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检索条件"任意字段=2023 International Conference on Computer Network Security and Software Engineering, CNSSE 2023"

共 6774 条记录，以下是81-90 订阅

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Research and Application of E-commerce Marketing Fraud Detection Method Based on Graph Neural network 24

Research and Application of E-commerce Marketing Fraud Detec...

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2nd international conference on Artificial Intelligence, Systems and network security, AISNS 2024

作者： Zhu, Hui Huang, Zihao Zhong, Weijie Wang, Zhenyu School of Economics and Trade Guangdong Mechanical &Electrical Polytechnic Guangzhou China School of Software Engineering South China University of Technology Guangzhou China School of Software Engineering South China University of Technology Guangdong Guangzhou China

ISBN: (纸本)9798400711237

In recent years, graph-based E-commerce Fraud detection methods have received more and more attention, but there are still some problems. Firstly, fraudulent users only account for a small part of active users, and the imbalance between classes in the graph leads to model deviation and affect the effectiveness of E-commerce Fraud detection. At the same time, the existing methods have ignored the sparse connections between fraudulent entities. In addition, most existing methods rely on the cost-sensitive matrix given by the expert experience and cannot adapt to learn the optimal cost transformation according to the data distribution. In this paper, we propose a cost sensitive graph neural network based on adaptive neighbor sampling, termed as CNSGNN. Firstly, the model designs a label-aware adaptive neighbor selector, using reinforcement learning to train a suitable sampling threshold, sampling neighbors by label similarity, thus alleviating the imbalance in the graph initially. Then, similarity scores are used to enhance the connection between fraudulent entities and help the sharing and transmission of characteristic information of fraudulent nodes. After that, GNN is used for information aggregation, and the cost-sensitive matrix optimizer is used to learn the optimal cost transformation to improve the classification effect. The experimental results show that the proposed model is superior to the current advanced baseline methods. © 2024 Copyright held by the owner/author(s).

关键词： Graph neural networks

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Optimizing Resource Allocation in the Internet of Vehicles: An Intelligent Vehicle-Edge-Cloud Collaboration Approach 20th

Optimizing Resource Allocation in the Internet of Vehicle...

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20th IFIP WG 10.3 international conference on network and Parallel Computing, NPC 2024

作者： Chen, Weijie Lin, Li Xiong, Jinbo Lin, Jiayi Huang, Ruihong Wang, Xing College of Computer and Cyber Security Fujian Normal University Fuzhou China Fujian Provincial University Engineering Research Center of Big Data Analysis and Application Fuzhou China

ISBN: (纸本)9789819628636

The proliferation of the Internet of Vehicles (IoV) has spurred the development of computationally intensive and latency-sensitive applications in vehicles. However, limited onboard computing resources hinder their execution. Vehicle edge computing addresses this by providing readily accessible resources from edge servers. However, efficient resource allocation remains a challenge due to limited edge server capacity and dynamic traffic patterns. This paper proposes a novel three-layer collaborative intelligence framework that leverages edge and cloud resources to minimize system latency in IoV. We employ a deep reinforcement learning algorithm to adapt to dynamic traffic conditions and make optimal resource allocation decisions. Extensive experiments demonstrate a significant reduction in latency (26.75%) compared to baseline methods. © IFIP international Federation for Information Processing 2025.

关键词： Deep reinforcement learning

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Bounded Collusion-Resistant Registered Functional Encryption for Circuits 30th

Bounded Collusion-Resistant Registered Functional Encryption...

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30th international conference on the Theory and Application of Cryptology and Information security

作者： Zhang, Yijian Chen, Jie He, Debiao Zhang, Yuqing East China Normal Univ Shanghai Key Lab Trustworthy Comp Sch Software Engn Shanghai Peoples R China Wuhan Univ Inst Math & AI Wuhan Peoples R China Univ Wollongong Inst Cybersecur & Cryptol Sch Comp & Informat Technol Wollongong NSW Australia Wuhan Univ Sch Cyber Sci & Engn Wuhan Peoples R China Univ Chinese Acad Sci Natl Comp Network Intrus Protect Ctr Beijing Peoples R China Hainan Univ Sch Cyberspace Secur Haikou Hainan Peoples R China

