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Technological Advancements and Innovations (ICTAI), International Conference on

作者： Sanjay Madan Monika Singh Punjab Engineering College Chandigarh India Centre for Development of Advanced Computing Mohali Punjab India Chandigarh University Mohali Punjab India

ISBN: (纸本)9781665420884

Every day, attackers target embedded IoT devices, causing damage to key cyber-infrastructure, obtaining users’ personal information, and misusing it to a greater extent. Data confidentiality, authentication, and privacy, denial of service, nonrepudiation, and digital content protection are only a few of the difficult security challenges that must be handled. To exploit these resource-constrained Cyber-physical systems, attackers use brute-force assaults, man-in-the-middle attacks, injecting malicious code, eavesdropping, and backdoors, among other methods. In this research, we present a hybrid analysis method for analyzing Linux-based IoT malware and event correlation for incident management using anomaly detection. For malware classification, the machine learning model is built using information from both static and dynamic analysis of harmful programs. For anomaly identification and event correlation, the anomalous DDoS traffic detection approach is also proposed. The F1-score is maximized for various DDoS attacks using the threshold selection approach, and the results are compared to the state-of-the-art literature.

关键词： Data privacy Technological innovation Correlation Machine learning Cyber-physical systems Denial-of-service attack Malware

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A Blockchain Based Vehicular Ad-hoc System

A Blockchain Based Vehicular Ad-hoc System

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International Conference on advanced Computer Control, ICACC

作者： Samuel Sabu Thomas Anjana S Viswesh Parameswaran Sidharth A J Arya Paul Vyshnav C J Jayesh T P Zenyze Labs Ernakulam India Growing Stars Infotech Ernakulam India Riafy Technologies Ernakulam India Vector India Pvt Ltd Bangalore India Electronics and Communication Engineering Adi Shankara Institute of Engineering and Technology Ernakulam India Centre for Development of Advanced Computing (CDAC) Trivandrum India Electronics and Communication Engineering Jawaharlal College of Engineering and Technology Palakkad India

ISBN: (数字)9798350379136

ISBN: (纸本)9798350379143

As connected vehicles become more prevalent, vehicular ad-hoc networks (VANETs) are being used to support vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communications for advanced driver-assistance systems (ADAS) and other intelligent services. However, secure communication is crucial in VANETs to prevent traffic accidents and ensure the safety of drivers and passengers. Many studies have been conducted on V2I authentication protocols, but most do not consider handover situations and can cause unnecessary computations, which can overload vehicles with limited computing resources. To address these issues, researchers have proposed a blockchain-based handover authentication protocol for VANETs. This protocol leverages the strength of blockchain technology to provide decentralization, data integrity, and transparency. It also ensures efficiency by only requiring lightweight computations during handover situations. The proposed protocol was subjected to formal analysis using Burrows–Abadi–Needham (BAN) logic, Real-Or-Random (ROR) oracle model, and Automated Validation of Internet Security Protocols and Applications (AVISPA) simulation. The researchers also conducted simulations using Network Simulator 3 (NS-3) to verify the practicality of the proposed protocol. Computational cost and security features of the proposed protocol were compared with existing protocols, demonstrating that the proposed protocol is more secure and efficient. Overall, the blockchain-based handover authentication protocol has the potential to improve the security and efficiency of VANETs, enabling safe and reliable communication between vehicles and infrastructure.

关键词： Protocols Computational modeling Vehicle-to-infrastructure Authentication Vehicular ad hoc networks Handover Computational efficiency Blockchains Safety Security

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A Framework of Internet of Things (IOT) for the Manufacturing and Image Classifaication System 2

A Framework of Internet of Things (IOT) for the Manufacturin...

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2nd International Conference on Advance computing and Innovative Technologies in Engineering, ICACITE 2022

作者： Gupta, Ayan Das Rafi, Shaik Mohammad Singh, Nagendra Gupta, Vikram Kumar Jaiswal, Sushma Gangodkar, Durgaprasad Chandernagore Government College Department of Geography West Bengal Hooghly India Chandernagore Government College Affiliated to the University of Burdwan India Artificial Intelligence and Information Technology Sri Mittapalli College of Engineering Andhrapradesh Guntur India Embedded Systems Centre for Development of Advanced Computing Noida India Quality and Reliability IIT Kharagpur India CG Bilaspur India Computer Science & Engineering Graphic Era Deemed to Be University Uttarakhand Dehradun India

ISBN: (纸本)9781665437899

Real-time identification of industrial processes and real-time image classification are necessary for recent days to reduce the excess power consumption and detect water pollution respectively. Usually, robotic technology in manufacturing industries is a costly initiative;thus, researchers are searching for a low-cost and effective loT (Internet of Things) technology that will detect and measure real time-condition of industrial machines. Moreover, the loT technology is useful in image classification as well for detecting water pollution. This research has explained the benefits and cost-effectiveness of available loT along with a comparison between image classification techniques. A primary quantitative survey method has been carried out to collect practical information based on the judgement of 60 respondents. Thereafter, the 'Purposive' sampling technique has been applied to discuss the primary data and uphold a significant judgement. Findings and analysis suggested that WSN (Wireless Sensor Network) is a cheaper technology that can be integrated into small- and large-scale manufacturing industries. Image classification loT has been identified for detecting water pollution where texture analysis is cheaper than spatiotemporal analysis. © 2022 IEEE.

