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High-speed encrypted traffic classification by using payload features

Digital communications and Networks 2025年第2期11卷 412-423页

作者： Xinge Yan Liukun He Yifan Xu Jiuxin Cao Liangmin Wang Guyang Xie School of Cyber Science and Engineering Southeast UniversityNanjing 211189China Nanjing Huafei Data Technology Co. Ltd.Nanjing 210019China School of Computer Science and Communication Engineering Jiangsu UniversityZhenjiang 212013China

Traffic encryption techniques facilitate cyberattackers to hide their presence and *** classification is an important method to prevent network ***,due to the tremendous traffic volume and limitations of computing,most existing traffic classification techniques are inapplicable to the high-speed network *** this paper,we propose a High-speed Encrypted Traffic Classification(HETC)method containing two ***,to efficiently detect whether traffic is encrypted,HETC focuses on randomly sampled short flows and extracts aggregation entropies with chi-square test features to measure the different patterns of the byte composition and distribution between encrypted and unencrypted ***,HETC introduces binary features upon the previous features and performs fine-grained traffic classification by combining these payload features with a Random Forest *** experimental results show that HETC can achieve a 94%F-measure in detecting encrypted flows and a 85%–93%F-measure in classifying fine-grained flows for a 1-KB flow-length dataset,outperforming the state-of-the-art comparison ***,HETC does not need to wait for the end of the flow and can extract mass computing *** average time for HETC to process each flow is only 2 or 16 ms,which is lower than the flow duration in most cases,making it a good candidate for high-speed traffic classification.

关键词： Traffic classification Flow analysis Information entropy Machine learning Randomness test

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Reinforcement Learning Based Edge Microservice Migration Strategy under Resource Constraints 5

Reinforcement Learning Based Edge Microservice Migration Str...

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5th International science and technology Conference Modern Network Technologies, MoNeTec 2024

作者： Dong, Mengxue Huo, Dongkun Zhang, Hong Zhang, Yan Hao, Yixue Hu, Long Chen, Min Huazhong University of Science and Technology School of Computer Science & Technology Wuhan China South China University of Technology School of Computer Science & Engineering Guangzhou China National University of Defense Technology College of Information and Communication Changsha China

ISBN: (纸本)9798350369007

Service migration can solve the issue of frequent user switching caused by the restricted coverage of edge cloud, which is currently a major focus of research. Simultaneously, microservice architecture gains traction in businesses for its benefits in maintainability and scalability. Existing migration strategies mainly target monolithic services, overlooking the complexities of microservice migration scenarios. Considering the limited edge cloud resources and the flexible combination of microservices to be migrated individually in the microservice migration process, we construct a microservice migration system architecture to solve this problem with the goal of minimizing latency and energy consumption. We transform the microservice migration problem to a Markov decision process and propose an intelligent microservice migration algorithm under resource constraints based on reinforcement learning algorithm. Simulation results indicate that our algorithm reduces user request latency and system energy consumption, while enhancing QoS compared to current approaches. © 2024 IEEE.

关键词： Adversarial machine learning

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A Novel Construction of Updatable Identity-Based Hash Proof System and Its Applications

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Chinese Journal of Electronics 2023年第3期32卷 564-576页

作者： QIAO Zirui ZHOU Yanwei YANG Bo ZHANG Wenzheng ZHANG Mingwu School of Computer Science Shaanxi Normal University State Key Laboratory of Cryptology Science and Technology on Communication Security Laboratory Henan Key Laboratory of Network Cryptography Technology School of Computere Hubei University of Technology

In the previous works, to further provide the continuous leakage resilience for the identity-based encryption scheme, a new cryptography primitive, called updatable identity-based hash proof system(U-IB-HPS),was proposed. However, most of the existing constructions have some deficiencies, they either do not have perfect key update function or the corresponding security with tight reduction relies on a non-static complexity assumption. To address the above problems, a new construction of U-IB-HPS is created, and the corresponding security of our system is proved based on the static complexity assumption. Also, the corresponding comparisons and analysis of performances show that our proposal not only achieves the perfect key update function and the anonymity, but also has the tight security reduction. In additional, our proposal achieves the same computational efficiency as other previous systems. To further illustrate the practical function of U-IB-HPS, a generic method of non-interactive data authorization protocol with continuous leakage resilience is designed by employing U-IB-HPS as an underlying tool, which can provide continuous leakage-resilient data authorization function for the cloud computing. Hence, the application field of U-IB-HPS is further extended through our study.

