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VFGCN: A Vertical Federated Learning Framework With Privacy Preserving for Graph Convolutional network

IEEE Transactions on Dependable and Secure Computing 2025年

作者： Wang, Gang Li, Qingming Liu, Ximeng Yan, Xiaoran Dong, Qingkuan Wu, Huiwen Kong, Xiangjie Zhou, Li Zhejiang Lab HangZhou310000 China Zhejiang University College of Computer Science and Technology Hangzhou310058 China Fuzhou University Key Laboratory of Information Security of Network Systems College of Computer and Big Data Fuzhou350108 China Xidian University State Key Laboratory of Integrated Services Networks Xi'an710071 China Zhejiang University of Technology College of Computer Science and Technology Hangzhou310023 China Dalian University of Technology School of Software Dalian116620 China

Due to the robust representational capabilities of graph data, employing graph neural networks for its processing has demonstrated superior performance over conventional deep learning algorithms. Graph data encompasses abundant features and structural information;however, its large-scale collection is often challenging in practice. This difficulty arises because data predominantly exists in isolated compartments, making it arduous to harmonize information across various organizations or to enable multiple organizations to collaborate effectively while safeguarding local data privacy. In light of an extreme data distribution scenario, where each client possesses distinct nodes with partially overlapping segments yet divergent data features, we introduce a dual-cloud server architecture. This framework encompasses the design of four secure subprotocols: ReEnc (secure re-encryption), SecPSI (secure outsourcing of PSI), SecWeight (secure weight calculation), and SecAgg (secure aggregation). Together, these components facilitate a vertical federated learning framework for graph convolutional networks, ensuring privacy preservation. We provide a security proof for the entire system and extensive evaluation on three benchmark datasets (Cora, Citeseer, and Pubmed) illustrates that our Vertical Federated Graph Convolutional network (VFGCN) surpasses existing privacy-preserving methodologies. © 2004-2012 IEEE.

关键词： Privacy by design

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FANS: fuzzing android native system services via automated interface analysis 20

FANS: fuzzing android native system services via automated i...

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Proceedings of the 29th USENIX Conference on security Symposium

作者： Baozheng Liu Chao Zhang Guang Gong Yishun Zeng Haifeng Ruan Jianwei Zhuge Institute of Network Science and Cyberspace Tsinghua University and Beijing National Research Center for Information Science and Technology Alpha Lab 360 Internet Security Center Department of Computer Science and Technology Tsinghua University

ISBN: (纸本)9781939133175

Android native system services provide essential supports and fundamental functionalities for user apps. Finding vulnerabilities in them is crucial for Android security. Fuzzing is one of the most popular vulnerability discovery solutions, yet faces several challenges when applied to Android native system services. First, such services are invoked via a special interprocess communication (IPC) mechanism, namely binder, via service-specific interfaces. Thus, the fuzzer has to recognize all interfaces and generate interface-specific test cases automatically. Second, effective test cases should satisfy the interface model of each interface. Third, the test cases should also satisfy the semantic requirements, including variable dependencies and interface *** this paper, we propose an automated generation-based fuzzing solution FANS to find vulnerabilities in Android native system services. It first collects all interfaces in target services and uncovers deep nested multi-level interfaces to test. Then, it automatically extracts interface models, including feasible transaction code, variable names and types in the transaction data, from the abstract syntax tree (AST) of target interfaces. Further, it infers variable dependencies in transactions via the variable name and type knowledge, and infers interface dependencies via the generation and use relationship. Finally, it employs the interface models and dependency knowledge to generate sequences of transactions, which have valid formats and semantics, to test interfaces of target services. We implemented a prototype of FANS from scratch and evaluated it on six smartphones equipped with a recent version of Android, i.e., android-9.0.0_r46 , and found 30 unique vulnerabilities deduplicated from thousands of crashes, of which 20 have been confirmed by Google. Surprisingly, we also discovered 138 unique Java exceptions during fuzzing.

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Design and Implementation of Classroom Attendance System Based on Video Face Recognition

Design and Implementation of Classroom Attendance System Bas...

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作者： Lin Zhi-heng Li Yong-zhen Network & Information Security Lab Dept.of Computer Science & TechnologyYanbian University

Classroom attendance,as an indispensable part of teaching activities,plays a very important role in classroom *** attendance can effectively supervise students to attend classes on time and ensure the quality of classroom ***,the current classroom attendance is mainly achieved by the way of teacher's namecalling,which will cause a lot of waste of classroom *** paper presents a classroom attendance system based on video face recognition *** system uses a camera installed in the classroom to obtain classroom video *** the collected video information,it is first divided into a frame of static pictures,and from the pictures,several pictures with clear face and better light are selected for face recognition,and finally the recognition results are aggregated and *** order to solve the influence of the location of the camera on the recognition results,the system can be combined with the platform control system to control the rotation and focusing of the camera through the platform,and further improve the recognition accuracy.

