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Secure authentication framework for cloud
The growing popularity of cloud based services is prompting organizations to consider shifting applications and data onto cloud. However, organizations dealing with highly sensitive information are apprehensive of moving its applications & data to public cloud owing to concern about security of its information. It is hence incumbent on service providers that only legitimate Users will access its services and resources in cloud. Verifying authenticity of remote users is a necessary pre-requisite in a cloud environment before allowing access to secure resources/services/ applications. The simplest & most commonly used user authentication mechanism is password based authentication. However, Users tend to choose easy to remember password, and many a times use same password for multiple accounts, which makes it often the weakest link in security. Furthermore, service providers authenticating Users on the basis of password, stores password verification information in their databases and such authentication schemes with verification table are known to be vulnerable to various attacks. From the perspective of authentication requirements, service providers in a cloud environment can be broadly categorized into two. Those service providers dealing with highly sensitive information and working in a regulated environment can be grouped into category one ?? as in those offering services for sectors like health care, finance. These providers require a strong and secure authentication mechanism to authenticate its users, without any additional functionality. Similarly, there is a second category of service providers dealing with secure information but operate in a collaborative environment ?? as providers providing their applications bundled through a web portal. To provide the Users with a seamless authentication experience, while accessing multiple services during a session, the second category of service providers prefer to have Single Signon functionality. Two-factor authentication technology overcomes the limitations of password authentication and decreases the probability that the claimant is presenting false evidence of its identity to verifier. If different service providers set up their own two-factor authentication services, Users have to do registration and login process repeatedly. Also, Users accessing multiple cloud services may be required to hold multiple authentication tokens associated with various service providers. Authentication factors such as crypto-tokens and smart cards with cryptographic capabilities have been vastly used as a second authentication factor. However, Users are required to always carry these authentication tokens which make it cumbersome from practical usability perspective. Also its usage involves cost thus restricting its adoption to corporate environments. The authentication process can be made more user-convenient if the authentication factor chosen is such that it is commonly used by all types of Users. Leveraging the use of mobile phone as an authentication factor can help address issue of user convenience at no extra cost while improving the security of authentication schemes. Though, there has been an increasing focus on strengthening the authentication methods of cloud service users, there is no significant work that discusses an authentication scheme that can be adopted by the two categories of cloud Service Providers. Taking cognizance of aforesaid issues related to secured authentication in cloud environment, this research focused on designing secure Two-Factor authentication schemes that can be adopted by the two categories of service providers. This research carried out in different levels, proposes authentication architecture and protocols for the two categories of service providers. At the first level, research proposes Direct Authentication architecture for cloud Service Providers who prefer to authenticate its users by using a strong authentication mechanism and does not require Single Sign-On (SSO) functionality. For those Providers who prefer to provide its user with a SSO functionality the research proposes Brokered Authentication architecture. The next level of research focuses on proposing User Authentication Protocols for both Direct Authentication Service Providers (DASPs) and Brokered Authentication Service Providers (BASPs). The research proposes use of strong, Two-Factor Authentication Protocols without Verifier Table. The suggested protocols, provides Users with flexibility of using a Password and either a Crypto-token or a Mobile-token to authenticate with Service Providers. The proposed approach eliminates the requirement of the User to remember multiple identities to access multiple services and provides the benefit of a higher level of security on account of second authentication factor and non-maintenance of verifier table at server. Access to different services offered by multiple service providers using a single authentication token requires interoperability between providers. Also, the Service Providers will have to address the task of issuing the second authentication factor to Users. As a result, the research intends to propose the utilization of proposed two-factor authentication scheme within a