedings of the 2023 International Conference on Communication Network and Machine Learning

作者： Binyong Li Jie Fang Xianhui Deng Yuhan Sheng School of Cybersecurity (Xin Gu Industrial College) Chengdu University of Information Technology China and Advanced Cryptography and System Security Key Laboratory of Sichuan Province China Sichuan Institute of Computer Sciences China School of Cybersecurity Chengdu University of Information Technology China

ISBN: (纸本)9798400716683

To address the problem of illegal information flow in the node chain access control model constructed by the existing attribute-based access control (ABAC) model when applied to a large-scale node chain scenario with more than 100 nodes, an illegal information flow detection method is proposed for the node chain access control model based on the classical Petri net. The method introduces the reachable identity and reachable identity graph of the classical single-Token Petri net, which can analyze the illegal information flow in the ABAC-based node-chain access control model conveniently and visually. Meanwhile, it can effectively use the reachable identity state in the Petri net to detect the illegal information flow in the model. The case analysis shows that the method can effectively detect the illegal information flow appearing in the model.

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User Interface Design’s Impact on Customer Satisfaction and Loyalty in SaaS E-Commerce

User Interface Design’s Impact on Customer Satisfaction and...

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Creative Communication and Innovative technology (ICCIT), IEEE

作者： Eka Purnama Harahap Pandu Hermawan Dhiyah Ayu Rini Kusumawardhani Nina Rahayu Maulana Arif Komara Harry Agustian Master of Technology Information University of Raharja Tangerang Indonesia Dept. of Information System Bina Bangsa University Serang Indonesia Dept. of Information System Pandawan Sejahtera Indonesia Tangerang Indonesia Dept. of Computer Systems University of Raharja Tangerang Indonesia Dept. of Digital Bussiness CAI Sejahtera Indonesia Tangerang Indonesia Dept. of Computer Systems Sesindo Tangerang Indonesia

ISBN: (数字)9798350367492

ISBN: (纸本)9798350367508

This study aims to analyze the impact of user interface (UI) design on customer satisfaction and loyalty in SaaS e-commerce applications, using a quantitative approach to measure the perceptions of SaaS e-commerce application users and determine how visual aspects and interface functionality contribute to the user experience, with data analysis conducted using the Partial Least Squares Structural Equation Modeling (PLS-SEM) method, indicating that an intuitive and responsive interface design significantly influences increased customer satisfaction, which in turn strengthens their loyalty to the application; the study seeks to provide insights that developing an effective user interface is crucial for building long-term relationships with customers and reaffirms the importance of integrating good interface design in e-commerce application development strategies, and further suggests that incorporating user-centered design principles and continuously collecting user feedback can enhance the user experience, thereby allowing developers to create interfaces that not only attract users but also retain them, essential for e-commerce businesses aiming to improve user engagement and loyalty in a highly competitive market.

关键词： Customer satisfaction Buildings Psychology Virtual reality User interfaces User experience Mathematical models Electronic commerce Usability Business

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Enhancing Network Intrusion Detection Using Effective Stacking of Ensemble Classifiers With Multi-Pronged Feature Selection Technique 2

Enhancing Network Intrusion Detection Using Effective Stacki...

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2nd International Conference on Emerging Trends in Electrical, Control, and Telecommunication Engineering, ETECTE 2023

作者： Rahman, Saifur Mursal, Salim Nasar Faraj Latif, Muhammad Armghan Mushtaq, Zohaib Irfan, Muhammad Waqar, Ali Najran University College of Engineering Department of Electrical Engineering Najran Saudi Arabia Cleveland State University Department of Computer and Information System United States University of Sargodha College of Engineering and Technology Department of Electrical Engineering Sargodha Pakistan North China electric power University Beijing China

ISBN: (纸本)9798350305654

information security depends on Network Intrusion Detection (NID), which properly identifies network threats. This work explores simulating a NID system by stacking ensemble classifiers with various feature selection methods. We used the NSL-KDD dataset for the investigation. The binary classification performance integrates all assaults into one class and treats another target variable as usual. Random Forest (RF), Bagging Classifier (BC), and Extra Tree Ensemble (ETE) using Logistics Regression (LR) as a meta estimator. Chi2-square (Chi2) and Recursive Feature Elimination (RFE) are also used for feature selection. The experimental findings suggest that the proposed technique is ideal for developing a classification model with high accuracy and outperforms standard machine learning classification methods. The Chi 2 attribute selection strategy with modest characteristics has the greatest accuracy of 99.84 %. A careful comparison with prior research shows that our technique produces state-of-the-art performance with reduced computing costs. © 2023 IEEE.