关键词： attendance in class face recognition image segmentation deep learning

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A novel identity-based authentication scheme for IoV security

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International Journal of network security 2020年第4期22卷 627-637页

作者： Wang, Changguang Dai, Zimeng Zhao, Dongmei Wang, Fangwei Key Lab of Network and Information Security of Hebei Province No.20 South ErHuan Road YuHua District Shijiazhuang050024 China College of Computer and Cyber Security Hebei Normal University No.20 South ErHuan Road YuHua District Shijiazhuang050024 China

In order to enhance the security of the IoV (Internet of Vehicles), a novel bi-directional authentication scheme is presented in this paper. By use of the elliptic curve en-cryption algorithm and the bilinear pair mapping theory, this scheme is designed to store the main system infor-mation in the RSU (Road Side Unit). During the pro-cess of communication, the shared key, identity ID, and handshake principle are used to perform mutual security authentication between the RSU and OBU (On Board Unit), thus ensuring the legitimacy of the communication nodes. Simulation experiments show that the computa-tional complexity is reduced by about 10%, the efficiency and security of the scheme are improved compared with the existing schemes while meeting the security requirements. © 2020, Femto Technique Co., Ltd.

关键词： Authentication

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Secure Data Propagation in Edge-Cloud Orchestrated Computing Paradigms: Statistcs and Taxonomy

Secure Data Propagation in Edge-Cloud Orchestrated Computing...

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International Conference on Advanced Cloud and Big Data (CBD)

作者： Feng Yu Xixian Li Huimin Zhang Li-e Wang College of computer science Guangxi Normal University Guilin China Key Laboratory of Computer Network and Information Integration Southeast University Nanjing China Guangxi Key Lab of Multi-source Information Mining &Security Guilin China Guangxi Key Laboratory of Trusted Software Guilin University of Electronic Technology Guilin China

Despite the importance of the secure data propagation in the edge-cloud orchestrated computing paradigms, to the best of our knowledge, there is lack of systematic and comprehensive review on this research topic. The purpose of this article is to provide a systematic literature survey on secure data propagation in edge-cloud orchestrated computing environment to examine the current technical achievements published between 2010 and February 2020. The brief contributions of the paper are as follows: (1)providing a comprehensive literature review of the secure data propagation approaches in the edge-cloud orchestrated computing paradigms, (2) designing a methodology for document retrieval and selection, (3) presenting analysis and comparison for main technique methods of secure data propagation in hybrid edge-cloud environment.

关键词： Systematics Bibliographies Taxonomy Big Data

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A Control Task Assignment Algorithm based on sub-graph isomorphism

A Control Task Assignment Algorithm based on sub-graph isomo...

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International Conference on Advanced Cloud and Big Data (CBD)

作者： Feng Yu Xixian Li Huimin Zhang Li-e Wang College of computer science Guangxi Normal University Guilin China Key Laboratory of Computer Network and Information Integration Southeast University Nanjing China Guangxi Key Lab of Multi-source Information Mining & Security Guilin China Guangxi Key Laboratory of Trusted Software Guilin University of Electronic Technology Guilin China

To enhance the controllability and trustworthiness of the Internet, a new network control architecture has been presented with control task extracted to the intra-domain control node and executed in distributed multi-domain cooperative style. The study on control task assigning approach plays a central role in this network control pattern and shares some features with virtual network mapping problem. Different from the previous heuristics-based algorithms, we designs a baseline assigning algorithm which tests if the control task request can be mapped to a sub-graph of substrate control network or not without control task migration. Subsequently, an extend version is described under task migration considered. Our experiment evaluations show the impact of parameters on the runtime and assigning accuracy rate.

关键词： Cloud computing Backtracking Runtime Heuristic algorithms Process control Big Data Feature extraction

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CACAI: Comparative analysis of crypto apps in India

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AIP Conference Proceedings 2023年第1期2916卷

作者： Rahul Johari Anuj Talwar Suhas Harbola Jyotsna Yadav Himesh Nayak Deo Prakash Vidyarthi SWINGER: Security Wireless IoT Network Group of Engineering and Research University School of Information Communication and Technology (USICT) Guru Gobind Singh Indraprastha University Sector-16C Dwarka Delhi India Computer vision and Image processing lab University School of Information Communication and Technology (USICT) Guru Gobind Singh Indraprastha University Sector-16C Dwarka Delhi India School of Computer and Systems Sciences Parallel and Distributed Systems Lab JNU Delhi India

Crypto-currency is a decentralized digital currency which can be used as a medium of exchange. As it does not have any central authority, it is unregulated and a volatile asset. Globally the crypto market is worth a few trillion dollars. The Indian crypto market suffered a lot due to a ban imposed by the Reserve Bank of India (RBI), an Indian regulatory agency, which lasted for around two years. Even after the ban and cautions issued by the RBI, the crypto market in India touched a billion dollar mark in no time. Currently, the crypto market has more than 10 million Indian investors which is growing fast as the number of exchange apps in the Indian market increase with the ease of trading in crypto. In the current research work Comparative Analysis of Crypto App in India (CACAI) has been performed and results exceed the expectations.

