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1st International Conference on Advances in Computing Research, ACR’23

作者： Mughaid, Ala Alqahtani, Ali AlZu’bi, Shadi Obaidat, Ibrahim Alqura’n, Rabee AlJamal, Mahmoud AL-Marayah, Raid Department of Information Technology Faculty of Prince Al-Hussien Bin Abdullah for IT The Hashemite University Zarqa Jordan Department of Networks and Communication Engineering College of Computer Science and Information Systems Najran University Najran Saudi Arabia Computer Science Department Faculty of Science and Information Technology Al Zaytoonah University of Jordan Amman Jordan

ISBN: (纸本)9783031337420

One of the most critical features of the Internet of Things (IoT) is that it allows a massive number of devices to communicate with each other at the same time, for example (cars, smoke alarms, watches, glasses, web cameras, etc.). Given that they can connect to the Internet, the huge demand to convert systems into smart systems that can be controlled remotely increases the chances of cyber-attacks that threaten security and availability becoming more frequent, severe, and in a different form. Distributed Denial of Service (DDoS) attacks have become the most common threats in IoT. These attacks make IoT systems unreliable because complex DDoS attacks cannot be detected by traditional security countermeasures such as firewalls and intrusion detection systems (IDS). In this research, we proposed a model dedicated to work on prediction and detection of DDoS attacks on networks IoT, where we run this model on a NF-BoT-IoT-v2 dataset, which contains 37,763,497 records divided into five categories (Benign, Reconnaissance, DDoS, DoS, and Theft), and then we process our dataset to be more business friendly so it only has two categories (100,000 records broken down into 23,906 benign attacks and 76,094 DDoS attacks). This study used WEKA and MATLAB tools to perform the classification efficiently and find the most important features through feature selection. We used a decision tree (J48) machine learning classifier, a Naive Bayes (NB) classifier, and a random forest (RF) classifier. However, the results were as expected and improved accuracy and efficiency. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Denial-of-service attack

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Design and Implementation of Side Channel Attack Based on Deep Learning LSTM

Design and Implementation of Side Channel Attack Based on De...

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2023 IEEE Region 10 Symposium, TENSYMP 2023

作者： Ahmed, Amjed Abbas Hasan, Mohammad Kamrul Center for Cyber Security Universiti Kebangsaan Malaysia Faculty of Information Science and Technology Bangi Malaysia Department of Computer Techniques Engineering Baghdad Iraq

ISBN: (纸本)9781665482585

Encryption algorithms and encryption devices both play a key role in ensuring the safety of data that has been encrypted. Various types of attacks, such as energy analysis, can be used to assess the reliability of the encryption devices. Since it was originally introduced, side channel attacks' deep learning-based methodology has drawn plenty of attention. This is one of several different attack strategies. In this paper, a side channel attack method based on the LSTM deep learning network is suggested. The method use Correlation Power Analysis (CPA) to find the relevant information in the side channel power consumption data. The choice of a suitable interest interval to utilize as the feature vector in the creation of the neural network model is then guided by the position of the interest points. The trials' findings show that the LSTM model outperforms both MLP and CNN in terms of how well it executes side channel attacks. © 2023 IEEE.

关键词： Side channel attack

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Smart Advertising Based on Customer Preferences and Manage the Supermarket 4

Smart Advertising Based on Customer Preferences and Manage t...

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4th International Conference on Advancements in Computing, ICAC 2022

作者： Eishan Dinuka, W.H.A. Wickramasinghe, A.Y.S.W. Weerasinghe, W.S.H. Karunaratne, K.P.G. Liyanapathirana, Chethana Rupasinghe, Lakmal Department of Computer Science and Software Engineering Faculty of Computing Sri Lanka Institute of Information Technology Malabe Sri Lanka Department of Information Technology Faculty of Computing Sri Lanka Institute of Information Technology Malabe Sri Lanka Department of Computer Systems Engineering Faculty of Computing Sri Lanka Institute of Information Technology Malabe Sri Lanka

