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25th IEEE International Conferences on High Performance computing and Communications, 9th International Conference on Data Science and Systems, 21st IEEE International Conference on Smart City and 9th IEEE International Conference on Dependability in Sensor, Cloud and Big Data Systems and Applications, HPCC/DSS/SmartCity/DependSys 2023

作者： Sun, Yu Liu, Guangqi Han, Xiaohui Zuo, Wenbo Liu, Weihua Qilu University of Technology Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center National Supercomputer Center in Jinan Shandong Academy of Sciences Jinan China Shandong Provincial Key Laboratory of Computer Networks Shandong Fundamental Research Center for Computer Science Jinan China Quancheng Provincial Laboratory Jinan China

ISBN: (纸本)9798350330014

Recently, the rapid advancement of communication technology has undoubtedly improved people's lives. Unfortunately, this progress has also given rise to a significant issue: the proliferation of phishing websites. Regrettably, phishing web sites have now emerged as one of the primary threats to cybersecurity. While there have been extensive efforts to develop anti-phishing techniques, many of these approaches focus solely on a single modality of information, such as the website's URL, HTML source code, or visual features. Given the growing sophistication of phishing attacks, relying on just one modality of information is no longer sufficient to accurately identify phishing websites. To tackle this challenge, our research aims to leverage the complementarity of various modalities to enhance phishing website detection. In this paper, we introduce a multi-modal framework called FusionNet to identify phishing web pages. This framework utilizes three distinct information modalities: URLs, HTML source codes, and visual features. Specifically, our approach first designs specific representation learning architectures tailored to each modality's unique properties. Subsequently, we incorpo-rate an attention mechanism to merge these representations, thereby exploiting the synergies between the multi-modal data. The learned feature representations are more discriminative, contributing to significantly improved phishing website detection accuracy. To evaluate the performance of FusionNet, we collect a dataset comprising phishing webpages, each sample contains all three modalities-URLs, HTML source codes, and visual features. Our extensive experiments conducted on this dataset demonstrate that FusionNet outperforms state-of-the-art methods in terms of both robustness and accuracy. © 2023 IEEE.

关键词： Websites

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Evolutionary Multitasking Based on Team Learning Strategy 6

Evolutionary Multitasking Based on Team Learning Strategy

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6th Asian Conference on Artificial Intelligence Technology, ACAIT 2022

作者： Li, Wei Xu, Qingzheng Gao, Xinyu Wang, Lei Xi'an University of Technology School of Computer Science and Engineering Xi'an China National University of Defense Technology College of Information and Communication Wuhan China Shaanxi Key Laboratory for Network Computing and Security Technology Xi'an China

ISBN: (纸本)9781665453110

Multi-factorial optimization (MFO) is a popular optimization mechanism recently, which aims to optimize multiple tasks in a single run. Generally, the multi-factorial optimization algorithm uses the random learning strategy to generate offspring, which leads to an inefficient exploration ability of the algorithm. To address this problem, this paper proposed a simple and effective strategy called team learning strategy (TLS). The proposed learning strategy divided the population into excellent team and ordinary team. Different teams employ different learning strategies. Moreover, nine MFO problems were used to assess the effectiveness of the proposed strategy. The experimental results show that the team learning strategy can improve the performance of the algorithm. © 2022 IEEE.

关键词： Evolutionary algorithms

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Dimensionality Reduction of Massive I/O Log Data Flow in power System

Dimensionality Reduction of Massive I/O Log Data Flow in Pow...

