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The Past, Present, and Future of Storage Technologies (Part 1 of 2)

ACM TRANSACTIONS ON STORAGE 2025年第1期21卷 1-3页

作者： Kuenning, Geoff Won, Youjip Zhao, Ming Computer Science Harvey Mudd College Claremont United States Electrical Engineering Korea Advanced Institute of Science and Technology Daejeon Korea (the Republic of) School of Computing and Information Sciences Arizona State University Tempe United States Computer Science Stony Brook University Stony Brook United States

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Mitigation for cloud computing security risks and governance

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International Journal of Cloud computing 2022年第5-6期11卷 560-567页

作者： Jabez, J. Narmadha, R. Porkodi, S. Devi, L. School of Computing Sathyabama Institute of Science and Technology Chennai India School of Electrical and Electronics Engineering Sathyabama Institute of Science and Technology Chennai India College of Engineering and Computer Science Lebanese French University Erbil Iraq PGCS Department Muthayammal College of Arts and Science Rasipuram India

The recent prosperous of cloud computing has become the biggest revenue for originalities with the issues of intricate servers that need regular maintenance, security, power and cooling systems throughout. Hence, it is extremely significant for any cloud service earner is to offer dense security models and policies to all users involves. Although creating best suited security strategies might necessitate enormous amount of reserve and endurance, it will bounce the casual for end user to relay on a computerised security system throughout. The cloud environs supplementary strongly secure, qualifying security hazards, appropriate controls must be imposed. Major contest is to consider cloud security and governance explanation together. In this segment, the emphasis will be in the contests involved in preserving a dependable security policy computerisation in at the application layer, network layer and host level of cloud computing. Moreover, securities related to models will be discussed to recruit for those security applications which are more composite and active. Copyright © 2022 Inderscience Enterprises Ltd.

关键词： Security systems

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A Novel Method of Evaluating the Harmonic Power Analyzer's Performance for PC-Based Testing and Measurement Applications Related to Electromagnetic Compatibility 2

A Novel Method of Evaluating the Harmonic Power Analyzer's P...

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2nd International Conference on computing and Data Analytics, ICCDA 2024

作者： Adeline Sneha, J. Wilfred Blessing, N.R. Palarimath, Suresh Poorana Senthilkumar, S. Manigandansekar Sutherlin Subitha, G. School of Computing Asia Pacific University of Technology & Innovation Kuala Lumpur Malaysia College of Computing and Information Sciences University of Technology and Applied Sciences Ibri Oman College of Computing and Information Sciences-Salalah University of Technology and Applied Sciences Oman Dr. N. G. P Arts and Science College Department of Computer Applications Tamil Nadu Coimbatore India Newyork University Abudhabi United Arab Emirates Stella Mary's College of Engineering Department of Computer Science and Engineering Tamil Nadu Kanyakumari India

ISBN: (纸本)9798331542573

This paper discusses the methods for performance analysis of a PC-based harmonic power analyzer used in EMC testing and measuring applications. According to IEC 61000-3-2, this is an easy-to-use, reasonably priced way to assess how well a harmonics emission measurement system is performing in real time. There is no mention of any alternative approach or calibration method to verify the performance analysis in the IEC 61000-3-2 standard. Different vendor equipment is used to create a single harmonic emission monitoring setup. Thus, getting calibrating services is a highly difficult task that also requires a significant financial investment. Using this straightforward, low-cost analysis technique, it is possible to monitor the operation of the measurement setup locally and address all of these problems. Overall, the paper provides a comprehensive overview of the new approach to performance analysis of a PC-based harmonics power analyzer for EMC test and measurement applications, emphasizing the importance of a simple, cost-effective, and reliable method for maintaining measurement system performance. © 2024 IEEE.

关键词： Cost effectiveness

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Interior Angle Computation for detecting Adversary Sensor in Wireless Sensor Networks

Interior Angle Computation for detecting Adversary Sensor in...