ISBN: (纸本)9798350398090

As a developing country, Sri Lanka needs to go along with cutting-edge technologies. In the beginning phase of this digital advertising, multiple advertisements were displayed on the users' feeds, including advertisements despite their preferences. This was a terrible user experience for the users. However, smart advertising based on customer preferences can manage the flow of advertisements on the feed as per the users' preferences. This same technique can be used in handling advertisements while shopping at supermarkets. These advertisements can be directed based on demographic characteristics like face and gender and previous customer transactions. Additionally, providing the nearest supermarket they can reach based on their current location. Queue management is the next most crucial facility that needs to be provided to a supermarket. However, the manual system of queue management is not effective. But with a modernized queue management system, overcrowded supermarkets can be managed effectively. This proposed system also considers providing a chatbot service to manage customer inquiries in a reliable strategy. In this system, we mainly used the Keras model called VGGFace for face detection, the Conventional Neural Network and Keras-based model for gender detection, the TensorFlow model called Single Shot MultiBox Detection MobileNet for queue and crowd detection, the Apriori algorithm base model for predicting the buying pattern, a Keras-based model for Artificial Intelligence chatbot and finally, google map Application Programming Interface for the nearest supermarket finding are models and technology. This system was developed to manage a supermarket properly. © 2022 IEEE.

关键词： Sales

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Autonomous Learning of Fuzzy Recurrent Neural Networks for Human Activity Recognition

Autonomous Learning of Fuzzy Recurrent Neural Networks for H...

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2023 International Conference on Machine Learning and Cybernetics, ICMLC 2023

作者： Liang, Shuai Bing Loo, Chu Kiong Sabri, Aznul Qalid Md Wong, Kok Wai Universiti Malaya Faculty of Computer Science and Information Technology Department of Artificial Intelligence Malaysia School of Engineering and It Murdoch University MurdochWA Australia

ISBN: (纸本)9798350303780

In this article, an Autonomous Fuzzy Echo State Network (AFESN) algorithm is being proposed. This algorithm combines Autonomous Learning Multi-Model Systems and Echo State Network (ESN) to perform Human Activity Recognition on the Heterogeneity Human Activity Recognition HHAR dataset. We incorporate the structural information of the dataset into the ESN by using the Takagi-Sugeno (TS) models/rules concept. The process of obtaining the structural information in the dataset was fully automated by the unimodal density based membership function, which then acts as the antecedent part. Subsequently, a consequent part composed by ESN was used to replace the affine models commonly used in TS models. The final model predictions are inferred by the fuzzy-weighed mechanism in a new fuzzy rule composed of multiple ESNs. Since our algorithm is fully automatic and does not require any prior knowledge, its use in online learning scenarios is adequately applicable. Lastly, the effectiveness of the algorithm is tested using the HHAR dataset and an accuracy of 42.9% was obtained. Compared with the performance of recent Autonomous Learning Multi-Model Systems (19.6%), our algorithm has gained a significant improvement. © 2023 IEEE.

关键词： Membership functions

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Harnessing Artificial Intelligence for High-Impact Data Science Applications

Harnessing Artificial Intelligence for High-Impact Data Scie...

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2023 IEEE International Conference on Paradigm Shift in information Technologies with Innovative Applications in Global Scenario, ICPSITIAGS 2023

作者： Singh, Akhilendra Pratap Shreenidhi, H.S. Jain, Narendra Kumar Vanaja, T. Wanjale, Kirti H. Dehankar, Pooja Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh India Faculty of Engineering and Technology Department of Computer Science and Engineering Karnataka Bangalore India Vivekananda Global University Department of Civil Engineering Jaipur India Prince Shri Venkateshwara Padmavathy Engineering College Department of Information Technology Chennai India Vishwakarma Institute of Information Technology Department of Computer Engineering Pune India School of Engineering Ajeenkya D. Y. Patil University Pune India

ISBN: (纸本)9798350329773

The software of synthetic Intelligence (AI) has end up more and more widespread in each industry and academia as a powerful tool for transforming statistics into precious insights. AI is especially effective for facts technological know-how packages, permitting agencies to pick out styles, traits, and correlations inside huge datasets. By using leveraging AI for records technological know-how packages, agencies can advantage actionable insights which include predictive analytics, forecast destiny occasions, and optimize results. This paper provides an in depth overview of the usage of AI in statistics technological know-how, the advantages of the use of AI, and the challenges related to its utility. An overview of several excessive-effect facts technology applications is likewise supplied, consisting of gadget getting to know, virtual fitness, herbal language processing, predictive analytics, and pc vision. The potential packages of AI are colossal and blanketed as a part of a complete information technological know-how strategy;it is able to offer corporations with a massive competitive benefit. © 2023 IEEE.

