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Resource investment for DDoS attack resistant SDN: a practical assessment

Science China(Information Sciences) 2023年第7期66卷 112-129页

作者： Bin YUAN Fan ZHANG Jun WAN Huan ZHAO Shui YU Deqing ZOU Qiangsheng HUA Hai JIN School of Cyber Science and Engineering Huazhong University of Science and Technology National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab Hubei Engineering Research Center on Big Data Security Shenzhen Huazhong University of Science and Technology Research Institute School of Computer Science and Technology Huazhong University of Science and Technology Cluster and Grid Computing Lab School of Computer Science University of Technology Sydney

Software-defined networks(SDNs) present a novel network architecture that is widely used in various datacenters. However, SDNs also suffer from many types of security threats, among which a distributed denial of service(DDoS) attack, which aims to drain the resources of SDN switches and controllers,is one of the most common. Once the switch or controller is damaged, the network services can be *** defense schemes against DDoS attacks have been proposed from the perspective of attack detection;however, such defense schemes are known to suffer from a time consuming and unpromising accuracy, which could result in an unavailable network service before specific countermeasures are taken. To address this issue through a systematic investigation, we propose an elaborate resource-management mechanism against DDoS attacks in an SDN. Specifically, by considering the SDN topology, we leverage the M/M/c queuing model to measure the resistance of an SDN to DDoS attacks. Network administrators can therefore invest a reasonable number of resources into SDN switches and SDN controllers to defend against DDoS attacks while guaranteeing the quality of service(QoS). Comprehensive analyses and empirical data-based experiments demonstrate the effectiveness of the proposed approach.

关键词： SDN security DDoS attacks resource management queueing theory QoS

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Embedded Speech Encoder for Low-resource Languages 15

Embedded Speech Encoder for Low-resource Languages

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15th International Conference on Information and Knowledge Technology, IKT 2024

作者： Tabatabaei, Alireza A. Sameti, Pouria Bohlooli, Ali Cyber-Physical System Lab. Faculty of Computer Engineering University of Isfahan Isfahan Iran

ISBN: (纸本)9798331522254

Although high-performance artificial intelligence (AI) models require substantial computational resources, embedded systems are constrained by limited hardware capabilities, such as memory and processing power. On the other hand, embedded systems have a broad range of applications, making the integration of AI and embedded systems a prominent topic in both hardware and AI research. Creating powerful speech embeddings for embedded systems is challenging, as such models, like Wave2Vec, are typically computationally intensive. Additionally, the scarcity of data for many low-resource languages further complicates the development of high-performance models. To address these challenges, we utilized BERT to generate speech embeddings. BERT was selected because, in addition to producing meaningful embeddings, it is trained on numerous low-resource languages and facilitates the design of efficient decoders. This study introduces a compact speech encoder tailored for low-resource languages, capable of functioning as an encoder across a diverse range of speech tasks. To achieve this, we utilized BERT to generate meaningful embeddings. However, due to the high dimensionality of BERT embeddings, which imposes significant computational demands on many embedded systems, we applied dimensionality reduction techniques. The reduced-dimensional vectors were subsequently used as labels for speech data to train a model composed of convolutional neural networks (CNNs) and fully connected layers. Finally, we demonstrated the encoder's effectiveness through an application in speech command recognition. © 2024 IEEE.

关键词： Embedded systems

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Finite Element Analysis Modeling, Data Generation and Energy Management for Paper Drying Process

Finite Element Analysis Modeling, Data Generation and Energy...

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TAPPICon 2023 - Rock the Roll: Unleashing the Harmonies of the Paper Industry

作者： Pandey, Kamlesh Zhang, Yunhao Pal, Lokendra Lee, Yuan Shin Singh, Anand Department of Forest Biomaterials Department of Industrial and System Engineering Department of Electrical and Computer Engineering

• Different statistical and machine learning approaches have been evaluated for modeling paper drying process. • A web-based interface also developed to store machine runs results into a local database for more complex model building • Performance of K-NN model is better in comparison to other model in terms of R2 and computation time. • An immersive learning tool using machine learning also developed for undergraduate student to approach paper making process through a data driven mindset. • In future this web application can act as a middleware between the CESMII server and shop floor, user can visualize the process and predict without physically running the machine. © 2023 TAPPICon 2023 - "Rock the Roll: Unleashing the Harmonies of the Paper Industry". All rights reserved.