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2020 International Conference on Communications, information System and Computer Engineering, CISCE 2020

作者： Zhang, Bo Xi, Zesheng Zhang, Tao Ma, Yuanyuan Shao, Zhipeng Li, Hongfa Global Energy Interconnection Research Institute Institute of Information and Communication Nanjing China State Grid Key Laboratory of Information and Network Security Nanjing Jiangsu China State Grid Fujian Electric Power Co. Ltd Information Telecommunication Branch China

ISBN: (纸本)9781728197616

Every day, the power system receives massive I/O logs. The amount of data in these logs is so large that it takes huge computational resources to analyze. Therefore, it is necessary to reduce the size of the massive I/O logs and only analyze the key log data, thereby reducing the workload of invalid analysis. This paper takes the I/O log of the substation as the research object, and studies the dimension reduction method of the massive I/O data flow log, which reduces the computational load brought by the high-dimensional I/O data flow log data and reduces the massive I/O data flow log. This paper proposes a method of secondary dimensionality reduction. Firstly, the high dimensional I/O log data stream is classified, so that the data is transformed from high-dimensional to low-dimensional. Then, the dimension is reduced again in each category, so that the most simplified massive I/O logs are achieved. Through theoretical analysis, we can come to the conclusion that the computational time complexity of the data after dimension reduction is reduced by more than 80%. © 2020 IEEE.

关键词： Data reduction

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Research on security assessment and control technology for power mobile terminal

Research on security assessment and control technology for p...

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2022 International Conference on Computer Application and information security, ICCAIS 2022

作者： Li, Yongfa Li, Shu Chen, Mu Chen, Yating Cao, Linjing Liu, Yang Sun, Yizhen State Grid Information Communication Company of Hunan Electric Power Corporation Hunan Changsha410004 China State Grid Key Laboratory of Information Network Security Institute of Information and Communication Global Energy Interconnection Research Institute Jiangsu Nanjing210003 China

ISBN: (纸本)9781510663459

With the rapid development of mobile Internet and the transformation of information technology in power energy enterprises, the demand for mobile office is increasing rapidly. However, the network security risks and attacks faced by mobile applications and terminals are also increasing, which brings hidden troubles to the safe production of enterprises. Therefore, this paper proposes a security assessment and control method for power mobile terminals, designs a mobile security protection system, puts forward indicators and methods for terminal security risk assessment, and designs a control mode for terminal risks, which effectively improves the security protection capability and emergency disposal ability of power mobile terminals, and helps the stable operation of power grid and ensure energy safety and reliability. © 2023 SPIE.

关键词： network security

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Traffic Engineering in Dynamic Hybrid Segment Routing networks

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Computers, Materials & Continua 2021年第7期68卷 655-670页

作者： Yingya Guo Kai Huang Cheng Hu Jiangyuan Yao Siyu Zhou College of Mathematics and Computer Science Fuzhou UniversityFuzhou350000China Fujian Key Laboratory of Network Computing and Intelligent Information Processing Fuzhou UniversityFuzhou350000China Key Laboratory of Spatial Data Mining&Information Sharing Ministry of EducationFuzhou350003China School of Information Science and Technology Guangdong University of Foreign StudiesGuangzhou510006China School of Computer Science and Cyberspace Security Hainan UniversityHaiKou570228China Tandon School of Engineering New York UniversityNew York10012USA Department of Computing Hong Kong Polytechnic UniversityHong Hom999077Hong Kong

The emergence of Segment Routing(SR)provides a novel routing paradigm that uses a routing technique called source packet *** SR architecture,the paths that the packets choose to route on are indicated at the ingress *** with shortest-path-based routing in traditional distributed routing protocols,SR can realize a flexible routing by implementing an arbitrary flow splitting at the ingress *** the advantages of SR,it may be difficult to update the existing IP network to a full SR deployed network,for economical and technical *** partial of the traditional IP network to the SR network,thus forming a hybrid SR network,is a preferable *** the traffic is dynamically changing in a daily time,in this paper,we propose a Weight Adjustment algorithm WASAR to optimize routing in a dynamic hybrid SR *** algorithm can be divided into three steps:firstly,representative Traffic Matrices(TMs)and the expected TM are obtained from the historical TMs through ultrascalable spectral clustering ***,given the network topology,the initial network weight setting and the expected TM,we can realize the link weight optimization and SR node deployment optimization through a Deep Reinforcement Learning(DRL)***,we optimize the flow splitting ratios of SR nodes in a centralized online manner under dynamic traffic demands,in order to improve the network *** the evaluation,we exploit historical TMs to test the performance of the obtained routing configuration in *** extensive experimental results validate that our proposed WASAR algorithm has superior performance in reducing Maximum Link Utilization(MLU)under the dynamic traffic.

