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Secure biometric authentication with de-duplication on distributed cloud storage
Cloud computing is one of the evolving fields of technology, which allows storage, access of data, programs, and their execution over the internet with offering a variety of information related services. With cloud information services, it is essential for information to be saved securely and to be distributed safely across numerous users. Cloud information storage has suffered from issues related to information integrity, data security, and information access by unauthenticated users. The distribution and storage of data among several users are highly scalable and cost-efficient but results in data redundancy and security issues. In this article, a biometric authentication scheme is proposed for the requested users to give access permission in a cloud-distributed environment and, at the same time, alleviate data redundancy. To achieve this, a cryptographic technique is used by service providers to generate the bio-key for authentication, which will be accessible only to authenticated users. A Gabor filter with distributed security and encryption using XOR operations is used to generate the proposed bio-key (biometric generated key) and avoid data deduplication in the cloud, ensuring avoidance of data redundancy and security. The proposed method is compared with existing algorithms, such as convergent encryption (CE), leakage resilient (LR), randomized convergent encryption (RCE), secure de-duplication scheme (SDS), to evaluate the de-duplication performance. Our comparative analysis shows that our proposed scheme results in smaller computation and communication costs than existing schemes. 2021 M et al. All Rights Reserved. -
Intelligent machine learning approach for cidscloud intrusion detection system
In this new era of information technology world, security in cloud computing has gained more importance because of the flexible nature of the cloud. In order to maintain security in cloud computing, the importance of developing an eminent intrusion detection system also increased. Researchers have already proposed intrusion detection schemes, but most of the traditional IDS are ineffective in detecting attacks. This can be attained by developing a new ML based algorithm for intrusion detection system for cloud. In the proposed methodology, a CIDS is incorporated that uses only selected features for the identification of the attack. The complex dataset will always make the observations difficult. Feature reduction plays a vital role in CIDS through time consumption. The current literature proposes a novel faster intelligent agent for data selection and feature reduction. The data selection agent selects only the data that promotes the attack. The selected data is passed through a feature reduction technique which reduces the features by deploying SVM and LR algorithms. The reduced features which in turn are subjected to the CIDS system. Thus, the overall time will be reduced to train the model. The performance of the system was evaluated with respect to accuracy and detection rate. Then, some existing IDS is analyzed based on these performance metrics, which in turn helps to predict the expected output. For analysis, UNSW-NB15 dataset is used which contains normal and abnormal data. The present work mainly ensures confidentiality and prevents unauthorized access. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021. -
Image and signal processing in the underwater environment
To handle submerged action recognition, researchers must first understand the fundamental principles of photonic crystals mostly in the liquid phase. Deterioration effects are produced by the mediums physical attributes, which are not present in typical pictures captured in the air because light is increasingly reduced as it passes through water, submarine pictures are characterized by low readability. As a consequence, the sceneries are poorly contrasting and murky. Its vision capability is limited to approximately twenty meters in clear blue water and five meters or less in muddy water due to light dispersion. Absorbing (the removal of incident light) and dispersion are the two factors that produce light degradation. So the actual quality of submersible digital imaging is influenced by the destructive interference processes of light in water. Longitudinal scattered (haphazardly diverted light traveling from objects to the cameras) causes picture details to be blurred. 2021, SciTechnol, All Rights Reserved. -
Marital Stress and Domestic Violence during the COVID- 19 Pandemic
Marital stress and domestic violence is prevalent in every society around the world. It has become a major concern during the Covid-19 pandemic. Governments have resorted to lockdown measures in order to contain the pandemic. The pandemic has made the weaker and more vulnerable people in a household more exposed to abusive partners. Social isolation and home confinement have detrimental effects on ones mental and physical well-being. Women have been shown to be at a very high risk from violence during The Covid19 pandemic. The research paper aims to understand the factors which compel women to stay in abusive and stressful marriages and the ways in which they can be empowered to lead their life with dignity and self-respect. The cultural contexts of most societies force women to stay in abusive marriages as the woman is often portrayed as the symbol of unity in families. Understanding the cultural bindings of women trapped in abusive households during the COVID-19 pandemic is a very crucial aspect as this can help in understanding the fear and apprehensions of women trapped in destructive marriages. This can be a key factor which can make it easier for support groups while providing counselling and other kinds of support to women trapped in abusive marriages. The paper also discusses the impact of abusive relationships on children and how it negatively shapes their personality and their emotional well- being. 2021 The Author(s). This open access article is distributed under a Creative Commons Attribution (CC-BY) 4.0 license. -
