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A Survey of Traditional and Cloud Specific Security Issues
The emerging technology popularly referred to as Cloud computing offers dynamically scalable computing resources on a pay per use basis over the Internet. Companies avail hardware and software resources as service from the cloud service provider as opposed to obtaining physical assets. Cloud computing has the potential for significant cost reduction and increased operating efficiency in computing. To achieve these benefits, however, there are still some challenges to be solved. Security is one of the prime concerns in adopting Cloud computing, since the user's data has to be released from the protection sphere of the data owner to the premises of cloud service provider. As more Cloud based applications keep evolving, the associated security threats are also growing. In this paper an attempt has been made to identify and categorize the security threats applicable to Cloud environment. Threats are classified into Cloud specific security issues and traditional security attacks on various service delivery models of Cloud. The work also briefly discusses the virtualization and authentication related issues in Cloud and tries to consolidate the various security threats in a classified manner. Springer-Verlag Berlin Heidelberg 2013. -
A Signature-Based Mutual Authentication Protocol for Remote Health Monitoring
Remote health monitoring can offer a lot of advantage to all the players in healthcare industry and it can contribute to reduced healthcare expenses. Wireless medical sensor networks capable of accumulating and transferring vital parameters of patients play a crucial role in remote health monitoring. Security and privacy are major concerns preventing the patients from adopting this technology with an open mind. This paper presents a signature-based authentication protocol for remote health monitoring. The work also discusses an authentication protocol for the mutual authentication of users and medical server. The protocol does not require the server to maintain a password table. The proposed algorithms are resistant to various attacks such as replay attack, stolen verifier attack, and privileged insider attack. The work includes the informal and formal security analysis of the proposed protocols. Scyther tool is used for formal security analysis and the results show that the protocol is resistant to various common and automated attacks. 2019, Springer Nature Singapore Pte Ltd. -
A mobile based remote user authentication scheme without verifier table for cloud based services
The emerging Cloud computing technology, offering computing resources as a service is gaining increasing attention of both the public and private sector. For the whole hearted adoption of Cloud, the service providers need to ensure that only valid users gain access to the services and data residing within the provider's premises. Ensuring secure access to sensitive resources within the Cloud requires a strong user authentication mechanism using multiple authentication factors. The mechanisms should also consider the increasing needs of Internet access through smart phones and other mobile devices and facilitate access through a variety of devices. Traditionally, a user needs to maintain separate user accounts for each Service Provider whose service he/she desires to use and this may cause inconvenience to users. Single Sign on (SSO) addresses this issue by permitting users to create one login credential and access multiple services hosted in different domains. In this scenario, a compromise of the single credential can result in account take over at many other sites. This points out to the requirement of strengthening the authentication mechanism by using more than one factor. This paper proposes a SSO based remote user authentication scheme for a Cloud environment. The proposed protocol uses password and mobile token and does not require the server to maintain a verifier table. The protocol is verified using automated security Protocol verification tool, Scyther and the results prove that the protocol provides protection against man-in-the-middle attack, replay attack and secrecy of the user's credentials. 2015 ACM. -
A Single Sign on based secure remote user authentication scheme for Multi-Server Environments
A Multi-Server Architecture comprises of a server environment having many different servers which provides the user the flexibility of accessing resources from multiple Service Providing Servers using the same credential. The primary objective of a Multi Server Environment (MSE) is to provide services of different Service Providers (SPs) without repeating registration at each SP server, and to get a unique single credential for all the servers in MSE. However, the conventional MSEs, proposed by various researchers, proposes the individual authentication service by each SP on their respective server using the credential issued by the Registration Authority of MSE. The mechanism requires the user to access each SP by keying the same credentials for every SP separately. Single Sign On (SSO) is an authentication mechanism that enables a user to sign-on once and access the services of various SPs in the same session. SAML is generally used as a Single Sign-On protocol. This work analyzes the smart card based authentication scheme for Multi-Server Environment proposed by Li et al.'s and discuss various security attacks on the said scheme. The paper also proposes a Secure Dynamic-ID based scheme using smart cards or crypto cards which do not require a verifier table and implements Single Sign On feature using SAML protocol, thus allowing the user to enjoy all the features of an MSE along with SSO. 2014 IEEE. -
