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Adversarial learning for Mirai botnet detection based on long short-term memory and XGBoost

International Journal of Cognitive Computing in engineering 2024年第1期5卷 153-160页

作者： Vajrobol, Vajratiya Gupta, Brij B. Gaurav, Akshat Chuang, Huan-Ming Institute of Informatics and Communication University of Delhi India International Center for AI and Cyber Security Research and Innovations. Asia University Taiwan Department of Computer Science and Information Engineering Asia University Taichung413 Taiwan Ronin Institute MontclairNJ United States Department of Information Management National Yunlin University of Science and Technology Yunlin Taiwan Symbiosis International University Pune India Department of Electrical and Computer Engineering Lebanese American University Beirut1102 Lebanon Dehradun India

In today's world, where digital threats are on the rise, one particularly concerning threat is the Mirai botnet. This malware is designed to infect and command a collection of Internet of Things (IoT) devices. The use of Mirai attacks has intensified in recent times, thus threatening the smooth operation of numerous devices that are connected to a network. Such attacks carry adverse consequences that include interference with services or the leakage of confidential information. To fight this growing threat, smart and flexible detection techniques are required to counter the new methods cyber attackers use. The aim of this research is to develop a resilient defense against Mirai botnet attacks. The Long Short Term Memory term (LSTM) and XGBoost combined have the best performance of 97.7% accuracy score. With this combination, the aim is to strengthen our cyber defenses against sophisticated and dynamically operating Mirai botnets to further enhance the security of our digital world. © 2024

关键词： Botnet

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A Post-structured Analysis of Chinese Thyroid Ultrasound Report Based on Natural Language Processing Technology and TI-RADS Model 24

A Post-structured Analysis of Chinese Thyroid Ultrasound Rep...

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8th International Conference on Medical and Health informatics, ICMHI 2024

作者： Miao, Shumei Sheng, Rongrong Jing, Mang Wang, Zhongmin Yang, Guanyu School of Computer Science and Engineering Southeast University Jiangsu Nanjing China Department of Information the First Affiliated Hospital of Nanjing Medical University Jiangsu Nanjing China Department of Intelligent medical engineering School of Biomedical Engineering and Informatics Nanjing Medical University Jiangsu Nanjing China

ISBN: (纸本)9798400716874

Thyroid nodules are common and multiple diseases of the head and neck. Ultrasound examination is an important imaging method for the diagnosis of benign and malignant thyroid nodules. The extraction of TI -RADS standard-related entity information from ultrasonic reports has an important influence on the intelligent judgment of benign and malignant of thyroid nodule. Based on TI-RADS system model, and using CRFs model and support vector machine technology, this study carried out post-structured analysis of Chinese ultrasonic thyroid report and obtained high accuracy. High quality information extraction provides important information support for the follow-up intelligent decision support, and provides a research basis for the automatic pre-diagnosis of benign and malignant thyroid nodules. © 2024 ACM.

关键词： Endocrinology

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Dual-Band Planar Microstrip Monopole Antenna Design Using Multi-Objective Hybrid Optimization Algorithm

Dual-Band Planar Microstrip Monopole Antenna Design Using Mu...

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2023 Photonics and Electromagnetics Research Symposium, PIERS 2023

作者： Hosseini, V. Shapour, F. Pinho, P. Farhang, Y. Majidzadeh, K. Ghobadi, Ch. Nourinia, J. Barshandeh, S. Shokri, M. Amiri, Zh. Jalilirad, M. Kaboutari, K. Payame Noor University Department of Computer Engineering and Information Technology Tehran Iran Islamic Azad University Urmia Branch Computer Engineering Department Urmia Iran Instituto de Telecomunicações Aveiro Portugal University of Aveiro Department of Electronics Telecommunications and Informatics Aveiro Portugal Islamic Azad University Khoy Branch Department of Computer Engineering Khoy Iran Urmia University Department of Electrical Engineering Urmia Iran School of Engineering Department of Computer Science Afagh Higher Education Institute Urmia Iran