关键词： Traffic engineering routing optimization segment routing deep reinforcement learning ultra-scalable spectral clustering

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LESaET: Low-Dimensional Embedding Method for Link Prediction Combining Self-Attention and Enhanced-TuckER

LESaET: Low-Dimensional Embedding Method for Link Prediction...

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2024 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2024

作者： Ding, Lichao Zhao, Jing Lu, Kai Hao, Zenghao Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center Jinan China Shandong Engineering Research Center of Big Data Applied Technology Faculty of Computer Science and Technology Jinan China Shandong Provincial Key Laboratory of Computer Networks Shandong Fundamental Research Center for Computer Science Jinan China

ISBN: (纸本)9781665410205

Knowledge graphs (KGs) provide a structured representation of the real world through entity-relation triples. However, current KGs are often incomplete, typically containing only a small fraction of all possible facts. This involves inferring missing content from existing information, a task known as link prediction. Existing methods in the field of link prediction struggle with controlling the dimensionality of embedding vectors or suffer from overly complex models. In order to tackle these challenges, we introduce a method in this paper, named Low-Dimensional Embedding Method for Link Prediction Combining Self-Attention and Enhanced-TuckER (LESaET). LESaET leverages both self-attention mechanisms and tensor factorization to learn expressive contextual-enhanced representations of KGs. Specifically, LESaET employs the multi-head self-attention mechanism of Transformer as an encoder to capture the mutual information between entities and relationships, and utilizes Enhanced-TuckER as a decoder, ultimately achieving expressive low-dimensional embeddings for link prediction tasks. LESaET demonstrates competitive performance compared to advanced methods on standard datasets. © 2024 IEEE.

关键词： Prediction models

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An energy aware data-centric routing algorithm for WSNs with high energy efficiency

An energy aware data-centric routing algorithm for WSNs with...

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4th International Conference on information Technology for Manufacturing Systems, ITMS 2013

作者： Du, Tao Qu, Shou Ning Xu, Jing Wen Shandong Provincial Key Laboratory of Network based Intelligent Computing University of Jinan China School of Information Science and Engineering University of Jinan China Jinan Thermal Power Co. Lid China

ISBN: (纸本)9783037858783

In WSNs, energy efficiency is one of the most important factors to influence its performance, and well designed routing algorithm can obviously improve the energy efficiency. Because data-centric routing algorithm is easy to be deployed and has more robust in application, many new algorithms are proposed based on this type. In this paper, some typical existing routing algorithms are analyzed, and the characters of these algorithms are introduced. According to these analyses an energy aware data-centric routing algorithm named EADC is proposed. In EADC, the nodes' residual energy is considered when transmitting route is selected. And to ensure nodes' energy information acute, a special package head and a link storing neighbor nodes are defined to update nodes' energy information when transmitting message. Through these designs, the route can be dynamic adjusted to make the energy consumption more reasonable. At last, EADC is compared with other typical routing algorithms in a series of experiments, and the experiments' result proves that EADC has obviously improved the WSNs' energy efficiency. © (2013) Trans Tech Publications, Switzerland.

关键词： Energy efficiency

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GA-Net: Gated Attention Mechanism Based Global Refinement network for Image Inpainting 29

GA-Net: Gated Attention Mechanism Based Global Refinement Ne...