关键词： Internet of things

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Optimal Geospatial Query Placement in Cloud 1st

Optimal Geospatial Query Placement in Cloud

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1st International Conference on Intelligent and Cloud computing, ICICC 2019

作者： Das, Jaydeep Addya, Sourav Kanti Ghosh, Soumya K. Buyya, Rajkumar Advanced Technology Development Centre Indian Institute of Technology Kharagpur KharagpurWest Bengal721302 India Department of Computer Science and Engineering Indian Institute of Technology Kharagpur KharagpurWest Bengal721302 India School of Computing and Information Systems University of Melbourne MelbourneVIC3010 Australia

ISBN: (纸本)9789811559709

computing resources requirements are increasing with the massive generation of geospatial queries. These queries extract information from a large volume of spatial data. Placement of geospatial queries in virtual machines with minimum resource and energy wastage is a big challenge. Getting query results from mobile locations within a specific time duration is also a major concern. In this work, a bi-objective optimization problem has been formulated to minimize the energy consumption of cloud servers and service processing time. To solve the problem, a crow search based bio-inspired heuristic has been proposed. The proposed algorithm has been compared with traditional First Fit and Best Fit algorithms through simulation, and the obtained results are significantly better than the traditional techniques. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Energy efficiency

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Wearable Sensors based Smart Secured Remote Health Monitoring System

Wearable Sensors based Smart Secured Remote Health Monitorin...

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Advances in Electrical, computing, Communication and Sustainable Technologies (ICAECT), International Conference on

作者： Aritra Ray Hena Ray A. K. C. School of Information Technology University of Calcutta Kolkata India Centre for Development of Advanced Computing Kolkata India

ISBN: (数字)9781728157917

ISBN: (纸本)9781728157924

There is a growing need of remote health monitoring systems that can monitor an array of health parameters and alert concerned individuals about the same, thereby maintaining the security of private medical data. Through our sensor array, consisting of electro-cardiogram, pulse rate, oximeter and accelerometer sensor whose output signals were conditioned through tuning of the exponential moving average parameter, we encrypted and transmitted it to the connected fog node, wherein some computations are performed before the data were being pushed to the Cloud platform for human activity monitoring and disorder detection though our designed algorithms. Alerts are released immediately to the concerned individuals, including the medical experts, with immediate data visualization through Android application. The system has achieved about 90% accuracy in our testing samples.

关键词： Data visualization Cryptography Monitoring Wearable sensors Tuning Testing Sensor arrays

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EpiClim: Weekly District-Wise all-India multi-epidemics Climate-Health Dataset for accelerated GeoHealth research

arXiv

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arXiv 2025年

作者： Kaur, Gurleen Ghoshal, Shubham Marbate, Reena Malviya, Neetiraj Kaur, Arshmehar Sb, Vaisakh Srivastava, Amit Kumar Singh, Manmeet Indian Institute of Science Education and Research Bhopal India Banaras Hindu University India Indian Institute of Public Health Delhi India Centre for Development of Advanced Computing Pune India Guru Tegh Bahadur Institute of Technology Delhi India Indian Institute of Tropical Meteorology Pune India Müncheberg Germany Jackson School of Geosciences University of Texas at Austin AustinTX United States

Climate change directly affects public health as it significantly influences the emergence and spread of epidemics. Factors such as temperature, precipitation majorly impact and promote the growth of prevalent diseases transmitted by vectors and water-borne diseases as seen from historical and contemporary evidence. We will see in this research work the correlation of various diseases like dengue, cholera, acute diarrheal disease and malaria with temperature for example dengue and malaria have a good correlation with temperature and cholera on the other hand usually outbreaks with anomalies with precipitation showing a good correlation with the precipitation factor. Collection of high quality data has become a must to be able to foster the growth of climate health models in understanding and predicting disease outbreaks due to climate variability. Innovative developments in weather and climate science, especially through AI-enabled numerical weather prediction, AI-NWP, boost confidence in forecasting key variables such as temperature and precipitation. However, a major obstacle to the integration of climate models with health prediction systems lies in the inaccessibility of comprehensive, publicly accessible health datasets for various diseases. Such data sets, especially on granular spatial and temporal scales, are crucial to advance climate health research and model development. In this paper we present the first weekly district-wise dataset for major epidemics spanning across India from 2009 to 2022. The data utilized in this study has been sourced from the Integrated Disease Surveillance Programme(IDSP),a publically available database maintained by the Government of India. This dataset, named "EpiClim: India’s Epidemic-Climate Dataset", bridges the gap by providing detailed insights into health data tailored for climate-health modeling. The data set offers insight into the temporal and spatial dynamics of diseases such as dengue, malaria, and acute-diarrheal di

关键词： Global warming

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Generating Graph from 2D Flowchart using Region-Based Segmentation

Generating Graph from 2D Flowchart using Region-Based Segmen...