ISBN: (纸本)9798350312843

This research uses a new proposed multi-objective optimization algorithm that utilizes an untested combined chaotic map to integrate Customized Mutated PSO (CM-PSO) with a Modified Genetic Algorithm (MGA) to design an antenna with specific electromagnetic characteristics. The hybrid approach achieves preferred outcomes faster than PSO, CM-PSO, GA, and MGA by avoiding being trapped in local minimums. The proposed Metaheuristic Algorithm (MA) functionality has been authenticated successfully using Benchmark Functions (BFs) like Rastrigin Function (RaF), Ackley Function (AF), Rosenbrock Function (RoF), and Booth Function (BoF). Finally, the validity of the offered approach for electromagnetic applications is demonstrated by optimizing a dual-band planar microstrip monopole antenna with a simple structure, such that its optimized S11 be less than -10 dB at two frequency bands encompasses 2.4 to 2.484 and 5.15 to 5.825 GHz for Wireless Local Area Network (WLAN) with IEEE 802.11 standards. The proposed algorithm allows the optimization criteria to be customized. The optimization algorithm developed in MATLAB is used to determine the necessary parameter adjustments in order to achieve expected frequency bands using CM-PSO or an innovative MGA, while high-frequency and electromagnetic simulations are performed using computer Simulation Technology (CST) Studio Suite. The dimensions of the proposed antenna's elements are critical input parameters of the algorithm, named decision variables. © 2023 IEEE.

关键词： Monopole antennas

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Classifying News Based on Indonesian News Using LightGBM

Classifying News Based on Indonesian News Using LightGBM

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2022 International Conference on computer engineering, Network and Intelligent Multimedia, CENIM 2022

作者： Lubis, Arif Ridho Prayudani, Santi Fatmi, Yulia Nugroho, Okvi Politeknik Negeri Medan Department of Computer Engineering and Informatics Medan Indonesia Kulkas IT Medan Indonesia

ISBN: (纸本)9781665476508

There were several news categories that present editors with challenges. Some news categories, such megapolitan, national, celebrity, news, lifestyle, and economics, used vocabulary that was quite similar to that of the other categories. International required an editor to be familiar with the article's contents in order for it to be uploaded and placed in the proper category. We had to first digest the news before we could label it compared to other kinds of data. The text mining approach, which attempts to make text or documents may be processed so that it will aid in the process of news classification, will be used to categorize and determine the type of news in this context. The Light Gradient Boosted Machine (LightGBM) model was used in this study to increase the gradient point with a learning stage and obtain the optimal value. This model's training process was intended to be quick while consuming less storage space and processing information more accurately. The accuracy of the classifications made using a confusion matrix to quantify the findings of this investigation, which were news type classifications, was 86%. © 2022 IEEE.

关键词： Digital storage

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Blockchain-based Internet of Musical Things

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Blockchain(Research and Applications) 2022年第3期3卷 60-69页

作者： Luca Turchet Chan Nam Ngo Department of Information Engineering and Computer Science University of TrentoTrento38122Italy Faculty of Mathematics Informaticsand Mechanics of the University of WarsawWarsaw00-927Poland

Blockchain technology is impacting several industries,including the creative industries and those operating in the Internet of Things(IoT).Lately,researchers'attention has been devoted to the application of blockchain in the recorded music ***,thus far,no research has investigated the use of such technology in the Internet of Musical Things(IoMusT).The IoMusT is a new area emerging in industry and academy as an extension of the IoT to the musical *** IoMusT itself,as the IoT,is a distributed network of musical things,which are objects augmented with information and communication technologies serving a musical *** IoMusT vision requires,above all,IoT features such as decentralization,seamless authentication,transparency,data integrity and privacy,and self-maintenance,as well as the musical domain features such as efficient handling of copyrights and speed of royalties *** features can be brought by *** this paper,we investigate the integration of blockchain technology with the IoMusT,and we name such synthesis“Blockchain-based IoMusT”.We present a vision for this new paradigm in terms of the novel opportunities that are enabled,and we propose a set of application scenarios enabled by technological ***,we outline the open research directions in this promising area.