Parity labeling in Signed Graphs
Let S = (G; ?) be a signed graph where G = (V;E) is a graph called the underlying graph of S and ?: E(G) ? {+; -}. Let f: V(G) ? {1, 2, ..., |V(G)|} such that ?(uv) = + if f(u) and f(v) are of same parity and ?(uv) = - if f(u) and f(v) are of opposite parity. The bijection f induces a signed graph Gf denoted as S, which is a parity signed graph. In this paper, we initiate the study of parity labeling in signed graphs. We define and find `rna' number denoted as ?-(S) for some classes of signed graphs. We also characterize some signed graphs which are parity signed graphs. Some directions for further research are also suggested. 2021, Journal of Prime Research in Mathematics. All rights reserved. -
An improved web caching system with locally normalized user intervals
Caching is one of the most promising areas in the field of future internet architecture like Information-centric Networking, Software Defined Networking, and IoT. In Web caching, most of the web content is readily available across the network, even if the webserver is not reachable. Several existing traditional caching methods and cache replacement strategies are evaluated based on the metrics like hit ratio and byte hit Ratio. However, these metrics have not been improved over the period because of the traditional caching policies. So, in this paper, we have used an intelligent function like locally normalized intervals of page visit, website duration, users' interest between user groups is proposed. These intervals are combined with multiple distance metrics like Manhattan, squared Euclidean, and 3-,4-,5-norm Minkowski. In order to obtain significant common user navigation patterns, the clustering relation between the users using different intervals and distances is thoroughly analyzed. These patterns are successfully coupled with greedy web cache replacement strategies to improve the efficiency of the proposed web cache system. Particularly for improving the caching metrics more, we used an AI-based intelligent approach like Random Forest classifier to boost the prefetch buffer performance and achieves the maximum hit rate of 0.89, 0.90, and byte hit rate of 0.87, 0.89 for Greedy Dual Size Frequency and Weighted Greedy Dual Size Frequency algorithms, respectively. Our experiments show good hit/byte hit rates than the frequently used algorithms like least recently used and least frequently used. 2013 IEEE. -
Secure key exchange scheme: A DNA computing-based approach to resist MITM in DHKE
Diffie-Hellman key exchange (DHKE) protocol was a pioneering work and considered as a new direction in the field of cryptography though it is not an encryption protocol. DHKE is a method to exchange the keys securely, based on the discrete logarithm problem. It has applications in internet security protocols including SSL, IP Sec and SSH. The major issue with DHKE is its vulnerability to man in the middle attack (MITM). Various techniques have been proposed to resist the MITM including digital signatures. This paper proposes DNA computing-based encryption techniques to resist MITM in DHKE. DNA cryptography builds on the concepts of biomolecular computations which are considered as one of the emerging directions in the cryptography. The proposed methodology also includes an encryption technique based on DNA-based codebook, secret sharing and DNA cryptography to exchange parameters securely. The security analysis of the proposed scheme is evaluated by theoretical analysis. Formal analysis of the proposed protocol is done using Scyther and all the modelled claims are validated and positive results are obtained. Copyright 2021 Inderscience Enterprises Ltd. -
Cost-enabled QoS aware task scheduling in the cloud management system
Maintaining the quality of service (QoS) related parameters is an important issue in cloud management systems. The lack of such QoS parameters discourages cloud users from using the services of cloud service providers. The proposed task scheduling algorithms consider QoS parameters such as the latency, make-span, and load balancing to satisfy the user requirements. These parameters cannot sufficiently guarantee the desired user experience or that a task will be completed within a predetermined time. Therefore, this study considered the cost-enabled QoS-aware task (job) scheduling algorithm to enhance user satisfaction and maximize the profit of commercial cloud providers. The proposed scheduling algorithm estimates the cost-enabled QoS metrics of the virtual resources available from the unified resource layer in real-time. Moreover, the virtual machine (VM) manager frequently updates the current state-of-the art information about resources in the proposed scheduler to make appropriate decisions. Hence, the proposed approach guarantees profit for cloud providers in addition to providing QoS parameters such as make-span, cloud utilization, and cloud utility, as demonstrated through a comparison with existing time-and cost-based task scheduling algorithms. 2021 - IOS Press. All rights reserved. -
