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Network Risk Assessment Method Based on Residual Risk Analysis 1

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7th international conference on Internet of things, ICIOT 2022 held as Part of the Services conference Federation, SCF 2022

作者： Jing, Hao Yan, Peizhi Wang, Gang Liu, Jiewei Fang, Yige School of Information Engineering Inner Mongolia University of Technology Hohhot China

ISBN: (数字)9783031235825

ISBN: (纸本)9783031235818

the existing network security theory usually believes that "residual risks" are acceptable to a certain degree. However, the reality is that most attackers can enter the network by using the residual risks. therefore Method of cyber risk assessment. First of all, the algorithm uses the access relationship between the network equipment to build an attack graph structure. Secondly, it uses an Grade protection evaluation score to replace the traditional CVSS score and introduce the indicator of the weight of the indicator to obtain a prior risk probability of each node in the network. Finally, according to real-time attack signs, the Bayesian reasoning algorithm calculates the post-test risk probability of the node to evaluate the risk of network in real time. © 2023, the Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Network security

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Automated ASPECTS Classification in Acute Ischemic Stroke using EfficientNetV2 7

Automated ASPECTS Classification in Acute Ischemic Stroke us...

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7th IEEE international conference for Convergence in technology, I2CT 2022

作者： Golkonda, Ramananjali Mounica Menon, Vivek Nambiar, Vivek Amrita Vishwa Vidyapeetham Department of Computer Science and Engineering Amritapuri Kollam690 525 India Amrita Institute of Medical Sciences Division of Stroke Medicine Department of Neurology Kochi682 041 India

ISBN: (纸本)9781665421683

Etiology of ischemic stroke can be attributed to large vessel occlusions (LVOs), which lead to insufficient supply of oxygen to brain. Early detection and evaluation of infarct core volume plays a crucial role in the optimal treatment for brain ischemia. In this work, we leverage transfer learning for automated computing of Alberta Stroke Program Early CT Score (ASPECTS) using Non-Contrast CT (NCCT) scans. We compare the performance of different state-of-the art ImageNet pre-trained networks for multi-class classification of NCCT scans based on ASPECTS score value ranging from 0-10. Additionally, based on ASPECTS and reperfusion therapy, we group the NCCT scans into two categories: 0-6 in Group0 and 7-10 in Group1, to perform binary classification using pre-trained networks. Our experiments validate the choice of pre-trained EfficientNetV2 with the highest Area Under Curve (AUC) of 0.995 in multi-class classification and 0.977 in binary class classification. © 2022 IEEE.

关键词： Classification (of information)

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An Efficient Reduced-Memory GPU-based Dynamic Programming Strategy for Bounded Knapsack Problems 7

An Efficient Reduced-Memory GPU-based Dynamic Programming St...

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7th international conference on Parallel, Distributed and Grid Computing, PDGC 2022

作者： Biswas, Girish Mukherjee, Nandini Jadavpur University Department of Computer Science and Engineering Kolkata India

ISBN: (纸本)9781665454018

Many dynamic programming approaches are existing for 1-0 Knapsack problem (KP) for fast GPU-based solution. these dynamic programming methods can be used for solving the problem of Bounded Knapsack Problem (BKP) after converting it into an equivalent 1-0 Knapsack problem. But, after conversion, large problem of BKP becomes too large 1-0 KP to fathoming via these methods on GPU-based system because of limited space availability in GPU device. In this paper, we present an implementation of an efficient dynamic programming technique to solve BKP on GPU-based system via CUDA. With an aspect to preserving the original problem size, BKP is not required to convert into equivalent 1/0 knapsack problem in this approach. Large problems are carried out with only minimally requisite CPU-GPU interactions and less memory occupancy on GPU for better efficiency and memory utilization. this GPU oriented parallel procedure shows brilliant speedup over sequential implementation of the dynamic technique. © 2022 IEEE.

关键词： Graphics processing unit

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BeLLE: Detecting National Differences in Computational thinking and computer Science through an international Challenge 7th

BeLLE: Detecting National Differences in Computational Thin...