关键词： Middleware

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Stress Analysis and Care Prediction for Hostellers

Stress Analysis and Care Prediction for Hostellers

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2024 International Conference on Communication, Computing and Internet of Things, IC3IoT 2024

作者： Vishnukumar, A. Kavitha, A. Akshaya, G. Rajalakshmi Engineering College Computer Science And Business System Rajalakshmi Nagar Chennai602105 India

ISBN: (纸本)9798350352689

Stress is one of the major concerns for students in recent days. The rapid changes in the environment, lack of adoptability, life style habits, social media interactions, education, finance in all means, students build a resilient stress thinking about various issues. The proposed study considers the specific concern on hostel students and their impact of stress due to various reasons. Students staying away from the parents initially have certain level of stress and emotional imbalance. The presented study considers the measures taken so far to analyse the human stress level in changing environment, using various existing tools and techniques etc. the role of technology and recent developments impact the analysis pattern of these problems are discussed. The study considers the benefits of internet of things (IoT), Embedded systems and devices enabled to detect the stress levels. The system considerations, challenges in stress analysis models are explored. © 2024 IEEE.

关键词： Students

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Analyzing Chatbot Architectures Utilising Deep Neural Networks 6

Analyzing Chatbot Architectures Utilising Deep Neural Networ...

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6th International Conference on Cybernetics, Cognition and Machine Learning Applications, ICCCMLA 2024

作者： Patil, Kavita Patil, Rohit Koyande, Vedanti Thakur, Amaya Singh Kadam, Kshitij JSPM's Rajarshi Shahu College of Engineering Computer Science and Business System Pune India

ISBN: (纸本)9798331505790

This survey paper examines the advancements and challenges in chatbot technology, focusing on deep neural networks (DNNs) and their application in natural language processing (NLP). It discusses various chatbot models, including Elizabot, Alicebot, Mitsuku, and Cleverbot, highlighting their evolution from rule-based systems to sophisticated AI conversational agents. The study introduces a specialized chatbot for website integration, emphasizing the importance of swift, accurate, and personalized interactions to enhance customer engagement. Additionally, the paper explores the integration of Large Language Models (LLMs) such as Gemini, GPT and BERT, fine-tuning with deep learning techniques to improve chatbot performance, and their potential to revolutionize customer interactions and business growth. © 2024 IEEE.

关键词： Chatbots

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Sagittarius: Floating Self Navigating Robot for Monitor the Water Quality of Rural Reservoirs 6

Sagittarius: Floating Self Navigating Robot for Monitor the ...

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6th International Conference on Advancements in Computing, ICAC 2024

作者： Pedige, Nishan Ilandara Abeywarna, Thaveesha Amarasinge, Randheera Bandara, Menuka Nawarathna Javakody, Anuradha Gamage, Narmada Sri Lanka Institute of Information Technology Department of Computer System Engineering Malabe Sri Lanka

ISBN: (纸本)9798331517878

This paper proposes an optimal solution for monitoring water quality in Sri Lanka, where reservoirs are essential for daily life and agriculture, especially in rural areas. Despite its importance, 3.6 million communities are affected by severe water quality problems, contributing to a high incidence of chronic kidney diseases. While water purification plants are the only solution, high salinity and hardness often make these sources unsuitable. Many rural reservoirs remain unpurified but could potentially provide safe water if properly monitored and maintained. Yet water sources are frequently contaminated by chemical waste and activities associated with agricultural business but effective solutions for continuous water quality monitoring are lacking. This study introduces an autonomous robot equipped with advanced sensors to monitor critical water quality parameters in real-time. By integrating machine learning for data analysis and prediction, Sagittarius enables continuous assessment of reservoir water quality, providing timely insights for public health protection. Field tests demonstrate a prediction accuracy exceeding 98.5%, supporting proactive water management and monitoring. This system has shown potential to aid in early detection of contamination, informing authorities promptly for preventive actions, and enabling sustainable water usage. This solution can significantly contribute to public health protection and informed water resource management decisions. © 2024 IEEE.

关键词： Reservoirs (water)

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Multi‐granularity re‐ranking for visible‐infrared person re‐identification

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CAAI Transactions on Intelligence Technology 2023年第3期8卷 770-779页

作者： Yadi Wang Hongyun Zhang Duoqian Miao Witold Pedrycz Department of Computer Science and Technology Tongji UniversityShanghaiChina Key Laboratory of Embedded System and Service Computing Ministry of EducationShanghaiChina Department of Electrical and Computer Engineering University of AlbertaEdmontonAlbertaCanada System Research Institute Polish Academy of SciencesWarsawPoland