ISBN: (纸本)9789819608744;9789819608751

As an emerging primitive, Registered Functional Encryption (RFE) eliminates the key-escrow issue that threatens numerous works for functional encryption, by replacing the trusted authority with a transparent key curator and allowing each user to sample their decryption keys locally. In this work, we present a new black-box approach to construct RFE for all polynomial-sized circuits. It considers adaptive simulation-based security in the bounded collusion model (Gorbunov et al. - CRYPTO'12), where the security can be ensured only if there are no more than Q >= 1 corrupted users and Q is fixed at the setup phase. Unlike earlier works, we do not employ unpractical Indistinguishability Obfuscation (iO). Conversely, it can be extended to support unbounded users, which is previously only known from iO. Technically, our general compiler exploits garbled circuits and a novel variant of slotted Registered Broadcast Encryption (RBE), namely global slotted RBE. This primitive is similar to slotted RBE, but needs optimally compact public parameters and ciphertext, so as to satisfy the efficiency requirement of the resulting RFE. Then we present two concrete global slotted RBE from pairings and lattices, respectively. With proposed compiler, we hence obtain two bounded collusion-resistant RFE schemes. Here, the first scheme relies on k-Lin assumption, while the second one supports unbounded users under LWE and evasive LWE assumptions.

关键词： Functional Encryption Registered Encryption Bounded Collusion Model Simulation-Based security

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Anti-Packet-Loss Encrypted Traffic Classification via Masked Autoencoder 18th

Anti-Packet-Loss Encrypted Traffic Classification via Maske...

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18th international conference on Wireless Artificial Intelligent Computing Systems and Applications, WASA 2024

作者： Yang, Chen Guo, Li Gu, Zheyuan Gou, Gaopeng Lin, Xinjie Xiong, Gang Guan, Yangyang Institute of Information Engineering Chinese Academy of Sciences Beijing China School of Cyber Security University of Chinese Academy of Sciences Beijing China

ISBN: (纸本)9783031714634

Encrypted traffic classification is an important technique for network management and network security assurance. Current mainstream methods utilize machine learning and deep learning techniques for classification, and train models with complete data pre-collected in experimental environments to achieve excellent classification performance. However, real network environments are widely affected by packet loss, which causes traffic data to exhibit a different distribution compared to the training and negatively impacts existing methods. To address this problem, in this paper, we propose APMA, an Anti-Packet-loss encrypted traffic classification method based on Masked Autoencoder, which utilizes two traffic-specific mask pre-training tasks to extract generalized knowledge from large-scale unlabeled traffic, and simulates packet loss to learn robust traffic representations that are applicable to different network environments. Extensive evaluations show that APMA can be applied to a variety of classification scenarios and network environments, achieving over 90% classification accuracy even at 15% packet loss. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Packet loss

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A Review on Internet of Things (IoT) Environment Using software-Defined networking (SDN) Based on Different networks

A Review on Internet of Things (IoT) Environment Using Softw...

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international conference on Advances and Applications of Artificial Intelligence and Machine Learning, ICAAAIML 2023

作者： Bajpai, Nidhi Dhingra, Madhavi Chaurasia, Nisha CSE Department Amity University Madhya Pradesh Gwalior India IT Department NIT Jalandhar Jalandhar India

ISBN: (纸本)9789819795062

software-Defined networking (SDN) and the Internet of Things (IoT) are collaborating in a transformative way to establish connections. The Internet of Things enables remote management of equipment as well as real-time data exchange via its billions of connected devices. This is supported by SDN's provision of a comprehensive network view, which enables remote access and control for both users and operators. The growing popularity of IoT and SDN represents a paradigm change that is fundamentally altering the environment of intelligent services and interconnected devices. The profound impact that their mutual relationship has had on contemporary connectivity is concisely outlined in this review. This extensive review paper investigates the advantageous association between software-Defined networking (SDN) and the Internet of Things (IoT), throwing insight on their combined capability to enhance network performance. Underscoring the critical contribution of SDN to centralized threat detection across Wide Area networks, Access networks, and Edge networks in the IoT domain, the study emphasizes the critical role of SDN in augmenting flexibility, manageability, and security in these networks. The advent of software-Defined Internet of Things (SDIoT) becomes an innovative focal point, demonstrating the significant effects that it has on IoT networks. The review further explores the frequent coexistence of terms related to SDN and IoT networks, underscoring their broad range of applications. Furthermore, the paper critically examines the difficulties associated with supervising IoT networks and assesses recent strategies that have been implemented in the past five years to overcome these obstacles. These strategies include load balancing, energy management, provisioning security services, and defect tolerance. The article generally presents an in-depth view on the ways in which SDN enhances the effectiveness and protection of IoT networks. As a result, it provides policymak

关键词： Internet of things

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A Novel Approach Using Machine Learning for Accurate Detection of DDoS Attack in software Defined network 2nd

A Novel Approach Using Machine Learning for Accurate Detecti...