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2023 IEEE International Conference on Intelligent and Innovative Technologies in computing, Electrical and Electronics, ICIITCEE 2023

作者： Saranya, R. Anitha, K. Khan, A. Ayub Sivakumar, M. Arthi, R. RMK College of Engineering and Technology Department of Computer Science and Engineering Tamil Nadu Chennai India School of Computing SRM Institute of Science and Technology Kattankulathur Department of Computing Technologies Tamil Nadu Chennai India Sona College of Technology Department of Electronics and Communication Engineering Tamil Nadu Salem India Sri Krishna College of Engineering and Technology Department of Computer Science and Engineering Tamil Nadu Coimbatore India Tamil Nadu Namakkal India

ISBN: (纸本)9781665462631

After being distributed over a wireless sensor network (WSN), the sensor nodes in the network normally remain in the same place permanently. An attacker who compromises a subset of the nodes is not essential to stand by the same restriction. This article introduces Interior Angle Computation for detecting adversary sensor (IACD) in WSN. The main awareness of this scheme for applying the angle-based method is to decide the adversary node. In this case, the sender wishes to transmit the information to the receiver, and the sender selects the neighbor node that will serve as the next hop in the network. The subsequent hop chooses, from among the neighbors of the sender node, the sensor node that is geographically closest to the recipient. The sender selected the neighboring node, and the sensor node that was physically closest to it created the triangle. In this triangle, the three inner angles add up to a total of 180 degrees, and in order to achieve a value of 180 degrees for the triangle, each of these three nodes must be a genuine sensor node. If it is not, then the node is an opponent. In addition, this approach applies a binary tree algorithm to improve the routing efficiency. It improves routing efficiency. The simulation results explain that the IACD has a better packet rate and increases the remaining energy in the network. In addition, it increases the adversary detection ratio in the WSN. © 2023 IEEE.

关键词： Sensor nodes

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AI-Enhanced Cloud Security Framework for IoT Networks Using a Predictive Analytics Approach 3

AI-Enhanced Cloud Security Framework for IoT Networks Using ...

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3rd International Conference for Advancement in technology, ICONAT 2024

作者： Ramesh Naidu, P. Dankan Gowda, V. Gujar, Shantanu Sudhir Shaikh, Salman Firoz Shandilya, Saurabh Sudhakar Reddy, N. Nitte Meenakshi Institute of Technology Department of Computer Science and Engineering Karnataka Bangalore560064 India BMS Institute of Technology and Management Department of Electronics and Communication Engineering Karnataka Bangalore India Rochester Institute of Technology Golisano College of Computing and Information Sciences Department of CyberSecurity RochesterNY14623 United States Rochester Institute of Technology Golisano College of Computing and Information Sciences Department of Computer Science RochesterNY14623 United States Poornima College of Engineering Department of Advance Computing Rajasthan Jaipur India Mohan Babu University School of Engineering Department of ECE Tirupati India

ISBN: (纸本)9798350354171

The use of IoT with cloud computing has seen a massive improvement when it comes to data processing as well as connectivity. However, this has its own set of security problems like violation of access, leakage of information and issues with respect to scaling up. These challenges are fundamental and complex, and so this paper seeks to introduce an AI-cloud security framework that incorporates the use of predictive analytical functions. It is used to provide a real-time measure of security threats in IoT networks with a view of safeguarding both the data and the devices used. The values of precision and recall were 95 percent and 90 percent, respectively, with an overall anomaly detection rate higher than the previous threat detection methods. The framework also unveiled overall improvements in response time and false positive rates over the conventional methods. Such findings suggest that implementing AI and predictive analytics into cloud security frameworks for IoT networks are highly conceivable. Concerning future work, the research underlines the need for security solutions that can adapt to IoT's increasing connectivity requirements in numerous applications and would open the path for the next developments in IoT protection frameworks. © 2024 IEEE.

关键词： Cloud security

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Design of an Explainable AI-Assisted Arrhythmia Detection and Interpretation Model Using ECG Data

Design of an Explainable AI-Assisted Arrhythmia Detection an...