A study on the weak form efficiency of metals & mining sector in bse
This study has been conducted to observe whether the weak form of efficiency holds true when the Metals & Mining sector is examined for the same. Data is collected for a 5 year period which ranges from 1st April 2014 to 31st March 2019. A total of 1232 observations have been taken from the three selected companies of the Metals & Mining sector of the BSE, namely, Coal India Ltd, Hindustan Zinc Ltd and JSW Steel Ltd. Jarque-Bera test is used to check whether the data is normally distributed or not. Augmented Dickey Fuller test has been used to establish whether the data series possesses stationarity or not. Finally Runs test and Autocorrelation tests are used to check whether the Metals & Mining sector of BSE is weak form efficient or not through the three representative companies. Upon analyzing the data through Runs Test, except for JSW Steel Ltd, the other two companies are identified to contain randomness in their data series. Autocorrelation test also suggests that the future stock prices can be predicted only to a minimal extent for the three representative companies. Based on the derived results, it is concluded that the Metals & Mining sector of BSE does not contain any statistical dependencies between its past and future stock prices and it is found to be weak form efficient. 2021, Badebio Biotechnololgy Ltd. All rights reserved. -
Well-being and Career Decision-making Difficulties Among Masters Students: A Simultaneous Multi-Equation Modeling
There is a stellar upsurge in the number of persons pursuing a masters level of education as well as the institutions offering it in the current generation. Nevertheless, an explicit theoretical and empirical implication of how the tutelages, at this level, shape the well-being of learnerssuch that it could help individuals overcome career decision-making difficulties remains to be elucidated. The present study addressed two major objectives. Firstly, we investigated the well-being of masters degree students along with career decision-making difficulties in India. Secondly, apart from exploring the possible influence of nationality of the respondents on career decision difficulty, the study expanded the literature on career decision-making difficulties to under-researched populations in developing countries. Through a cross-sectional research design, we recruited a sample of 136 masters degree respondents. The result reveals that while the composite well-being resources significantly influenced Career Decision Difficulties, the nationality of respondents appeared not as a germane factor in this context. Following the evaluation of the direct effect of individual well-being resources; Self-acceptance and Personal growth proved to have a statistically significant effect on career decision-making difficulties. Also, among the constituents of career decision-making difficulties studied, lack of readiness appears to be the major concern among the respondents. The findings expand the literature on cognitive, vocational, and organization science vis-a-vis career decision-making difficulties and provide useful insights for educational institutions and practitioners. 2021 The Author(s). This open access article is distributed under a Creative Commons Attribution (CC-BY) 4.0 license. -
A collaborative defense protocol against collaborative attacks in wireless mesh networks
Wireless mesh network is an evolving next generation multi-hop broadband wireless technology. Collaborative attacks are more severe at the transport layer of such networks where the transmission control protocol's three-way handshake process is affected with the intention to bring the network down by denying its services. In this paper, we propose a novel collaborative defense protocol (CDP) which uses a handshake-based verification process and a collaborative flood detection and reaction process to effectively carry out the defense. This protocol presents a group of monitors that collaboratively entail in defending the attack; thus reduces the burden on a single monitor. Moreover, this paper proposes a novel transport layer post-connection flooding attack that occurs after establishing a TCP connection and we show that CDP can detect and mitigate this attack. The CDP protocol has been implemented in Java and its performance has been evaluated using essential metrics. We show that CDP is efficient and reliable and it can identify the attack before any major damage has occurred. Copyright 2021 Inderscience Enterprises Ltd. -
An IoT-based tracking application to monitor goods carrying vehicle for public distribution system in India
Designing a secured transportation system to handover food items to various fair price shops is one of the objectives of smart city development in India. In this paper, an IoT-based tracking solution for moving goods carrying vehicle is proposed. A hardware prototype model is developed using different sensors with GPS/GPRS tracking module and is attached to the vehicle. An alarm is raised to make decision in case of trouble or malfunction. The data generated by the model during the movement of vehicle is encrypted using RSA algorithm and sent to cloud for monitoring by an application developed using PHP and analysis using MapReduce programming model. Experiments are conducted to study the feasibility of the developed model during deployment. From the experiment it is observed that, the developed hardware model and the application meet the objective of monitoring vehicle, safer recovery in case of malfunction and secured delivery of items. Copyright 2021 Inderscience Enterprises Ltd. -