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2nd international conference on Cyber Intelligence and Information Retrieval, CIIR 2023

作者： Sharma, Hitesh Kumar Choudhury, Tanupriya Kotecha, Ketan Mahdi, Hussain Falih Dutta, Soumi Bhattacharya, Abhishek Sar, Ayan Energy Acres Bidholi Uttarakhand Bidholi India School of Computer Science University of Petroleum and Energy Studies Uttarakhand Dehradun India Pune India Pune India Department of Computer and Software Engineering University of Diyala Baquba Iraq Sister Nivedita University Chakpachuria India

ISBN: (纸本)9789819776023

A denial Of Service (DoS) attack is termed an attack when the request-receiving server or network shuts down or becomes inaccessible for service. This kind of attack is caused by flooding the target server or network with huge traffic or sending information which can trigger a vulnerability to the server and lead to server crash. Different kinds of DoS attacks can occur on a network including a classic DoS attack which is carried out by a single client machine sending tons of requests and data to a server by itself to increase its processing to the extent that no new genuine requests are answered by the server and network is ultimately unreachable. Another kind of DoS attack is termed a DDoS (Distributed Denial Of Service) attack which includes a master host machine that leverages the network of machines around it to send multiple requests to the server from different machines which act as zombie machines for the attack as the machine won’t even have an idea itself that they are being used for an attack on the server. As multiple requests and data hits the server from different locations, the server becomes unavailable for processing and leads to network failure. These zombie machines are termed botnets which are connected online and are used to overwhelm a target website with fake traffic. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Denial-of-service attack

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Measurement of Performance Parameters in the GPON Optical network 23

Measurement of Performance Parameters in the GPON Optical Ne...

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23rd Slovak-Czech-Polish Optical conference on Wave and Quantum Aspects of Contemporary Optics

作者： Trubák, Kamil Štípal, Jiří Látal, Jan Šiška, Petr Vojtěch, Josef Hristov, Hristo Department of Telecommunications Faculty of Electrical Engineering and Computer Science VSB-Technical University of Ostrava 17. listopadu 2172/15 Ostrava-Poruba708 00 Czech Republic CESNET a. l. e. Zikova 1903/4 Prague160 00 6 Czech Republic Department of Software Technologies Plovdiv University "Paisii Hilendarski" Plovdiv4000 Bulgaria

ISBN: (数字)9781510688094

ISBN: (纸本)9781510688087

With the increasing number of end users that are using multimedia services, demand for access network high bitrate systems with sufficient quality of services also increases. However, this might not always be ensured by the telecom operators, as they must perform network optimization concerning Quality of Service (QoS) and multimedia data transmission. In this work, we focused on Gigabit Passive Optical network (GPON) performance testing with the help of various tools (iPerf, RFC 6349 or ITU-T Y.1564). The Grafana software tool is used to monitor data streams. Measurements were made to limit the downstream bitrate of up to 20 end users at 100 Mbit/s. Based on the repeated measurements, an aggregation curve is modelled indicating the available bitrate with respect to the network load. © 2025 SPIE.

关键词： Internet protocols

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Comparing MAE and RMSE as Fitness of Genetic Algorithm for Optimizing Echo State network Hyperparameters with Different Probabilistic Distributions 25th

Comparing MAE and RMSE as Fitness of Genetic Algorithm for O...