A proof of concept implementation of a mobile based authentication scheme without password table for cloud environment
Cloud computing is a fast growing technology offering a wide range of software and infrastructure services on a pay-per-use basis. Many small and medium businesses (SMB's) have adopted this utility based Computing Model as it contributes to reduced operational and capital expenditure. Though the resource sharing feature adopted by Cloud service providers (CSP's) enables the organizations to invest less on infrastructure, it also raises concerns about the security of data stored at CSP's premises. The fact that data is prone to get accessed by the insiders or by other customers sharing the storage space is a matter of concern. Regulating access to protected resources requires reliable and secure authentication mechanism, which assures that only authorized users are provided access to the services and resources offered by CSP. This paper proposes a strong two-factor authentication mechanism using password and mobile token. The proposed model provides Single Sign-on (SSO) functionality and does not require a password table. Besides introducing the authentication scheme, the proof of concept implementation is also provided. 2015 IEEE. -
A Quantitative Analysis of Trading Strategy Performance Over Ten Years
This study conducts a comparative analysis of two trading strategies over a ten-year period to assess their profitability and risk. Strategy 1 operates on a simple buy at close and sell at open principle, while Strategy 2 trades only when the closing price is above the 200-day moving average, introducing a conditional filter for market entry. Through the evaluation of performance metrics including total PNL, drawdown, standard deviation, and Sharpe ratio, the research highlights the differences in risk and return between the strategies. Results indicate Strategy 1 achieves higher profitability but at the cost of greater risk, as shown by larger drawdowns. Conversely, Strategy 2's conditional approach yields slightly lower returns but demonstrates a superior risk-adjusted performance. The findings emphasize the significance of risk management and the potential benefits of conditional filters in trading strategies, offering valuable insights for traders and investors in making informed strategy selections. 2024 IEEE. -
Perception and Practices of EdTech Platform: A Sentiment Analysis
Virtual and digital learning being the new normal, pandemic outburst and unexpected disruption in the functioning of educational services have paved way for online learning services. Considering the fast-Track growth of the education technology (EdTech) industry, in order to sustain, it is imperative for the industry to understand the underlying issues by capturing the end users' perception. The primary purpose of this research is to examine the perception of users towards EdTech platforms A sample of 600 reviews regarding three major EdTech platforms were scraped from MouthShut.com as textual data and analysed using lexicon-based method. The polarity of the sentiments pertaining to the reviews of different platforms was analysed using sentiment analysis. Furthermore, the topic modelling on the reviews was performed using natural language programming. The results revealed a positive sentiment of users towards the EdTech services and platforms. The most influential factors are faculty expertise, interface user-friendliness, syllabus, and pricing model. Our findings help EdTech service providers to understand which factors are driving this dramatic shift in student behaviour so they may develop better strategies to attract and retain consumers. Despite the rise in EdTech platform popularity, this is the first study to investigate perception of EdTech users comprehensively. 2022 IEEE. -
Effectiveness of Farmers Risk Management Strategies in Smallholder Agriculture: Evidence from India