关键词： Feature Selection

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Modified Aquila Optimizer Feature Selection Approach and Support Vector Machine Classifier for Intrusion Detection system

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Multimedia Tools and Applications 2024年第21期83卷 59887-59913页

作者： Abualigah, Laith Ahmed, Saba Hussein Almomani, Mohammad H. Zitar, Raed Abu Alsoud, Anas Ratib Abuhaija, Belal Hanandeh, Essam Said Jia, Heming Elminaam, Diaa Salama Abd Elaziz, Mohamed Abd Computer Science Department Al Al-Bayt University Mafraq25113 Jordan Department of Electrical and Computer Engineering Lebanese American University Byblos13-5053 Lebanon Hourani Center for Applied Scientific Research Al-Ahliyya Amman University Amman19328 Jordan MEU Research Unit Middle East University Amman11831 Jordan Applied Science Research Center Applied Science Private University Amman11931 Jordan School of Computer Sciences Universiti Sains Malaysia Pulau Pinang11800 Malaysia School of Engineering and Technology Sunway University Malaysia Petaling Jaya27500 Malaysia Department of Mathematics Facility of Science The Hashemite University P.O box 330127 Zarqa13133 Jordan Sorbonne Center of Artificial Intelligence Sorbonne University-Abu Dhabi Abu Dhabi United Arab Emirates Department of Computer Science Wenzhou-Kean University Wenzhou China Department of Computer Information System Zarqa University P.O. Box 13132 Zarqa Jordan School of Information Engineering Sanming University Sanming365004 China Information Systems Department Faculty of Computers and Artificial Intelligence Benha University Benha12311 Egypt Computer Science Department Faculty of Computer Science Misr International University Cairo12585 Egypt Faculty of Computer Science & Engineering Galala University Suze435611 Egypt Ajman University Ajman346 United Arab Emirates Department of Mathematics Faculty of Science Zagazig University Zagazig44519 Egypt

With the ever-expanding ubiquity of the Internet, wireless networks have permeated every facet of modern life, escalating concerns surrounding network security for users. Consequently, the demand for a robust Intrusion Detection system (IDS) has surged. The IDS serves as a critical bastion within the security framework, a significance further magnified in wireless networks where intrusions may stem from the deluge of sensor data. This influx of data, however, inevitably taxes the efficiency and computational speed of IDS. To address these limitations, numerous strategies for enhancing IDS performance have been posited by researchers. This paper introduces a novel feature selection method grounded in Support Vector Machine (SVM) and harnessing the innovative modified Aquila Optimizer (mAO) for Intrusion Detection systems in Wireless Sensor Networks. To evaluate the efficacy of our approach, we employed the KDD'99 dataset for testing and benchmarking against established methods. Multiple performance metrics, including accuracy, detection rate, false alarm rate, feature count, and execution time, were utilized for assessment. Our comparative analysis reveals the superiority of the proposed method, with standout results in terms of feature reduction, detection accuracy, and false alarm mitigation, yielding significant improvements of 11%, 98.76%, and 0.02%, respectively. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2023.

关键词： Network security

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A Hierarchical Traffic Sign Image Recognition Algorithm Keeping the Local Topology

A Hierarchical Traffic Sign Image Recognition Algorithm Keep...

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Advanced Algorithms and Control Engineering (ICAACE), International Conference on

作者： Longhui Liu Wenhui Gong Wenjie Wang Zhiqiang Zeng Wei Li Xiamen Global Navigation Satellite System Development & Application Co. Ltd. Xiamen China School of Computer and Information Engineering Xiamen University of Technology Xiamen China

ISBN: (数字)9798350361445

ISBN: (纸本)9798350361452

Traffic sign recognition is crucial in enabling intelligent driving. This paper proposes a robust hierarchical traffic sign image recognition algorithm that maintains local topology. The algorithm is divided into two matching levels: rough matching and fine matching. The multi-scale image's Oriented Fast and Rotated BRIEF (ORB) [1] are extracted in coarse matching. Hamming distance is adopted to measure the similarity of feature points to execute rough and fast matching. In precise matching, the matched candidate feature points are further filtered using the number of features of surrounding points, that is, the Shape Context [2] feature, to achieve precise matching. This hierarchical matching method maintains the local topological characteristics of the image while performing robust and fast matching. In the experiment, the data set provided by Changsha University of Science and technology was used to assess the performance of the algorithm presented in this article.

关键词： Matched filters Image recognition Costs Shape Feature extraction Mobile handsets Topology

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