Visible‐infrared person re‐identification(VI‐ReID)is a supplementary task of single‐modality re‐identification,which makes up for the defect of conventional re‐identification under insufficient *** is more challenging than single‐modality ReID because,in addition to difficulties in pedestrian posture,camera shoot-ing angle and background change,there are also difficulties in the cross‐modality *** works only involve coarse‐grained global features in the re‐ranking calculation,which cannot effectively use fine‐grained ***,fine‐grained features are particularly important due to the lack of information in cross‐modality re‐*** this end,the Q‐center Multi‐granularity K‐reciprocal Re‐ranking Algorithm(termed QCMR)is proposed,including a Q‐nearest neighbour centre encoder(termed QNC)and a Multi‐granularity K‐reciprocal Encoder(termed MGK)for a more comprehensive feature *** converts the probe‐corresponding modality features into gallery corresponding modality features through modality transfer to narrow the modality *** takes a coarse‐grained mutual nearest neighbour as the dominant and combines a fine‐grained nearest neighbour as a supplement for similarity *** experiments on two widely used VI‐ReID benchmarks,SYSU‐MM01 and RegDB have shown that our method achieves state‐of‐the‐art ***,the mAP of SYSU‐MM01 is increased by 5.9%in all‐search mode.

关键词： computer vision recognition

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Research on vulnerability mining of authentication protocol based on fuzzy simulation

Research on vulnerability mining of authentication protocol ...

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2023 IEEE International Symposium on Broadband Multimedia systems and Broadcasting, BMSB 2023

作者： Lv, Lele Feng, Zhi Dong, Wei Zhao, Yunfei Zhao, Yunze Gai, Xinyu National Computer System Engineering Research Institute of China Beijing China

ISBN: (纸本)9798350321524

Authentication and authorization protocols simplify the login authorization of third-party applications and provide basic guarantees and prerequisites for security services. However, due to the high uncertainty of protocol execution, the diversity of security attributes and the complexity of logical structure, it is very difficult to construct a verification model and detect the security of the protocol in actual operation. In this paper, a fuzzy simulation based authentication protocol logic vulnerability mining method is proposed. Fuzzy body roles are introduced to inject randomization factors into the protocol interaction process to create multiple interaction scenes and detect protocol vulnerabilities in dynamic environment. At the same time, Noisy-Dueling DQN, an improved reinforcement learning algorithm, can intelligently excavate protocol vulnerabilities. Finally, through the detection and analysis of OAuth2.0 protocol, the attack path of the protocol is found, and the effectiveness of the method is proved. The experimental results show that, compared with the traditional DQN algorithm, the convergence speed of Noisy Dueling DQN algorithm has been effectively improved , which makes the model tend to the optimal state faster during training, and effectively improves the efficiency of vulnerability mining. © 2023 IEEE.

关键词： Reinforcement learning

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A Multi-label Classification Method for Positive and Unlabeled Dataset. 4

A Multi-label Classification Method for Positive and Unlabel...

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4th Asia Service Sciences and Software engineering Conference, ASSE 2023

作者： Takahashi, Hikaru Qiangfu, Zhao University of Aizu Computer Science and Engineering Department Major in Computer Information System Japan University of Aizu Computer Science and Engineering Department Japan

ISBN: (纸本)9798400708534

Positive and Unlabeled (PU) learning is a learning method which can be applied to various field such as recommendation and big data analysis. A direct method to solve PU learning is transform it into a weighted classification problem. However, previously proposed methods assume a strict condition. In this paper, we first investigate if the condition can be satisfied in real world situations and then propose a normalized weighted method which can relax the difficultly of PU learning. © 2023 ACM.

关键词： Machine learning

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Research on Model and Simulation of Vehicle Network Based on LTE Technology

Research on Model and Simulation of Vehicle Network Based on...

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2023 IEEE International Symposium on Broadband Multimedia systems and Broadcasting, BMSB 2023

作者： Gai, Xinyu Li, Zhicheng Zhang, Yaqin Li, Shiqi Meng, Guimin Lv, Lele National Computer System Engineering Research Institute of China Beijing China

ISBN: (纸本)9798350321524

Vehicle Ad Hoc Network (VANET) is one of the important means to realize intelligent transportation system, which can improve road safety and traffic efficiency. At present, two key technologies of vehicle communication include DSRC (Dedicated Short-Range Communication) and LTE (Long Term Evolution). After 20 years of in-depth research, DSRC has reached sufficient technical maturity, but its performance improvement space is relatively limited. LTE is a relatively new 3GPP-based standard and is considered the strongest competitor to IEEE *** are many mature analysis models in DSRC reliability analysis, however as LTE is a newly emerging vehicle networking technology, the existing analysis models have some problems that do not conform to actual traffic scenarios and incomplete analysis of beacon transmission errors. Although technological innovations allow LTE to have many features over DSRC, studies have found that DSRC outperforms in some *** the existing shortcomings of analysis models, this paper proposes an LTE broadcast performance analysis model based on the Poisson distribution traffic model. This model uses the Markov State Transition Process to evaluate the probability of packet reception for LTE combined with four transmission errors. The numerical results of the analysis model is cross-validated through the network simulation results obtained by the MATLAB simulator, which proves the correct-ness of the model. © 2023 IEEE.

关键词： Reliability analysis

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