关键词： Predictive analytics

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Neutrosophic Model for Evaluation Healthcare Security Criteria for Powerful and Lightweight Secure Storage System in Cloud-Based E-Healthcare Services

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Neutrosophic Sets and Systems 2023年 58卷 367-378页

作者： El-Douh, Ahmed A. Lu, SongFeng Abdelhafeez, Ahmed Ali, Ahmed M. Aziz, Alber S. School of Cyber Science and Engineering Huazhong University of Science and Technology Wuhan430074 China Faculty of Information Systems and Computer Science October 6th University Giza12585 Egypt Faculty of Computers and Informatics Zagazig University Sharqiyah Zagazig44519 Egypt

Large data volumes make manually keeping and preserving health records for future reference problematic. Most unusual is the coronavirus epidemic's overcrowding of hospitals. The Secure Pattern Electronic Healthcare Records (SPEHR) scheme provides a powerful and lightweight secure storage system for cloud-based E-healthcare services that meets remote healthcare security criteria. So we proposed a neutrosophic model with a multi-criterion decision-making (MCDM) method for the analysis and evaluation of these criteria. The neutrosophic model is used to deal with vague and uncertain data. Then we integrated the neutrosophic model with the AHP method to rank and compute the weights of the criteria. Offering stakeholders a secure interface and avoiding unwanted access to cloud-stored data mitigates E-healthcare risks. The key derivation ensures end-to-end data. ciphering to prevent unauthorized use (KDF). This work provides robust security solutions for various environments. This work can meet security needs for people and secure-communicating organizations. We found the data privacy is the best criterion. © (2023). All Rights Reserved.

关键词： Access control

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Partial Discharge Localization Model in Power Transformer with Fingerprinting Technique 9

Partial Discharge Localization Model in Power Transformer wi...

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9th International Conference on engineering, Applied Sciences, and technology, ICEAST 2023

作者： Chaisang, Aditep Tiengthong, Thanadol Maw, Myo Myint Promwong, Sathaporn Rambhai Barni Rajabhat University Faculty of Industrial Technology Chanthaburi22000 Thailand School of Engineering King Mongkut's Institute of Technology Ladkrabang Bangkok10520 Thailand Mandalay Technological University Faculty of Engineering Dept. Computer Engineering and Information Technology Mandalay Myanmar

ISBN: (纸本)9798350322040

Partial discharge localization in power transformers is of utmost importance, requiring an effective evaluation method to identify the location of such events precisely. Antenna placement poses challenges within power transformers, as improper positioning can significantly affect localization precision. This paper introduces an evaluation of the fingerprinting method for ultra-high frequency partial discharge localization. The fingerprinting method, commonly employed in wireless localization systems, is utilized to assess the accuracy of partial discharge localization. The proposed method leverages fingerprinting analysis and received signal strength to evaluate partial discharge events in power transformers. Experimental partial discharge measurements are conducted on a power transformer model provided by Tesla Power Company. The results include the average received signal strength at each measurement position and the distance error of the partial discharge location determined using the fingerprinting method. This research contributes to assessing partial discharge in power transformers, offering valuable insights for enhancing their health and performance evaluation. © 2023 IEEE.

关键词： Partial discharges

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A Data Analysis Method Using Orthogonal Transformation in a Reproducing Kernel Hilbert Space

A Data Analysis Method Using Orthogonal Transformation in a ...

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2023 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2023

作者： Qu, Lingxiao Pei, Yan Li, Jianqiang Graduate School of Computer Science and Engineering University of Aizu Fukushima Aizuwakamatsu965-8580 Japan Beijing University of Technology Faculty of Information Technology Beijing100124 China

ISBN: (纸本)9798350337020

We propose a data analysis method that combines the objectives of nonlinear principal component analysis and nonlinear discriminant analysis with the kernel method in a reproducing kernel Hilbert space. This method addresses nonlinear data analysis problems in high-dimensional spaces, specifically the reproducing kernel Hilbert space, through the use of the kernel trick. Our proposed method can be considered as a semi-supervised data analysis approach. We evaluate our proposed method using various kernel functions and datasets, both visually and quantitatively. The evaluation results demonstrate that our proposal outperforms kernel principal component analysis and generalized discriminant analysis in terms of classification performance. This indicates the advantages and originality of our proposed method. Furthermore, we analyze and discuss our findings based on the evaluation results, and highlight potential areas for further research and future work related to our proposal. © 2023 IEEE.