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7th international conference on Creative Mathematical Sciences Communication, CMSC 2024

作者： Kaarto, Heidi Bilbao, Javier Pears, Arnold Dagienė, Valentina Kilpi, Janica Parviainen, Marika Pluhár, Zsuzsa Gülbahar, Yasemin Laakso, Mikko-Jussi Turku Research Institute for Learning Analytics University of Turku Turku Finland Bilbao Spain KTH Royal Institute of Technology Stockholm Sweden Vilnius University Institute of Educational Sciences Vilnius Lithuania Eötvös Loránd University Budapest Hungary Teachers College Columbia University New York United States

ISBN: (纸本)9783031732560

the Bebras challenge is an international initiative to engage school pupils with computer science and computational thinking via an annual challenge designed by computer science experts and educators. BeLLE is an international consortium focusing on international comparisons of standard challenge task banks. the consortium uses the ViLLE platform to manage the challenge as it offers a digital exercise-based learning environment with comprehensive learning analytics. the goal is to learn more about students’ knowledge in computer science and computational thinking in order to provide information for curriculum development and other educational planning and research. BeLLE started in 2021 with a pilots in Hungary and India. After the successful pilot, the consortium expanded substantially in the following year, many multiple choice questions were transformed into interactive tasks, and the process of organizing the challenge in ViLLE was refined. In this paper, we present some results of the challenge conducted within the BeLLE consortium in 2022. Over 90,000 students (47 % girls, 53 % boys) participated in the challenge in total through BeLLE. the results show that most students across countries and age groups get less than half of the maximum scores. the difference between girls and boys become apparent in Hungary and Lithuania: in the two oldest age groups (14–16 and 16–19 years old) boys score higher than girls. the time spent on the challenge is often 30 to 40 min with a difference between girls and boys in Hungary and Lithuania: boys use either less or more time than girls. © the Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Contrastive Learning

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Systematic Literature Review of Stemming and Lemmatization Performance for Sentence Similarity 7

Systematic Literature Review of Stemming and Lemmatization P...

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7th IEEE international conference on information technology and Digital Applications, ICITDA 2022

作者： Pramana, Rio Debora Subroto, Jonathan Jansen Gunawan, Alexander Agung Santoso Anderies Bina Nusantara University School of Computer Science Computer Science Department Jakarta11480 Indonesia

ISBN: (数字)9781665461368

ISBN: (纸本)9781665461368

In today's era, where the Internet is a huge part of people's life, information Retrieval (IR) is as important as ever for people to retrieve relevant information in a quick way. the sentence similarity task is an integral aspect of IR. Improving the performance of this task will also improve IR. To help achieve this, stemming and lemmatization was made. However, it is still unclear to many which one is the best to use for sentence similarity tasks. therefore, the purpose of this study is to find which preprocessing technique (stemming and lemmatization) is best for sentence similarity tasks. In this study, the authors would like to conduct a Systematic Literature Review (SLR) on stemming and lemmatization based on many previous studies related to this topic. Previous studies have tried to assess and compare both preprocessing techniques using many evaluation methods, and it is found that a lot of factors go into deciding which preprocessing technique (stemming or lemmatization) is the best option. In general, the authors conclude lemmatization is considered the best option for sentence similarity tasks since it produces better results than stemming. However, if speed optimization is imperative, then stemming is the better option since its computational speed is faster. © 2022 IEEE.

关键词： information retrieval

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An Intrusion Detection System for Securing IoT Based Sensor Networks from Routing Attacks 7th

An Intrusion Detection System for Securing IoT Based Sensor ...

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7th international conference on computer, Communication and Signal processing, ICCCSP 2023

作者： Subramani, Shalini Selvi, M. Kumar, S. V. N. Santhosh thangaramya, K. Anand, M. Kannan, A. School of Computer Science and Engineering Vellore Institute of Technology Vellore632014 India School of Information Technology and Engineering Vellore Institute of Technology Vellore632014 India Computer Science and Engineering College of Engineering Guindy Anna University Chennai600025 India Department of Electronics and Communication Saveetha Engineering College Chennai602105 India