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29th IEEE International Conference on Parallel and Distributed Systems, ICPADS 2023

作者： Qiu, Ran Zhao, Shengrong Liang, Hu Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center Jinan China Shandong Engineering Research Center of Big Data Applied Technology Faculty of Computer Science and Technology Jinan China Shandong Fundamental Research Center for Computer Science Shandong Provincial Key Laboratory of Computer Networks Jinan China

ISBN: (纸本)9798350330717

Underwater images are often affected by problems such as light attenuation, color distortion, noise and scattering, resulting in image defects. A novel image inpainting method is proposed to intelligently predict and fill damaged areas for complete and continuous visualization of the image. First, in order to effectively solve the problem of color distortion caused by light refraction in underwater environments, the improved gated attention mechanism is used. This mechanism improves the local details by learning and weighting the important features of the image. Second, gated convolution automatically determines the degree of restoration for each pixel based on local features of the original image. It eliminates distractions such as low contrast and scattering, retaining more original detailed information. By doing so, image inpainting techniques improve the quality and visualization of underwater images. © 2023 IEEE.

关键词： Gated convolution Image inpainting Underwater images

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Multilingual Knowledge Graph Completion via Multimodal Decouple and Relation-based Ensemble Inference 29

Multilingual Knowledge Graph Completion via Multimodal Decou...

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29th IEEE International Conference on Parallel and Distributed Systems, ICPADS 2023

作者： Liu, Xiaojing Jiang, Xuesong Yi, Fengge Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center Jinan China Shandong Engineering Research Center of Big Data Applied Technology Faculty of Computer Science and Technology Jinan China Shandong Fundamental Research Center for Computer Science Shandong Provincial Key Laboratory of Computer Networks Jinan China

ISBN: (纸本)9798350330717

The objective of Multimodal Knowledge Graph Completion (MKGC) is to forecast absent entities within a knowledge graph by leveraging additional textual and visual modalities. Existing studies commonly utilize a singular relationship embedding to depict all modalities within an entity pair, thus connecting several relationships derived from diverse modalities. However, this coupling may introduce interference from conflicting information between modalities, as the relationships between modalities for a given entity pair can be contradictory. Moreover, existing Ensemble Inference methods fail to dynamically adjust modal weights based on their differences and importance, despite the varying contributions of different modalities. In this paper, we propose the Multimodal Decouple and Relation-based Ensemble inference (MDRE) model. For each modality, we construct corresponding relationship embeddings and build separate triple representations to avoid interferences among modalities. During the training phase, we employ confidence-constrained training with temperature scaling to alleviate conflicting information in textual and visual modalities. For inference, we utilize the Relation-based Ensemble Inference method to adjust modal weights at the relationship level, thus achieving improved prediction results. Experimental results on two datasets demonstrate that MDRE outperforms existing single-modal and multimodal knowledge graph completion methods in terms of performance. © 2023 IEEE.

关键词： knowledge graph knowledge graph completion multimodal fusion

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Design of power Grid Cyber security Framework Based on Whole Life Cycle Management 2

Design of Power Grid Cyber Security Framework Based on Whole...

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2020 2nd International Conference on Computer Modeling, Simulation and Algorithm, CMSA 2020

作者： He, Jindong Wu, Dan Zhao, Zhichao Guo, Qian State Grid Fujian Electric Power Research Institute Fuzhou China Global Energy Interconnection Research Institute Co. Ltd State Grid Key Laboratory of Information and Network Security Nanjing China

The whole process security of power information system is the key to make power grid operation safe and stable. Firstly, the concept and characteristics of whole life cycle management (WLCM) are summarized by this paper systematically. Secondly, the power network security architecture based on full life cycle security management is constructed, which is designed to protect the cyber security of power grid from three aspects: control flow, technical support system and mechanism guarantee system. Thirdly, the cyber security's management and control flow of power grid, the technical support system of power grid cyber security (PGIS) and the mechanism guarantee system based on life cycle management are proposed. And the control flow, technical support and guarantee mechanism were designed in detail. Finally, the method proposed in this paper is carried out in a provincial power-grid company. The results show that this method can significantly reduce the power network security risk and improve the power grid network security level, which is of great significance to the operation safety of the power grid and has strong engineering application value. © Published under licence by IOP Publishing Ltd.

关键词： network security

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