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Algorithms for Globally-Optimal Secure Signaling over Gaussian MIMO Wiretap Channels Under Interference Constraints

arXiv

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arXiv 2020年

作者： Dong, Limeng Loyka, Sergey Li, Yong Ministry of Education Key Lab for Intelligent Networks and Network Security School of Information and Communications Engineering Xi’an Jiaotong University Xi’anShaanxi710049 China School of Electrical Engineering and Computer Science University of Ottawa Canada School of Electronics and Information Northwestern Polytechnical University Xian China

Multi-user Gaussian MIMO wiretap channel is considered under interference power constraints (IPC), in addition to the total transmit power constraint (TPC). Algorithms for global maximization of its secrecy rate are proposed. Their convergence to the secrecy capacity is rigorously proved and a number of properties are established analytically. Unlike known algorithms, the proposed ones are not limited to the MISO case and are proved to converge to a global rather than local optimum in the general MIMO case, even when the channel is not degraded. In practice, the convergence is fast as only a small to moderate number of Newton steps is required to achieve a high precision level. The interplay of TPC and IPC is shown to result in an unusual property when an optimal point of the max-min problem does not provide an optimal transmit covariance matrix in some (singular) cases. To address this issue, an algorithm is developed to compute an optimal transmit covariance matrix in those singular cases. It is shown that this algorithm also solves the dual (nonconvex) problems of globally minimizing the total transmit power subject to the secrecy and interference constraints;it provides the minimum transmit power and respective signaling strategy needed to achieve the secrecy capacity, hence allowing power savings. Copyright © 2020, The Authors. All rights reserved.

关键词： Covariance matrix

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Blockchain-Based Secure Authentication Scheme for Medical Data Sharing

Blockchain-Based Secure Authentication Scheme for Medical Da...

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2019国际计算机前沿大会

作者： Xu Cheng Fulong Chen Dong Xie Hui Sun Cheng Huang Zhuyun Qi School of Computer and Information Anhui Normal University Anhui Provincial Key Lab of Network and Information Security School of Electronic and Computer Engineering Peking University

Data security is vital for medical cyber physical system(MCPS).The decentralization feature of blockchain is helpful to solve the problem that the secure authentication process is highly dependent on the trusted third party and implement data security *** this paper,the blockchain technology is used to describe the security requirements in authentication process.A network model of MCPS based on blockchain is *** analysis of medical data storage architecture,data was ensured not to be tampered and *** security threat was eliminated by bilinear mapping in the authentication process of medical data providers and *** credibility problem of the trusted third party was avoided and the two-way authentication was realized between the hospital and blockchain *** security analysis and performance test were carried out to verify the security and related performance of the authentication *** results show that the MCPS based on blockchain realizes medical treatment data sharing,and meets safety requirements in the security authentication phase.

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Bipartite graph embedding via mutual information maximization

arXiv

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arXiv 2020年

作者： Cao, Jiangxia Lin, Xixun Liu, Luchen Liu, Tingwen Guo, Shu Wang, Bin Institute of Information Engineering Chinese Academy of Sciences & School of Cyber Security University of Chinese Academy of Sciences China National Computer Network Emergency Response Technical Team Coordination Center of China China Xiaomi AI Lab Xiaomi Inc China

Bipartite graph embedding has recently attracted much attention due to the fact that bipartite graphs are widely used in various application domains. Most previous methods, which adopt random walk-based or reconstruction-based objectives, are typically effective to learn local graph structures. However, the global properties of bipartite graph, including community structures of homogeneous nodes and long-range dependencies of heterogeneous nodes, are not well preserved. In this paper, we propose a bipartite graph embedding called BiGI to capture such global properties by introducing a novel local-global infomax objective. Specifically, BiGI first generates a global representation which is composed of two prototype representations. BiGI then encodes sampled edges as local representations via the proposed subgraph-level attention mechanism. Through maximizing the mutual information between local and global representations, BiGI enables nodes in bipartite graph to be globally relevant. Our model is evaluated on various benchmark datasets for the tasks of top-K recommendation and link prediction. Extensive experiments demonstrate that BiGI achieves consistent and significant improvements over state-of-the-art baselines. Detailed analyses verify the high effectiveness of modeling the global properties of bipartite graph. Copyright © 2020, The Authors. All rights reserved.

关键词： Machine learning

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