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25th international conference on Intelligent Data engineering and Automated Learning

作者： de Araujo, Henrique Vaz Cardoso, Fabian Correa de Mattos, Viviane Leite Dias Borges, Eduardo Nunes Lucca, Giancarlo Dalmazo, Bruno Lopes Berri, Rafael Alceste Fed Univ Rio Grande BR-96203900 Rio Grande RS Brazil Fed Univ Rio Grande Computat Modeling Grad Program BR-96203900 Rio Grande RS Brazil Univ Rio Verde Fac Software Engn BR-75901970 Rio Verde Go Brazil Univ Catolica Pelotas BR-96015560 Pelotas RS Brazil

ISBN: (纸本)9783031777370;9783031777387

This work aims to compare Mean Absolute Error (MAE) and Root Mean Squared Error (RMSE) as fitness functions in a genetic algorithm used to optimize the hyperparameters of an Echo State network (ESN) with five probabilistic distributions. We have used financial time series data extracted from the Brazilian Stock Market. The ESN proved to be excellent for predicting time series. However, using MAE and RMSE within the genetic algorithm was ineffective since the results did not differ significantly despite the asymmetrical data distribution. Two of the five distributions stood out, Uniform and Student's t, showing low variability both with the use of RMSE and MAE, where we graphically observed that Uniform presented better prediction using the MAE fitness.

关键词： Stock price forecasting Financial Time Series ESN

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Demystifying Blockchain Scalability: Sibling Chains with Minimal Interleaving 19th

Demystifying Blockchain Scalability: Sibling Chains with Min...

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19th international conference on security and Privacy in Communication networks

作者： Ma, Jiangfeng Zhang, Xuetao Li, Xiangxue East China Normal Univ Shanghai Key Lab Trustworthy Comp Sch Software Engn Shanghai 200062 Peoples R China Shanghai Key Lab Trusted Data Circulat & Governan Shanghai 200240 Peoples R China

ISBN: (纸本)9783031649479;9783031649486

Blockchain provides alluring infrastructure for distributed ledgers supporting anonymous online payments. However, existing solutions for blockchain scalability have limitations of either being increasingly cumbersome in security analysis or inherent deficiencies (e.g., surviving on duplicate transactions). Moreover, current state-of-the-art scalable blockchains suffer from low throughput when used for larger transaction blockchains. To improve scalability, we propose sibcha, a novel protocol that equipped with k (power of 2) parallel sibling chains that correspond to k transaction pools (indexed by the rightmost log(2) k bits of transaction payers' addresses). In the protocol, i-th transaction (along with a Merkle tree path) would be announced to the i-th chain based on the rightmost log(2) k bits of the hashing determined in solving proof-ofwork (PoW) puzzle (i is the exact value in decimal format represented by the log2 k bits). To achieve parallel transactions, we design a interchain mechanism without other correlations (such as block ordering, inter-chain transactions, block updates, eventual atomicity decoupling, two-phase PoW puzzle solving, etc.), which makes sibcha considerably simpler than current state-of-the-art solutions (e.g., OHIE at IEEE S&P 2020 and Monoxide at USENIX security 2019). SibCha has much less (e.g., 1.86x similar to 3.16x) confirmation latency than OHIE. Prototype implementations also demonstrate that its throughput scales linearly with available bandwidth (1.5x that of Conflux).

关键词： Scalability

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A Solution Against Selective Jamming Attack in IEEE 802.15.4e Wireless networks 4th

A Solution Against Selective Jamming Attack in IEEE 802.15.4...

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4th international conference on Data and Information in Online Environments

作者： Wang, Xinlong Yang, Wei Hou, Chengqi Jiangxi Normal Univ Sch Software Nanchang Jiangxi Peoples R China

ISBN: (纸本)9783031807121;9783031807138

Industrial wireless technology plays a crucial role in the application of the Internet of Things (IoT). Among them, in the context of increasingly complex network topologies and the issue of control node energy consumption, the IEEE 802.15.4e protocol is a standard protocol for industrial wireless networks. The protocol incorporates Time Slotted Channel Hopping (TSCH) technology, which is widely adopted in the industrial wireless network domain due to its low latency and high reliability characteristics. However, the IEEE 802.15.4e protocol does not specify a link scheduling algorithm, leaving TSCH networks vulnerable to intelligent jamming attacks. In this paper, we explore the impact of intelligent jamming attacks on TSCH networks and emphasize the harmful consequences of this type of attack. Subsequently, a channel selection scheme for user nodes at the MAC layer of TSCH networks is proposed. Leveraging the background of game theory, the problem of link channel selection is modeled as a Stackelberg game, and a method based on stochastic selection theory is utilized to derive the game solution through the continuously updated probability matrix. Results, considering both system jamming calculations and node transmission rates, demonstrate the high effectiveness and sufficient reliability of the proposed scheme in mitigating selective intelligent jamming attacks.

关键词： TSCH Selective jamming attack Channel selection

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