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2020 IEEE International Students' Conference on Electrical, Electronics and Computer Science, SCEECS 2020

作者： Leena, C. Ganesh, M. Centre for Development of Advanced Computing Education Technology Unit Mumbai India SNDT Women's University P.G Dept of Computer Science Mumbai India

ISBN: (纸本)9781728148625

Visual content-based information retrieval intended message retrieval from infographics and their applications are gaining attention in many scientific domains. This seeks an understanding of the structure and correct semantics of infographics. Parsing flowchart and analyzing each element of infographics in the correct sequence is challenging. Using computer vision techniques, reconstruction of the structure in digital format is possible and can help to understand the features of the structure. This paper describes technical details to extract various elements of a 2D flowchart in a meaningful sequence, relate elements as connected in a flowchart and represent in conventional data structures. Region-based segmentation with adaptive thresholding and morphological operations are applied for feature extraction. The graph is generated by maintaining the semantics of the flowchart. The experimental results are evaluated for semantic correctness of flowchart and found that 90% of generated graphs are semantically correct as a flowchart. © 2020 IEEE.

关键词： Semantics

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Summarizing long scientific documents through hierarchical structure extraction

Natural Language Processing Journal

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Natural Language Processing Journal 2024年 8卷

作者： Grishma Sharma Deepak Sharma M. Sasikumar Department of Computer Engineering Somaiya Vidyavihar University Vidyavihar Mumbai 400077 India CDAC- Centre for Development of Advanced Computing Mumbai 400049 India

In the realm of academia, staying updated with the latest advancements has become increasingly difficult due to the rapid rise in scientific publications. Text summarization emerges as a solution to this challenge by distilling essential contributions into concise summaries. Despite the structured nature of scientific documents, current summarization techniques often overlook this valuable structural information. Our proposed method addresses this gap through an unsupervised, extractive, user preference-based, and hierarchical iterative graph-based ranking algorithm for summarizing long scientific documents. Unlike existing approaches, our method operates by leveraging the inherent structural information within scientific texts to generate diverse summaries tailored to user preferences. To assess the efficiency of our approach, we conducted evaluations on two distinct long document datasets: ScisummNet and a custom dataset comprising papers from esteemed journals and conferences with human-extracted sentences as gold summaries. The results obtained using automatic evaluation metric Rouge scores as well as human evaluation, demonstrate that our method performs better than other well-known unsupervised algorithms. This emphasizes the need for structural information in text summarization, enabling more effective and customizable solutions.

关键词： Extractive text summarization Hierarchical structure ScisummNet dataset Scientific paper summarization Rouge score

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A Traffic Monitoring and Policy Enforcement Framework for HTTP

A Traffic Monitoring and Policy Enforcement Framework for HT...

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ISEA ASIA SECURITY AND PRIVACY (ISEASP)

作者： N. Muraleedharan Anna Thomas S. Indu B.S. Bindhumadhava Centre for Development of Advanced Computing (C-DAC) Bangalore India

ISBN: (数字)9781728167084

ISBN: (纸本)9781728167091

Due to the accessibility and popularity of Internet, web based applications are commonly used for providing different services to the users. At the same time, the simplicity to conduct attacks and the availability of several attack tools have made web applications the most common target for attackers. Hence monitoring and analysis of web applications require special attention. In this paper, we describe a policy enforcement and web attack detection framework for HTTP protocol. The proposed framework can monitor and analyze HTTP traffic to detect injection, misconfiguration and directory traversal attacks. Moreover, this framework can be used to enforce web application access policies involving content type, URL and device level access.

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Performance Evaluation of Different Halftone Kernels for Binary Face Recognition

Performance Evaluation of Different Halftone Kernels for Bin...

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作者： Singh, Yumnam Kirani Vanlalhruaia Centre for Development of Advanced Computing Ground Floor IIPC Building NIT Silchar Campus Assam Silchar India National Institute of Electronics and Information Technology Mizoram Aizawl India

Face recognition is done gray or color images. Face recognition can be also done in binary images. Halftone images are binary images having gray shade information. These images are more informative as compared to binary images. Halftone images can be generated from different kernels. The quality of a halftone image depends on the kernel used to generate it. Halftone images can be used to generate human recognizable features for face recognition. The human recognizable features are fed to multiclass SVM classifiers for face recognition. The performance of using different human recognizable features generated from halftone images of different standard kernels is studied. It is found that some of kernels give higher recognition rate than the other. Also, the performance is also dependent on size of the window used for feature extraction. In most cases, the minimum size window 3 × 3 gives higher recognition rate in most of the cases. Of the standard kernels Frankie Siera-3, Stucki kernels give higher recognition rate and of the proposed kernels P2 kernel gives higher recognition rate than other proposed kernels. © 2020, Springer Nature Switzerland AG.

关键词： Face recognition

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