ISBN: (纸本)9783031398100

Internet of things is made up of sensor nodes that can sense the given environment, gather the data from environment and then communicates the data to the sink node and the internet through wireless communication. As it follows the routing protocols used in Wireless Sensor Networks, the Denial of Service (DoS) attacks including selective forwarding and flooding are launched by the attackers through Routing Protocol for Low-Power and Lossy Network (RPL) attacks. Intrusion detection systems are able to handle the RPL based DoS attacks and can prevent the attackers from participation in the routing process. therefore, we propose a new fuzzy temporal random forest algorithm for detecting the attacks more efficiently. In addition, a new intelligent agent based intrusion prevention system which uses fuzzy temporal inference rules for intrusion prevention is also proposed in this work. the proposed model has been compared with other machine learning algorithms such as decision trees, logistic regression, random forest, K-Nearest Neighbor and also the deep learning algorithm namely the Convolution neural networks. Based on the experimentations carried out, we could prove that the proposed algorithm provides higher intrusion detection accuracy, reduces the false positive rate and detection time when compared with the related work. © IFIP international Federation for information processing 2023.

关键词： Denial-of-service attack

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Predictive EQCi-Optimized Load Scheduling for Heterogeneous IoT-Data in Fog Computing Environments 7

Predictive EQCi-Optimized Load Scheduling for Heterogeneous ...

引用

7th international conference on Image information processing, ICIIP 2023

作者： Madasamy, Sridhar Vikkram, R. Basi Reddy, A. Nandhini, T. Gupta, Shipra Nagamani, A. Cognizant Technology Solution 500 Frank W. Burr Boulevard TeaneckNJ07666 United States Karpagam College of Engineering Department of Information Technology Tamilnadu Coimbatore India Mohan Babu University School of Computing Department of Computer Science And Engineering Andhra Pradesh Tirupati India KSR Institute For Engineering And Technology Department of Information Technology TamilNadu Tiruchengode637 215 India Graphic Era Hill University School of Management Uttarakhand Dehradun India Mlr Institute of Technology Department of Computer Science And Engineering Telangana Hyderabad500043 India

ISBN: (纸本)9798350371406

this paper presents a pioneering predictive EQCi-optimized load scheduling technique tailored to the complexities of heterogeneous IoT data within fog computing environments. the proposed method strategically assigns tasks to fog nodes by considering Load Scheduling Policies (LSPs) and the computing capabilities of fog nodes. Incorporating an EQCi-technique, the model enhances load allocation precision for various LSPs, facilitated by representing LSPs as quantum bits (qubits). this representation enables efficient assessment of probabilistic Execution Index values and Node Availability Index (NAI) for fog nodes, facilitating real-time task allocation. Furthermore, the introduction of EQCi-NN introduces a predictive model that anticipates the optimal fog node for specific tasks with given LSPs. this predictive capability minimizes execution delays and enhances throughput within the fog computing environment. the proposed technique's performance is rigorously validated through simulations using the iFogSim toolkit, and its efficacy is demonstrated against existing load scheduling methods. Comparative analysis with other predictive techniques highlights the precision and efficiency of the proposed prediction model. the research underscores the presented system's effectiveness in predicting optimal computational nodes within fog computing platforms, particularly in scenarios necessitating real-time analytical outcomes. By synergizing quantum-inspired representation and predictive modeling, this study advances load scheduling methodologies in fog computing, optimizing resource utilization and bolstering the responsiveness of IoT-driven applications. © 2023 IEEE.

关键词： Fog computing

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Personalized QoE Optimization with Edge-Aided Video Enhancement Services 23

Personalized QoE Optimization with Edge-Aided Video Enhancem...