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International Conference on Business Intelligence and Information technology, BIIT 2023

作者： Banerjee, Sourav Tauro, Jacob Dasgupta, Kousik Barik, Sudip Debnath, Narayan C. Computer Science and Engineering Kalyani Government Engineering College Nadia Kalyani India School of Computing and Information Technology Eastern International University Binh Duong Viet Nam

ISBN: (纸本)9789819739790

Arrhythmia is a common cardiac condition characterized by irregular heartbeats that, if left untreated, can have major health effects. In this paper, we present a random forest-based binary classification method for identifying arrhythmia. The random forest approach is an ensemble learning methodology that can handle large datasets with little overfitting, making it a good choice for analysing medical data. Moreover, the interpretability of the model is further improved by the Explainable AI in the form of decision tree analysis, which offers vital insights into the individual ECG aspects impacting the classification choices. The science of arrhythmia diagnosis and patient treatment is finally advanced because of this openness, which also helps physicians make wise decisions based on the model’s predictions. The experiment was performed on the MIT-BIH ECG dataset by applying a 75–25 split. The accuracy of 98.99 was achieved using random forest classifier, and then using decision tree explainer, we found out the most significant features for the classification, and the explanation tree illustration helps decode the reason for the classification of the data for normal or arrhythmia classes. This explainer model will help the healthcare personnel to better understand and take decision for the betterment of the patients. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Diseases

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Monitoring and Evaluating ECU Communication Data for Vulnerabilities Detection 5th

Monitoring and Evaluating ECU Communication Data for Vulnera...

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5th Doctoral Symposium on Computational Intelligence, DoSCI 2024

作者： Samanta, Samadrita Biswas, Rahul Mishra, Sushruta Kumar, Anil Dheidan, Ali Hasan Kalinga Institute of Industrial Technology Patia Odisha Bhubaneswar751024 India School of Computing DIT University Dehradun India College of Technical Engineering National University of Science and Technology Dhi Qar 64001 Iraq

ISBN: (纸本)9789819767250

In today's automotive industry, Electronic Control Units (ECUs) control a large number of functions in vehicles. Increasing cyberattacks on ECUs pose a danger to vehicle safety and security due to the rising dependence on automation and Electronic Control Units (ECUs). This study proposes a new way to find ECU attacks by using Python's large library and tools for automotive security. The three main parts of the approach are collecting and processing data, and finding outliers. To gather data, an Arduino and a CAN bus shield are used to make a CAN network and record the data that the ECUs send and receive. Among the preprocessing tasks is the determination of the time intervals for message reception among nodes and the standardization of data to account for variances caused by hardware constraints. Examining the slope of data plots is a technique used for anomaly detection. The compromised Electronic Control Unit (ECU) is detected by a noticeable change in the slope, which indicates a potential attack. A proof-of-concept illustrates the strategy's efficacy. By inserting an adversarial Electronic Control Unit (ECU), which interferes with normal ECU communication patterns, we can simulate real-life attack scenarios. This Python-based method finds different threats successfully and with high accuracy. This study makes a big contribution to the fields of cyberphysical systems and automotive cybersecurity by showing a reliable way to detect attacks on Electronic Control Units (ECUs) that using Python. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Automotive industry

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Tangles in IOTA to make crypto currency transactions free and secure

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International Journal of Cloud computing 2022年第1期11卷 1-13页

作者： Anakath, A.S. Kannadasan, R. Prabakaran, N. Basha, M.S. Saleem Department of MCA EGS Pillai Engineering College Nagapattinam 611002 India School Computer Science and Engineering Vellore Institute of Technology Vellore632014 India Department of Computing and Informatics Mazoon College Muscat133 Oman

Blockchain introduction has made a revolutionary change in the crypto currency around the world but it has not delivered on its promises of free and faster transaction confirmation. Serguei Popov's proposal of using tangles, a directed acyclic graph, which essentially is considered to be the successor of blockchains and offers the required features like machine to machine micro payment and fee-less transaction. It requires the user to approve the previous two transactions in the web to participate in the network. This essentially eliminates the miners and the mining part form the currency exchange and provides the user or participants to do their transactions fee-less. Since the participant verifies the previous two transactions it also contributes to the security of the tangle. In this paper, features of internet of things application (IOTA) and all the improvements in it using tangles are discussed along with how it contributed to the security and how it enables the participants to have fee-less transactions is also discussed. Copyright © 2022 Inderscience Enterprises Ltd.