specific environment which includes a trusted entity called an Identity Provider (IdP), with whom Users and Service Providers will be registered. The IdP is responsible for issuing and managing the second authentication factor. In brokered authentication, the IdP playing the role of an authentication broker also provides Single Sign-on functionality. The Security Assertion Markup Language (SAML) is used by BASPs and the IdP to exchange authentication information about Users. A major objective of this research is to propose an authentication model that can be adopted by both categories of service providers. Hence, this research proposes an authentication framework for cloud which supports an integrated authentication architecture that provides the service providers with the flexibility to choose between direct and brokered authentication. The integrated two-factor authentication protocol, which does not require the server to maintain a verifier table, supported by the frame work allows users to do a single registration and access services of both direct & brokered authentication service providers using the same crypto-token/mobile-token. To verify claims about security strengths of the proposed authentication protocols, security analysis is done using theoretical intuition. The proposed protocols are found to offer desirable security features such as resistance to replay attack, stolen verifier attack, guessing attack, user impersonation attack etc. To verify the efficiency of the proposed protocols, the communication and computation costs are compared with similar schemes and it is seen that the costs are comparable. To validate the resistance of protocols to authentication attacks, they are analyzed using automated verification tool called ????Scyther??? and the protocol strength is verified by ???no attacks??? results. -
Malayalam biopics: From books to films /
This article talks about the difficulties that emerge when considering biographical films that are focused around biographical or autobiographical works of writing utilizing careful investigations of three Malayalam films. The films are an adjustment from their individual books. -
Secure authentication frame work for cloud
The growing popularity of cloud based services is prompting organizations to consider shifting applications and data onto cloud. However, organizations dealing with highly sensitive information are apprehensive of moving its applications and data to public cloud owing to concern about security of its information. It is hence incumbent on service providers that only legitimate Users will access its services and resources in cloud. newlineVerifying authenticity of remote users is a necessary pre-requisite in a cloud environment before allowing access to secure resources/services/ applications. The simplest and most commonly used user authentication mechanism is password based authentication. However, Users tend to choose easy to remember password, and many a times use same password for multiple accounts, which makes it often the weakest link in security. Furthermore, service providers authenticating Users on the basis of password, stores password verification information in their databases and such authentication schemes with verification table are known to be vulnerable to various attacks. newlineFrom the perspective of authentication requirements, service providers in a cloud environment can be broadly categorized into two. Those service providers dealing with highly sensitive information and working in a regulated environment can be grouped into category one as in those offering services for sectors like health care, finance. These providers require a strong and secure authentication mechanism to authenticate its users, without any additional functionality. Similarly, there is a second category of service providers dealing with secure information but operate in a collaborative environment as providers providing their applications bundled through a web portal. To provide the Users with a seamless authentication experience, while accessing multiple services during a session, the second category of service providers prefer to have Single Sign-on functionality. -
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. -
Valorisation of coffee husk as replacement of sand in alkali-activated bricks
The coffee industry is known to generate voluminous amount of waste during its production process. Different types of waste such as coffee hush ash and spent coffee ground, to name a few, have been extensively researched as a substitute in the construction industry. However, the utilization of coffee husk as a substitute for construction materials has seen limited exploration. In particular, there are no studies which investigate the utilization of waste coffee husk (WCH) in alkali-activated bricks. Therefore, in this research WCH was employed as a substitute to sand in alkali-activated bricks. Alkali-activated bricks were synthesized with ground granulated blast furnace slag (GGBFS), fly ash (FA), sand, and sodium silicate solution (SS). Sand was replaced with WCH at replacement rates of 0 %, 5 %, 10 %, 15 %, 20 %, and 30 % by volume. The developed bricks were evaluated for strength, density, water absorption, porosity, and efflorescence. Additionally, structural and morphological characteristics