Smallholder farmers in developing countries are more vulnerable to climate risks, and most of them, because of a lack of access to institutional risk management measures such as crop insurance, rely on traditional measures to offset the adverse effects of such risks on agricultural production. Employing a multinomial endogenous switching regression technique to the farm-level data, this study first identifies the determinants of farmers own risk management measures and then evaluates their impacts on farm income and downside risk exposure. There are three key highlights of this analysis. One, farmers, based on their past exposures to climate risks, endowments of resources, and access to credit and information, often use more than one measure or strategy to mitigate, transfer, and cope with the climate risks. Two, all the risk management strategies are found to be effective in improving farm income and reducing risk exposure, but it is their joint implementation that yields larger payoffs. Three, the joint adoption of different adaptation strategies is positively associated with farm size, but with liquidity and information constraints relaxed, the probability of their joint adoption is expected to increase further. These findings impinge on the concept of climate-smart agriculture and suggest the need to identify and integrate traditional farm management practices with science-based innovations to provide an effective solution to climate risks. 2021, The Author(s), under exclusive licence to Springer Nature B.V. -
Musculoskeletal Disorders and Psychological Well-being among Indian Nurses: A Narrative Review of Impacts and Interventions (2024)
Background: A prevalent occupational health issue that may have a detrimental effect on nurses' mental health and general well-being is musculoskeletal problems. This narrative review aimed to explore the social, economic, and personal implications of Musculoskeletal Disorder on nurses in India, and examine support, and intervention strategies available for them. Material & Methods: A comprehensive literature search was conducted in electronic databases, including PubMed, Scopus, and Google Scholar, using relevant keywords related to Musculoskeletal Disorder, mental health, nurses, social, personal, support, and intervention. The inclusion criteria were articles published in English and focused the nursing workforce in India. Results: A total of 15 articles were selected for review synthesis. According to the summary, nurses in India who suffer from musculoskeletal disorders deal with serious social and personal repercussions that impact their everyday life and general well-being. Musculoskeletal Disorder can lead to decreased social connections, reduced job satisfaction, and physical and emotional distress. However, limited interventions are available that address Musculoskeletal Disorder and the mental health of nurses in India. Conclusion: There is a significant effect of Musculoskeletal Disorder on the mental health, quality of life, and economic well-being of nurses in India. However, limited scientific research exists exploring the prevalence and psychosocial implications of Musculoskeletal Disorder in the Indian nursing population. Consequently, additional research is essential to comprehend the scope and ramifications of this occupational health concern. To create interventions and support systems that are effective in the unique cultural and occupational context of nursing in India, it is imperative to engage in interdisciplinary collaboration. 2024 The Author(s); Published by Rafsanjan University of Medical Sciences. -
Transformative Metamorphosis in Context to IoT in Education 4.0
In the modern technology-driven era, it is important to consider a new model of education to keep pace with Industry 4.0. In view of this, the present paper critically explores the issues, discusses potential solutions along with a comprehensive analysis of the applications of technologies such as Internet of Things (IoT) in modern education specially Education 4.0, and examines the potential of these technologies to transform the education sector. The challenges faced by previous education models are analysed along with how they pave the way to the inclusion of IoT in education, leading to Education 4.0. The potential benefits of IoT in improving learning outcomes, enhancing student engagement and retention, and supporting teachers are also highlighted. In addition, it addresses the ethical and privacy concerns associated with the use of these technologies and suggests areas for future research. 2023 A. K. Biswal et al. -
IoT-Based Response Time Analysis of Messages for Smart Autonomous Collision Avoidance System Using Controller Area Network
Many accidents and serious problems occur on the road due to the rapid increase in traffic congestion in all sections of the country. Autonomous vehicles provide a solution to successfully and cost-effectively avoid this problem while minimizing user disruption. Currently, more engaging electromechanical elements with an analog interface are used to develop affordable automobiles for efficient and cost-effective operation for a smart driving platform with a semiautonomous automobile, strengthening the vehicle involvement of the driver while increasing safety. As a result, it takes longer for various car elements to respond, which causes more problems during message transmission. This project aims to create a Controller Area Network (CAN) for analyzing message response times by incorporating a few application nodes on the IoT platform, such as an antilock braking system, flexible cruise control, and seat belt section, for some real-time control system applications. These application nodes are car analytical parts that are linked to IoT modules to prevent collisions. An autonomous device for collision avoidance and obstacle detection in a vehicle can impact road accidents if the CAN protocol is implemented. 2022 Anil Kumar Biswal et al. -