关键词： Authorization Cloud computing Protocols Identity-based encryption Complexity theory Computational efficiency Proposals

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The synergistic interplay of artificial intelligence and digital twin in environmentally planning sustainable smart cities:A comprehensive systematic review

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Environmental science and Ecotechnology 2024年第4期20卷 79-104页

作者： Simon Elias Bibri Jeffrey Huang Senthil Kumar Jagatheesaperumal John Krogstie Swiss Federal Institute of Technology Lausanne(EPFL) Institute of Computer and Communication Sciences(IINFCOM)School of ArchitectureCivil and Environmental Engineering(ENAC)Media and Design Laboratory(LDM)1015LausanneSwitzerland Department of Electronics&Communication Engineering Mepco Schlenk Engineering CollegeSivakasi626005TamilnaduIndia Department of Computer Science Norwegian University of Science and Technology(NTNU)TrondheimNorway

The dynamic landscape of sustainable smart cities is witnessing a significant transformation due to the integration of emerging computational technologies and innovative *** advancements are reshaping data-driven planning strategies,practices,and approaches,thereby facilitating the achievement of environmental sustainability *** transformative wave signals a fundamental shift d marked by the synergistic operation of artificial intelligence(AI),artificial intelligence of things(AIoT),and urban digital twin(UDT)*** previous research has largely explored urban AI,urban AIoT,and UDT in isolation,a significant knowledge gap exists regarding their synergistic interplay,collaborative integration,and collective impact on data-driven environmental planning in the dynamic context of sustainable smart *** address this gap,this study conducts a comprehensive systematic review to uncover the intricate interactions among these interconnected technologies,models,and domains while elucidating the nuanced dynamics and untapped synergies in the complex ecosystem of sustainable smart *** to this study are four guiding research questions:*** theoretical and practical foundations underpin the convergence of AI,AIoT,UDT,data-driven planning,and environmental sustainability in sustainable smart cities,and how can these components be synthesized into a novel comprehensive framework?*** does integrating AI and AIoT reshape the landscape of datadriven planning to improve the environmental performance of sustainable smart cities?*** can AI and AIoT augment the capabilities of UDT to enhance data-driven environmental planning processes in sustainable smart cities?*** challenges and barriers arise in integrating and implementing AI,AIoT,and UDT in data-driven environmental urban planning,and what strategies can be devised to surmount or mitigate them?Methodologically,this study involves a rigorous analysis and synthesis of studies publis

关键词： Sustainable smart cities Artificial intelligence Artificial intelligence of things Urban digital twin Data-driven urban planning Environmental planning Environmental sustainability

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Automated object recognition in high-resolution optical remote sensing imagery

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National science Review 2023年第6期10卷 38-41页

作者： Yazhou Yao Tao Chen Hanbo Bi Xinhao Cai Gensheng Pei Guoye Yang Zhiyuan Yan Xian Sun Xing Xu Hai Zhang School of Computer Science and Engineering Nanjing University of Science and Technology Aerospace Information Research Institute Chinese Academy of Sciences School of Electronic Electrical and Communication Engineering University of Chinese Academy of Sciences Key Laboratory of Network Information System Technology (NIST) Aerospace Information Research Institute Chinese Academy of Sciences Department of Computer Science and Technology Tsinghua University School of Computer Science and Engineering University of Electronic Science and Technology of China Pazhou Laboratory (Huangpu) School of Mathematics Northwest University

INTRODUCTION With the rapid development of remote sensing technology,high-quality remote sensing images have become widely *** automated object detection and recognition of these images,which aims to automatically locate objects of interest in remote sensing images and distinguish their specific categories,is an important fundamental task in the *** provides an effective means for geospatial object monitoring in many social applications,such as intelligent transportation,urban planning,environmental monitoring and homeland security.