关键词： Internet of Musical Things Blockchain Music industry Privacy Security Internet of Things

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QoS-Aware Load Balancing Scheme in Dense Wi-Fi 6 WLANs 1

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8th EAI International Conference on Industrial Networks and Intelligent Systems, INISCOM 2022

作者： Ak, Elif Canberk, Berk Computer Engineering Department Istanbul Technical University Istanbul Turkey Artificial Intelligence and Data Engineering Department Computer and Informatics Faculty Istanbul Technical University Istanbul Turkey

ISBN: (数字)9783031088780

ISBN: (纸本)9783031088773

Nowadays, increasing mobile and wireless usage demand accelerates new enhancements on IEEE 802.11 family to provide concurrent transmission and high efficiency. Thus, IEEE 802.11ax is released with the aim to improve overall throughput in dense WLANs considering the overlapping channel interference. However, the current WLANs suffer from uneven load distribution among the Access Points (AP). Because a station simply connects to the AP with the highest received signal strength indication (RSSI) in a legacy association way. And RSSI might not be the only criteria in the current WLANs due to the variety of application requirements and high date rates. Therefore, we propose a complete association scheme called Access Controller (AC) to manage admission, association, and adaptive carrier sensitivity control as a whole. The station from an overloaded AP is handed to a less loaded AP by considering various crucial metrics such as packet delivery ratio, fairness, RSSI, throughput, and round trip time. After effective load balancing, we adaptively tune the carrier sensitivity threshold to enhance concurrent transmission in IEEE 802.11ax WLANs. The results show that the proposed AC scheme outperforms in terms of fairness and per-station throughput in dense WiFi6 scenarios with over 500 stations. © 2022, ICST Institute for computer Sciences, Social informatics and Telecommunications engineering.

关键词： Wireless local area networks (WLAN)

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Evaluation of the security of password-protected encrypted RAR3 and RAR5 archives

Evaluation of the security of password-protected encrypted R...

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2022 International Conference on Networks, Communications and Information Technology, NCIT 2022

作者： Krupalija, Ehlimana Mrdović, Saša Cogo, Emir Prazina, Irfan Bećirović, Šeila Department of Computer Science and Informatics Faculty of Electrical Engineering University of Sarajevo Sarajevo Bosnia and Herzegovina

ISBN: (纸本)9783800760190

Roshal Archive (RAR) format is one of the most widely used data archive formats, enabling users to reduce the size of data and protect it with the desired password before the data is transferred to its intended recipients over the network. This work focuses on the security of encrypted RAR archives and various different approaches for their decryption. Two different datasets composed of randomly generated and real-world user passwords were used for deploying brute force and dictionary attacks on password-protected RAR archives. Two available and widely used tools, John the Ripper and Hashcat, were used for cracking passwords of encrypted RAR3 and RAR5 archives. Experimental results indicate that both brute force and dictionary attacks were unsuccessful for RAR archives protected with randomly generated passwords, even of very small length. Real-world user passwords were successfully cracked only partially by brute force attacks, whereas dictionary attacks were very successful. The success rate for RAR5 archives was only slightly lower than for RAR3 archives and processing times were similar, indicating that this new version of the RAR format does not significantly improve data security. Instead, the security of RAR archives can be increased by using longer passwords more similar to randomly generated data, which are not present in commonly used dictionaries, as indicated by the experimental results. © VDE VERLAG GMBH ∙ Berlin ∙ Offenbach.

关键词： Cryptography

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CervixNet: A Reward-Based Weighted Ensemble Framework for Cervical Cancer Classification 4th

CervixNet: A Reward-Based Weighted Ensemble Framework for Ce...