Adaptive Fault-Tolerant System and Optimal Power Allocation for Smart Vehicles in Smart Cities Using Controller Area Network
Nowadays, the power consumption and dependable repeated data collection are causing the main issue for fault or collision in controller area network (CAN), which has a great impact for designing autonomous vehicle in smart cities. Whenever a smart vehicle is designed with several sensor nodes, Internet of Things (IoT) modules are linked through CAN for reliable transmission of a message for avoiding collision, but it is failed in communication due to delay and collision in communication of message frame from a source node to the destination. Generally, the emerging role of IoT and vehicles has undoubtedly brought a new path for tomorrow's cities. The method proposed in this paper is used to gain fault-tolerant capability through Probabilistic Automatic Repeat Request (PARQ) and also Probabilistic Automatic Repeat Request (PARQ) with Fault Impact (PARQ-FI), in addition to providing optimal power allocation in CAN sensor nodes for enhancing the performance of the process and also significantly acting a role for making future smart cities. Several message frames are needed to be retransmitted on PARQ and fault impact (PARQ-FI) calculates the message with a response probability of each node. 2021 Anil Kumar Biswal et al. -
IoT-based smart alert system for drowsy driver detection
In current years, drowsy driver detection is the most necessary procedure to prevent any road accidents, probably worldwide. The aim of this study was to construct a smart alert technique for building intelligent vehicles that can automatically avoid drowsy driver impairment. But drowsiness is a natural phenomenon in the human body that happens due to different factors. Hence, it is required to design a robust alert system to avoid the cause of the mishap. In this proposed paper, we address a drowsy driver alert system that has been developed using such a technique in which the Video Stream Processing (VSP) is analyzed by eye blink concept through an Eye Aspect Ratio (EAR) and Euclidean distance of the eye. Face landmark algorithm is also used as a proper way to eye detection. When the drivers fatigue is detected, the IoT module issues a warning message along with impact of collision and location information, thereby alerting with the help of a voice speaking through the Raspberry Pi monitoring system. Copyright 2021 Anil Kumar Biswal et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. -
Gendered Informality: An Assessment of Operational Attributes and Entrepreneurial Performance of Female-Owned Enterprises in Jharkhand
The present study utilises the National Sample Survey Organization (NSSO)s 73rd round unincorporated non-agricultural enterprise data to analyse diverse operational and economic attributes of female-owned enterprises and their influence on enterprise performance with regard to enterprises gross value added (GVA) in the state of Jharkhand. The study additionally endeavours to ascertain the correlation amidst the operational attributes and the type of enterprise owned (established or own account) in the state. From a methodological standpoint, the current inquiry incorporates exploratory and regression analysis to give a comprehensive understanding of female entrepreneurship in Jharkhand and its gender differentials. The study findings indicate that specific attributes such as enterprise registration, account maintenance, enterprise locating outside the household premises, expanding and perennial status have a positive association with the GVA of the female-owned enterprise. It further highlights that female entrepreneurs, especially from marginalised backgrounds, view entrepreneurship as a necessity rather than a choice. There exists a notable gender disparity, with majority of enterprises owned by females predominantly operating within residential premises. Moreover, female involvement in a well-established enterprise is substantially lower compared to male workers, thus indicating an inverse correlation between the nature of the enterprise and its employment framework. 2024 Institute of Rural Management, Anand, Gujarat, India. -
Colonoscopy contrast-enhanced by intuitionistic fuzzy soft sets for polyp cancer localization
Medical images often suffer from low contrast, irregular gray-level spacing and contain a lot of uncertainties due to constraints of imaging devices and environment (various lighting conditions) when capturing images. In order to achieve any clinical-diagnosis method for medical imaging with better comprehensibility, image contrast enhancement algorithms would be appropriate to improve the visual quality of medical images. In this paper, an automated image enhancement method is presented for colonoscopy images based on the intuitionistic fuzzy soft set. The fuzzy soft set is used to model the intuitionistic fuzzy soft image matrix based on a set of soft features of the colonoscopy images. The technique decomposes the fuzzy image into multiple blocks and estimates a soft-score based on an adaptive soft parametric hesitancy map by using the hesitant entropy for each block to quantify the uncertainties. In the processing stage, an adaptive intensity modification process is done for each block according to its soft-score. These scores are accurately addressed the gray-level ambiguities in colonoscopy images that lead to better results. Finally, the enhanced image achieved by performing a defuzzification together with all unprocessed blocks. Qualitative and quantitative assessments demonstrate that the proposed method improves image contrast and region-of-interest of polyps in colonogram. Experimental results on enhancing a large CVC-Clinic-DB and ASU-Mayo clinic colonoscopy benchmark datasets show that the proposed method outperforms the state-of-the-art medical image enhancement methods. 2020 Elsevier B.V. -