关键词： Distributed ledger

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Board 61: Work in Progress: Teaching Logic Design with Interactive Computer Games

Board 61: Work in Progress: Teaching Logic Design with Inter...

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2024 ASEE Annual Conference and Exposition

作者： Ketineni, Arnav Ketineni, Hrithik Liu, Kyle Perkowski, Marek Department of Electrical and Computer Engineering Portland State University United States Robbinsville High School United States Westview High School United States College of Computing Georgia Institute of Technology United States

Sum-of-Products (SOP) expressions are two-level representations of Boolean functions consisting of an OR sum of AND terms. There exist many methods of SOP synthesis, but the Karnaugh map method is the most frequently taught in undergraduate curriculum. Unfortunately, most traditional approaches to teaching Karnaugh map-based SOP minimization are not very engaging for the learner. To increase student engagement, game-based approaches to teaching are increasingly being used to supplement traditional teaching methods. There has been limited research into extending such game-based teaching approaches towards SOP minimization with Karnaugh maps. This paper proposes a game to teach Karnaugh map-based SOP minimization. The players of the proposed learning game seek to maximize the true minterms they individually cover within the Karnaugh map through a back-and-forth turn-based model. The system consists of both a two-player version between two human players and a single-player version that involves a computer opponent in place of a second human player. This game makes learning about Karnaugh map-based SOP minimization more engaging and convenient to practice. Results found significant increases in learning retention and self-reported engagement for users of both the single and two-player versions compared to conventional teaching methods. These findings underscore the potential that incorporating game design elements into instruction can have in enhancing students' understanding of topics such as SOP minimization and Karnaugh maps. These results highlight the importance of future research investigating the educational benefits of applying game-based learning to other introductory logic design topics. © American Society for engineering Education, 2024.

关键词： Boolean functions

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Prediction of Kidney Disease Utilizing a Hybrid Deep Learning Methodology 2

Prediction of Kidney Disease Utilizing a Hybrid Deep Learnin...

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2nd International Conference on Computer, Communication and Control, IC4 2024

作者： Nallarasan, V. Ponnusamy, Vijayakumar Lakshminarayanan, R. Sona, K. Vigneshwari, S. Vinoth, R. Srm Institute of Science and Technology School of Computing Department of Networking and Communications Chengalpattu Kattankulathur India Srm Institute of Science and Technology Department of Electronics and Communications Chengalpattu Kattankulathur India Sri Ramakrishna Engineering College Department of Computer Science and Engineering India V.S.B College of Engineering Technical Campus India Gojan School of Business and Technology Department of Information Technology RedhillsTamilnadu Chennai600052 India

ISBN: (纸本)9798350387933

The kidney is an essential organ inside the human body, playing a crucial role in several physiological processes. One of its primary roles is the filtration of waste products and surplus fluids from the bloodstream, facilitating their subsequent elimination via urine production. In order to mitigate potential life-threatening complications, it is essential to identify and investigate chronic renal illnesses. The suggested method takes into account the limitations of early prediction and robust decision-making oscillations due to the presence of False Positive Rates in Kidney CT Images. The suggested system incorporates a hybrid method that combines machine learning and deep learning techniques. A prognostic method is developed by using the kidney dataset collected from TCIA, which involves the analysis of patients' past health information. The suggested system incorporates a hybrid approach of random forest regression and multinomial regression algorithms to identify the Explorer data analysis technique for the chronic kidney disease dataset. The secondary approach involves using a computer tomography image dataset obtained from the TCIA public data set. This dataset is processed using a deep convolutional neural network (DCNN) architecture that has many layers of deep convolution filters. The purpose of this architecture is to accurately detect and classify kidney abnormalities within the images. The integration of main and secondary outcomes is used to determine the presence or absence of renal disease in a patient. In this study, we examine a unique methodology known as Hybrid Deep K-Net (H-DKN). The accuracy reached by HDKN is reported to be 97%. Furthermore, we compare this approach with many state-of-the-art methods that have been established on the current platform. © 2024 IEEE.

关键词： Decision making

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