关键词： Data Analysis Method Data Science Kernel Method Linear Discriminant Analysis Principal Component Analysis

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Dual Radial-Resonant Wide Beamwidth Circular Sector Microstrip Patch Antennas

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Chinese Journal of Electronics 2023年第4期32卷 710-719页

作者： MAO Xiaohui LU Wenjun JI Feiyan XING Xiuqiong ZHU Lei Jiangsu Key Laboratory of Wireless Communications Nanjing University of Posts and Telecommunications Key Laboratory of Wireless Sensor Network & Communication Shanghai Institute of Microsystem and Information Technology Chinese Academy of Sciences Department of Electrical and Computer Engineering Faculty of Science and Technology University of Macau

In this article, a design approach to a radial-resonant wide beamwidth circular sector patch antenna is advanced. As properly evolved from a U-shaped d ipole, a prototype magnetic dipole can be fit in the radial direction of a circular sector patch radiator, with its length set as the positive odd-integer multiples of onequarter wavelength. In this way, multiple TM0m（m = 1,2,...） modes resonant circular sector patch antenna with short-circuited circumference and widened E-plane beamwidth can be realized by proper excitation and perturbations. Prototype antennas are then designed and fabricated to validate the design approach. Experimental results reveal that the E-plane beamwidth of a dual-resonant antenna fabricated on air/Teflon substrate can be effectively broadened to 128°/120°, with an impedance bandwidth of 17.4%/7.1%, respectively. In both cases, the antenna heights are strictly limited to no more than 0.03-guided wavelength. It is evidently validated that the proposed approach can effectively enhance the operational bandwidth and beamwidth of a microstrip patch antenna while maintaining its inherent low profile merit.

关键词： Geometry Patch antennas Perturbation methods Prototypes Magnetic resonance Microstrip antennas Bandwidth

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Transforming Homes into Smart Havens: Advanced Control with NodeMCU and Android technology 4

Transforming Homes into Smart Havens: Advanced Control with ...

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4th International Conference on Power, Energy, Control and Transmission Systems, ICPECTS 2024

作者： Selvarathi, C. Santhi, P. Deepa, K. Shri, G. Ramya Visali, C. Abirami, T. Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Department of Computer Science and Engineering Avadi Tamilnadu Chennai600 062 India Srm Institute of Science and Technology Faculty of Engineering and Technology Department of Computer Science and Engineering Tamilnadu Tiruchirapalli India M. Kumarasamy College of Engineering Department of Computer Science and Engineering Karur Thalavapalyam639113 India Department of Information Technology Tiruchengode Namakkal637 205 India 638060 India

ISBN: (纸本)9798331508845

Creating groundbreaking solutions that benefit the populace is imperative in the modern era. The Internet of Things (IoT) serves as a trailblazing sector, fostering the development of contrivances automating an array of tasks. The IoT encompasses an interlinked network of cyber-connected contrivances executing functions with minimal human intervention. Capitalizing on IoT principles, this exploration endeavors to contrive a device aiding individuals grappling with mobility impediments. The envisioned gizmo consists of two primary sectors: a hardware module featuring a channel relay, Arduino, and an astute luminescent bulb, and a software element encompassing cloud and IoT platforms alongside a purpose-built app. The chief function of this contraption is to discern specific vocalizations in an individual's utterances, effectuating or deactivating the astute contraption to institute an intelligent habitation. In the initial phase, a luminous bulb will serve as a demonstration, employing for app origination. The distinctive aspect of this program lies in its vocalization-receptive microphone, with Bluetooth and Wi-Fi chips augmenting transmission velocity between the luminescent bulb and the mobile device. Meticulous attention will be accorded to auditory sensitivity and expeditious data transmission, with potential integration of diverse contrivances like ventilators and temperature-regulating apparatus into the envisioned gizmo. Furthermore, contemplation extends to a fortified safety attribute ensuring singular response to a particular vocal identity. © 2024 IEEE.

关键词： Luminescent devices

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