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Machine Learning in Tennis Match Analysis: Predicting Score Point Victor and Momentum Shift 5

Machine Learning in Tennis Match Analysis: Predicting Score ...

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5th International Conference on Machine Learning and computer Application, ICMLCA 2024

作者： Hu, Jinming Yang, Xiaohua Huang, Zixuan Xie, Jinqi School of Computer and Communication Engineering Changsha University of Science & Technology Changsha China School of Mathematics and Computer Science Shanxi Normal University Taiyuan China

ISBN: (纸本)9798331530334

In tennis and other competitive sports, momentum plays a pivotal role, where actions like consecutive scoring can enhance a player's momentum and increase his chances of winning the match. Quantifying momentum and predicting match outcomes in real-time are critical for both scientific training and strategic decision-making in the sports industry. However, traditional forecasting approaches often overlook the cumulative nature of time-series data and lack quantitative analysis of the dynamic properties influencing match outcomes. In this study, we compare seven machine learning models across two key tasks: predicting the winner of the next point and identifying the critical moment of momentum transition. We introduce a novel momentum formula to quantify the win/loss trends throughout a match. Our experiments using data from the 2023 Wimbledon Championships, demonstrate up to 70% accuracy in predicting point winners using logistic regression (LR) and up to 97% accuracy in detecting momentum shifts via a light gradient boosting machine (LGBM). These findings underscore the significance of momentum in tennis and offer valuable insights for performance optimization and competitive strategy development. © 2024 IEEE.

关键词： Tennis

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Comment Analyzer by Sentimental Analysis through Natural Language Processing 10

Comment Analyzer by Sentimental Analysis through Natural Lan...

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10th International Conference on communication and Signal Processing, ICCSP 2024

作者： Chinnasamy, P. Ayyasamy, Ramesh Kumar Madhukar, Gadde Karthik, Gaddamidi Bhargav, Tanneru Nayak, Dungavath Yuva Kiran Mlr Institute of Technology Department of Computer Science and Engineering Hyderabad India Faculty of Information and Communication Technology Kampar Malaysia

ISBN: (纸本)9798350353068

Comment analyzers were widely employed across industries for sentiment analysis, social media monitoring, and customer feedback evaluation. These tools facilitated insight into public opinions and sentiments expressed in comments on various platforms. Sentiment analysis is a natural language processing technique that determines the emotional tone of the text, helping to categorize it as positive, negative, or neutral, making it valuable for understanding public opinion and customer feedback. With the explosive increase of comments, it is difficult to analyze them manually. The issue arises because online content is huge and complicated, making it tough to grasp the subtle emotions and attitudes people have in their comments. This mystery surrounding digital conversations needs a solution: a Comment Analyzer with Sentiment Analysis. Text categorization in the form of sentiment analysis incorporates NLP, machine learning, data mining, information retrieval, Power BI for data analysis, and other study areas. These limitations highlight the need for more sophisticated sentiment analysis techniques, such as the Vader sentiment analysis provided in this study, to overcome existing system shortcomings and increase sentiment classification accuracy. The Comment Analyzer using Sentiment Analysis represents a pioneering approach to unraveling the cryptic sentiments embedded within the myriad comments and discussions that saturate the digital sphere. We are using data sets such as YouTube video comments and Ecommerce Product comments. © 2024 IEEE.

关键词： Sentiment analysis

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Improving Micro-expression Recognition using Multi-sequence Driven Face Generation

Improving Micro-expression Recognition using Multi-sequence ...