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23rd IEEE international conference on High Performance Computing and Communications, 7th IEEE international conference on Data Science and Systems, 19th IEEE international conference on Smart City and 7th IEEE international conference on Dependability in Sensor, Cloud and Big Data Systems and Applications, HPCC-DSS-SmartCity-DependSys 2021

作者： Liao, Hanlong Tang, Guoming Liang, Teng Wang, Longguang Guo, Deke National University of Defense Technology Science and Technology on Information Systems Engineering Laboratory Hunan Changsha China Peng Cheng Laboratory Shenzhen China

ISBN: (纸本)9781665494571

Video enhancement technologies can not only improve video qualities but also enrich personalized video experiences. With these technologies, the requested videos can be enhanced either on end devices or cloud servers. However, client devices may not have sufficient computing resources or energy, while cloud servers may not satisfy users' short delay requirement. Motivated by the 5G and edge computing technologies, we present veEdge in this paper, an edge-assisted video transmission framework for general-purpose video enhancement services. To balance the trade-off between video enhancement quality and processing delay, we formulate an optimization problem considering video requesting, processing, and playback time simultaneously. To solve the problem in an online fashion, we develop a deep reinforcement learning (DRL) based approach to select the best video enhancement model in favor of various targets, such as bandwidth and quality. the experimental results show that our solutions can significantly improve users' quality of experience (QoE). © 2021 IEEE.

关键词： Adaptation models Processor scheduling Reinforcement learning Streaming media Delays Quality assessment Quality of experience

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Research on the Online Recognition of the Motion Image of the Adjacent Joints of the Lower Limbs 2022

Research on the Online Recognition of the Motion Image of th...

引用

7th international conference on Multimedia and Image processing, ICMIP 2022

作者： Wan, Jiale Zhao, Li Bian, Yan Key Laboratory of Information Sensing and Intelligent Control Tianjin University of Technology and Education Tianjin300222 China

ISBN: (纸本)9781450387408

At present, offline analysis and research of lower limb motor imagery brain computer interface (MI-BCI) are relatively mature, but there are few researches on the online recognition of lower limb MI-BCI. the online recognition of the two MI tasks of the knee-Ankle adjacent joints of the right lower extremity was carried out, and the EEG signals of the two MI tasks assisted by electrical stimulation are collected. the Filter Bank Common Spatial Pattern (FBCSP) is used for feature extraction, and BP neural network is used for online recognition. the average recognition accuracy rate of online motor imagery of 13 subjects reaches 79.62%, and the recognition accuracy rate of the highest person is 92.50%, which verified the feasibility and practicability of online MI-BCI in adjacent joints of lower limbs. © 2022 ACM.

关键词： Brain computer interface

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Evaluating the Performance of State-of-the-art Methods and Classifying Covid-19 Infected Tissues 7

Evaluating the Performance of State-of-the-art Methods and C...

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7th IEEE international conference for Convergence in technology, I2CT 2022

作者： Kamruzzaman, M.M. Moinuddin, Md. Liton, Atikul Islam Azad, Mir Mohammad Hossain, Muhammad Anwar Rahman, Wahidur Jouf University College of Computer and Information Sciences Department of Computer Science Sakakah Saudi Arabia Khwaja Yunus Ali University Department of Computer Science and Engineering Sirajganj6751 Bangladesh University of South Asia Department of Computer Science and Engineering Dhaka Bangladesh Hamdard University Bangladesh Department of Computer Science and Engineering Munshiganj1510 Bangladesh Hamdard University Bangladesh Department of Aurvedic Medicine Munshiganj1510 Bangladesh Uttara University Department of Computer Science and Engineering Uttara Dhaka Bangladesh

ISBN: (纸本)9781665421683

In this study, the Traditional Convolution Neural Network (TCNN) and state-of-the-art approaches were applied to the datasets of Chest X-ray and CT scan imaging modalities and trained them concurrently. the TCNN's performance for detecting COVID-19 infected tissues was determined through a comparison examination using state-of-the-art approaches. the accuracy of the models has been improved by lowering the model's losses and overfitting. Finally, the training data size has been enhanced utilizing various picture augmentation methods such as flip-up-down, flip-down-left-right, and so on. VGG19 and InceptionV3 were tested in this work, and accuracy scores of 97 percent (X-ray images) and 96 percent (CT-scan images) were obtained. the model's loss functions, Precision, Recall, and F1-Score, were extracted and interpreted in the study. We examined the researchers' modified DL models and discovered that they were 65 percent accurate on X-ray data and 62 percent accurate on CT scan images. Experiments have demonstrated that when the number of sample images rises, the VGG19 and InceptionV3 perform well. © 2022 IEEE.

关键词： COVID-19

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