of bricks were assessed by Fourier-transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), Thermogravimetric analysis (TGA), and Scanning electron microscopy (SEM) analysis. The results indicate that bricks with WCH improve the compressive strength with a maximum value of 15.7 MPa, and reduce the density with a minimum value of 1509 kg/m3 for composites with 30 % WCH, respectively. The water absorption and porosity of bricks increased with incorporation of WCH due to porous structure of WCH. The physico-chemical analysis of the bricks shows effective geopolymerization in the composite system with WCH, and further the bricks with 30 % WCH depict thermal stability with insignificant weight loss at 575 ?. Finally, the composites with 30 % WCH classify as good quality bricks as per IS 1077: 1992 specifications, and this will improve practical feasibility of such materials in the construction industry. 2024 The Authors -
Appraisal of the potential of endophytic bacterium Bacillus amyloliquefaciens from Alternanthera philoxeroides: A triple approach to heavy metal bioremediation, diesel biodegradation, and biosurfactant production
Endophytic microbes have been associated with many positive traits due to their endurance mechanisms. The current study was designed at exploring the potential of the endophytic bacterium Bacillus amyloliquefaciens MEBAphL4 isolated from Alternanthera philoxeroides for biosurfactant production and bioremediation efficiency. This endophyte, isolated from the polluted Madiwala lake in Bangalore, displayed elevated resistance to Cr and Pb till 2000 mg/L. The metal removal efficiency was found to be higher for Cr (25.7 %) at pH 6 and for Pb (92.3 %) at pH 9. Further, the present study also describes biosurfactant production with good emulsification ability (E24-52 %) and stability over a range of pH (8?12), temperature (2040C) and salinity (515 %). Biosurfactant production was enhanced 1.18-fold using the Response Surface Methodology approach and characterised by Fourier Transformation Infra-red Spectroscopy and Ultra-Performance Liquid Chromatography- Mass Spectrometry showing the presence of lipopeptides, fengycin, iturin and surfactin of molecular weights 1463.65, 1043.44 and 1012.56 Da respectively. The potential application of the biosurfactant in degrading various hydrocarbons was evaluated, demonstrating its effectiveness in bioremediation of oil-contaminated sites. Specifically, diesel biodegradation was measured at 56.460.95 %. These findings underscore the potential of B. amyloliquefaciens in environmental applications such as heavy metal biosorption and the bioremediation of contaminated sites, particularly those affected by oil spills and correlates to UN SDG6 of clean water and sanitation. 2024 Elsevier Ltd -
Endophytic bacteria Klebsiella spp. and Bacillus spp. from Alternanthera philoxeroides in Madiwala Lake exhibit additive plant growth-promoting and biocontrol activities
Background: The worldwide increase in human population and environmental damage has put immense pressure on the overall global crop production making it inadequate to feed the entire population. Therefore, the need for sustainable and environment-friendly practices to enhance agricultural productivity is a pressing priority. Endophytic bacteria with plant growth-promoting ability and biocontrol activity can strongly enhance plant growth under changing environmental biotic and abiotic conditions. Herein, we isolated halotolerant endophytic bacteria from an aquatic plant, Alternanthera philoxeroides, from the polluted waters of Madiwala Lake in Bangalore and studied their plant growth promotion (PGP) and biocontrol ability for use as bioinoculant. Results: The isolated bacterial endophytes were screened for salt tolerance ranging from 5 to 15% NaCl concentration. Klebsiella pneumoniae showed halotolerant up to 10% NaCl and Bacillus amyloliquefaciens and Bacillus subtilis showed up to 15%. All three strains demonstrated good PGP abilities such as aminocyclopropane-1-carboxylic acid (ACC) deaminase activity, phosphate solubilization, ammonia production, and nitrogen fixation. In addition, K. pneumoniae also exhibited high indoleacetic acid (IAA) production (195.66 2.51g/ml) and potassium solubilization (2.13 0.07ppm). B. amyloliquefaciens and B. subtilis showed good extracellular enzyme production against cellulase, lipase, protease, and amylase. Both the isolates showed a broad spectrum of antimicrobial activity against the tested organisms. The optimization of IAA production by K. pneumoniae was done by the response surface methodology (RSM) tool. Characterization of IAA produced by the isolate was done by gas chromatography-mass spectrometry (GCMS) analysis. The enhanced plant growth-promoting ability of K. pneumoniae was also demonstrated using various growth parameters in a pot trial experiment using the seeds of Vigna unguiculata. Conclusion: The isolated bacterial endophytes reported in this study can be utilized as PGP promotion and biocontrol agents in agricultural applications, to enhance crop yield under salinity stress. The isolate K. pneumoniae may be used as a biofertilizer in sustainable agriculture and more work can be done to optimize the best formulations for its application as a microbial inoculant for crops. 2023, The Author(s).