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4th International Conference on Frontiers in Computing and Systems, COMSYS 2023

作者： Roy, Kaushiki Bhattacharjee, Deboparna Banik, Debapriya Krejcar, Ondrej Sarkar, Ram Kolkata700091 India University of Engineering and Management Kolkata700160 India Department of Computer Science and Engineering Jadavpur University Kolkata700032 India Department of Computer Science and Engineering RCC Institute of Information Technology Kolkata700015 India Department of Computer Science and Engineering ICFAI University Tripura Agartala799210 India Center for Basic and Applied Science Faculty of Informatics and Management University of Hradec Kralove Rokitanskeho 62 Hradec Kralove500 03 Czech Republic

ISBN: (纸本)9789819726103

Cervical cancer is one of the most common causes of death among women worldwide. However, this fatal disease can be treated, and the mortality rate can be decreased if detected at an early stage. The Papanicolaou test is the gold standard for screening cervical cancer patients. However, the process of manual inspection is tedious and subject to manual errors. Thus, computer-based automatic screening is considered a viable alternative. To this end, in the present work, we have developed a novel system for classifying cervical cancer images as either normal or malignant. We have used the Herlev dataset in this study, which is the standard Pap smear image benchmark dataset. The proposed framework uses multiple base deep learning frameworks, namely Vision Transformer, Xception, VGG-19, VGG-16, and ResNet-101, for classification. Further, we have introduced a novel reward-based weighing technique to decide the weights of individual classifiers, which are, in turn, used to make decisions about the final class label of an input image using the weighted average technique. The proposed framework achieves an overall accuracy, precision, recall, F1-score, and AUC of 96%, 94%, 92%, 93%, and 94%, respectively, for the binary classification task that is normal vs. malignant. An elaborate study of the performance achieved by our proposed framework on the Herlev dataset shows it to be both robust and effective for the Pap smear image classification task. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Classification (of information)

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The Calibration of Single Beam Distance Sensors based on Machine Learning Methods

The Calibration of Single Beam Distance Sensors based on Mac...

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2023 IEEE International Conference on Big Data, BigData 2023

作者： Biernacki, Piotr Ziebinski, Adam Syu, Jia-Hao Lin, Jerry Chun-Wei Silesian University of Technology Institute of Theoretical and Applied Informatics Polish Academy of Sciences Institute of Informatics Gliwice Poland Silesian University of Technology Institute of Informatics Gliwice Poland National Taiwan University Department of Computer Science and Information Engineering Taipei Taiwan

ISBN: (纸本)9798350324457

Smart cities require the use of many different types of sensors to make the communication, and distance sensors are one of the most commonly used elements in transportation systems and related infrastructures. The introduction of increasingly advanced autonomous systems in many areas of smart cities requires high measurement precision of the sensors used. High precision is essential for proper operation, long-term use, and safety in machine-to-machine or machine-to-human interactions. This paper presents a comparison of the accuracy of distance measurements for two commercially available single-beam LiDARs and two ultrasonic sensors. The aim of the research was to develop a calibration method in order to improve the accuracy of distance sensors. Based on the collected distance measurements, the sensors were calibrated using selected machine learning algorithms. The results of the experiments show the effectiveness of the proposed calibration methods, which yield an average mean absolute error (MAE) of 1.76 E-05 meters (m) and a root mean square error (RMSE) of 1.33 E-04 m for the tested sensors. © 2023 IEEE.

关键词： machine learning sensors calibration single-beam distance sensors

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Public Roads Management and Visualisation

Public Roads Management and Visualisation

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International Symposium on Applied Machine Intelligence and informatics (SAMI)

作者： Jaroslav Marko Anton Baláź Department of Computer and Informatics Faculty of Electrical Engineering and Informatics Technical University of Košice Košice Slovakia

ISBN: (数字)9798350379365

ISBN: (纸本)9798350379372

The paper deals with the issue of collecting and displaying geographic information about roads in Slovakia with emphasis on information about obstacles on roads. The main objective is to design a solution for collecting and displaying the roads based on the analysis of existing systems and identifying the requirements for an optimal design. The paper starts with an analysis of available solutions and the development of requirements for the most favourable design, followed by the planning of an optimal solution for collecting and displaying road obstruction data. The focus of the paper is on the development of a method for creating and modifying geographic obstacle information, the design of a textual and graphical display of the information, and the design of a three-level model for user access to the application. The paper concludes with a discussion of the proposed solution, comparing the requirements for the optimal design with the developed design.

关键词： Roads Planning Object recognition informatics Machine intelligence

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