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2025 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2025

作者： Chen, Yuan Zhong, Chongju Huang, Pinyi Cai, Wangyang Wang, Lei School of Computer Science and Engineering Central South University China School of Computer and Communication Engineering Changsha University of Science and Technology China

ISBN: (纸本)9798350368741

Micro-expression (ME) recognition holds great potential for revealing true human emotions. A significant barrier to effective ME recognition is the lack of sufficient annotated ME video data because MEs are subtle and involuntary facial expressions that are very hard to capture. To address this issue, data augmentation techniques, such as ME migration based on a driven video, have been employed to enrich training samples. Considering that MEs can be complex facial movements involving multiple action unit (AU) changes, we propose a novel ME generation approach that enables the creation of more realistic facial sequences by fusing MEs from multiple videos rather than just single driven video. To enhance the effectiveness of multi-sequence ME transfer, we adapt the thin plate spline motion model and improve traditional face alignment methods to better suit the model, facilitating multi-sequence driven ME generation. In our experiments, we conduct a downstream ME recognition task using models trained on our augmented ME sequences to demonstrate the effectiveness of our approach on the SAMM, SMIC, and CASME II datasets. The results confirm that our proposed approach outperforms state-of-the-art (SOTA) augmentation and generation methods in terms of F1 score and recognition accuracy. © 2025 IEEE.

关键词： face alignment micro-expression generation thin plate spline motion model video fusion

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End-to-End Human Pose Reconstruction from Radar Signals Based on Deep Residual Networks 2

End-to-End Human Pose Reconstruction from Radar Signals Base...

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2nd IEEE International Conference on Signal, Information and Data Processing, ICSIDP 2024

作者： Wang, Tao Song, Yongkun Jin, Tian Dai, Yongpeng Yan, Tianxing Zhang, Ke Changsha University of Science and Technology Computer and Communication Engineering Institute Changsha China National University of Defense Technology College of Electronic Science and Technology Changsha China

ISBN: (纸本)9798331515669

The reconstruction of human pose using radar primarily focuses on effectively estimating the position and pose of a target based on radar echo signals. Compared to traditional optical methods, radar signals can operate under limited lighting conditions, in the presence of occlusions, or beyond the line of sight. This paper proposes an end-to-end human pose reconstruction method based on a deep residual network. This method bypasses traditional imaging and detection algorithms, directly extracting amplitude and phase features from radar echo signals, and outputs the target's azimuth, distance, and pose information. Experimental results verify the effectiveness of the algorithm. © 2024 IEEE.

关键词： Radar target recognition

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VR Simulation: Advancing Practical Skills in computer science Education 18

VR Simulation: Advancing Practical Skills in Computer Scienc...

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18th European Conference on Games Based Learning, ECGBL 2024

作者： Alhumairi, Ali Ebrahimi, Reza Sahli, Nabil Fakhrulddin, Alya Computer Science Department German University of Technology in Oman Muscat Oman Communication Technology Duisburg Essen University Germany

ISBN: (纸本)9781917204194

This study presents the successful integration of Virtual Reality (VR) tools as an element in computer science curriculum at German University of technology, Oman. The research study investigates the use of MyScore, a VR application developed by RWTH Aachen University - Teaching & Research Field Engineering Hydrology as an environment for computer hardware assembly and troubleshooting exercises. The VR simulation utilized in this study acts as a gamified environment, incorporating elements like scorekeeping and interactive challenges to enhance practical learning in computer science, akin to game-based strategies that engage and motivate students. Over of some weeks, the project involved seven students and one tutor in immersive learning sessions to develop applied skills computer hardware assembly with VR technology over conventional teaching methods. Structured surveys and direct observations were used for data collection through students' interactions with the VR sessions. We also evaluated the students learning experiences as well as the usability of technology. The results showed that the user-friendliness of the VR interface and its ability to accurately simulate real-world tasks associated with computer assembly received both positive and negative reactions. While some students praised the technology for being pretty cutting-edge, some criticized it as unrealistic or non-interactive. We also received complaints that ranged from actually moving around in the virtual space to navigating only through teleportation spark points. Specifically, two students gotten motion sickness which is a well-known obstacle associated with VR environments and consequently left the sessions prematurely. The feedback of the instructor pointed towards that setting up the VR equipment is straightforward and described some potentials methods. Still, a call for more reliability in simulations and better interfaces began to surface as nevertheless less controversial agenda items. Howev

关键词： Students

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