Reducing approximation error with rapid convergence rate for non-negative matrix factorization (NMF)
Non-Negative Matrix Factorization (NMF) is utilized in many important applications. This paper presents development of an efficient low rank approximate NMF algorithm for feature extraction related to text mining and spectral data analysis. NMF can be used for clustering. NMF factorizes a positive matrix A to two positive matrices W and H matrices where A = WH. The proposal uses k-means clustering algorithm to determine the centroid of each cluster and assigns the centroid coordinates of each cluster as one column for W matrix. The initial choice of W matrix is positive. The H matrix is determined with gradient descent algorithm based on thin QR optimization. The performance comparison of the proposed NMF algorithm is illustrated with results. The accurate choice of initial positive W matrix reduces approximation error and the use of thin QR algorithm in combination with gradient descent approach provides rapid convergence rate for NMF. The proposed algorithm is implemented with the randomly generated matrix in MATLAB environment. The number of significant singular values of the generated matrix is selected as the number of clusters. The error and convergence rate comparison of the proposed algorithm with the current algorithms are demonstrated in this research. The accurate measurement of execution time for individual program is not possible in MATLAB. The average time execution over 200 iterations is therefore calculated with an increasing iteration count of the proposed algorithm and the comparative results are presented. 2021 by authors, all rights reserved. -
Machine Learning Insights into Mobile Phone Usage and Its Effects on Student Health and Academic Achievement
The research intends to find how students' health and academic performance are affected by their smartphone use. Considering how widely smartphones are used among students, it is important to know how they could affect health and learning results. This study aims to create prediction models that can spot trends and links between smartphone usage, health ratings, and academic achievement, thereby offering insightful information for teachers and legislators to encourage better and more efficient use among their charges. Data on students' mobile phone use, health evaluations, and academic achievement were gathered for the study. Preprocessing of the dataset helped to translate categorical variables into numerical forms and manage missing values. Trained and assessed were many machine learning models: Random Forest, SVM, Decision Tree, Gradient Boosting, Logistic Regression, AdaBoost, and K-Nearest Neighbors (KNN). The models' performance was evaluated in line with their accuracy in influencing performance effects and health ratings. Predictive accuracy was improved by use of feature engineering and model optimization methods. With 63.33% of accuracy for estimating health ratings, the SVM model was most successful in capturing the link between smartphone usage and health results. With an accuracy of 50%, logistic regression performed very well in forecasting performance effect, therefore stressing important linear connections between consumption habits and academic success. Random Forest and Decision Tree models were less successful for performance impact even if they showed strong performance in health forecasts. These results highlight the need of customized treatments to reduce the detrimental consequences of too high mobile phone use on students' academic performance and health. 2024 IEEE. -
Radar Cross Section (RCS) of HIS-based Microstrip Patch Array: Parametric Analysis
Low profile structures such as High Impedance Surfaces (HIS) are capable of modifying the scattering properties of a radiating structure. This paper presents the novel design of patch antenna/array with non-uniform HIS based ground plane. Two FSS elements of different dimensions are designed with different resonant frequencies. The performance of the high impedance surfaces has been carried out by varying the HIS dimensions and height of the substrate. Using the analyses, patch antenna/array with ground plane based on non-uniform configurations of HIS elements are designed. The radiation and scattering characteristics of microstrip patch antenna/array with HIS- based ground plane are compared to those with conventional PEC-based ground plane. A maximum of 8 dB RCS reduction has been achieved for patch array with non-uniform HIS layer. 2018 IEEE.