A Novel Approach for Linguistic Steganography Evaluation Based on Artificial Neural Networks
Increasing prevalence and simplicity of using Artificial Intelligence (AI) techniques, Steganography is shifting from conventional model building to AI model building. AI enables computers to learn from their mistakes, adapt to emerging inputs, and carry out human-like activities. Traditional Linguistic Steganographic approaches lack automation, analysis of Cover text and hidden text volume and accuracy. A formal methodology is used in only a few Steganographic approaches. In the vast majority of situations, traditional approaches fail to survive third-party vulnerability. This study looks at evaluation of an AI-based statistical language model for text Steganography. Since the advent of Natural Language Processing (NLP) into the research field, linguistic Steganography has superseded other types of Steganography. This paper proposes the positive aspects of NLP-based Markov chain model for an auto-generative cover text. The embedding rate, volume, and other attributes of Recurrent Neural Networks (RNN) Steganographic schemes are contrasted in this article between RNN-Stega and RNN-generated Lyrics, two RNN methods. Here the RNN model follows Long Short Term Memory (LSTM) neural network. The paper also includes a case study on Artificial Intelligence and Information Security, which discusses history, applications, AI challenges, and how AI can help with security threats and vulnerabilities. The final portion is dedicated to the study's shortcomings, which may be the subject of future research. 2013 IEEE. -
An empirical analysis of ICT tools with gamification for the Indian school education system
Information and communication technologies (ICTs) are used as a part of different fields, for example, training, business, and healthcare. The main objective of this paper is to introduce ICT as a better method to teach and test student's performance so it can become a part of the school curriculum and enhance learner's experience. To accomplish this objective, multiple kinds of literature were studied to get insights into the factors associated with ICT and gamification. Based on the findings, a survey was conducted on teachers to know the favourability of ICT in modern schools. Based on the response, two application prototypes are developed for students to get their performance and results that support the study. Most importantly, similar concepts were taught to students using both, traditional and ICT based approaches. A test was conducted via both methods. It was discovered that the performance of the students increased by 13% when the modern approach was followed to conduct the test. Copyright 2021 Inderscience Enterprises Ltd. -
Nexus Between Interest Rate Risk and Economic Value of Equity of Banks
This analytical study looks to provide recommendations to the banking sector on different policies and regulations by examining certain aspects of the Basel III accord, which was designed to manage specific operational, capital and market risks of banks. A review of extant literature reveals that only a few papers have been written on simulation-based approaches, using basis and re-pricing risks. We look to connect this as a source while attempting to define and measure the impact of interest rate risk (IRR) on the economic value of equity (EVE) of banks. We propose to use the driverdriven method, wherein interest rate shocks are derived through prime lending rate (PLR) for the period of 20162019 in the context of India. Monte Carlo Simulation and OLS regression was performed to predict the IRR; Granger causality was used to examine the cause and effect relationship; the impulse response function (IRF) was used for sensitivity analysis; and the vector error correction model (VECM) technique was used for co-integrating relationships. Notably, the EVE movement caused due to shocks in interest rates had to be traced as it envisages probable EVE losses. Importantly, our study is among the first few to show the relationship between IRR and EVE of banks, especially after the deregulation of Indian banking sector. 2021 International Management Institute, New Delhi. -
Has Indias Employment Guarantee Program Achieved Intended Targets?
This paper explores the performance of the worlds largest employment guarantee program, the Mahatma Gandhi National Rural Employment Guarantee Schemes in India, both nationally and through a sub-national-level comparison based on key performance indicators viz. (i) financial indicators, (ii) physical performance indicators, and (iii) inclusiveness indicators. The paper is based on administrative data taken from the Ministry of Rural Development from 2006 to 2019. Despite sharp increases in fund allocation, total expenditures, and utilization rates, there was deceleration in majority of physical performance indicators after 2016, including total person-days employment and person-days of employment per household, with wide variation in sub-national level implementation capabilities. The finding also rejects the falsity of saturation of MGNREGA work in the rural areas, which is reflected in a strong positive correlation between fund allocation and employment generation. Its broader objective of social safety net for vulnerable people in rural areas shows an achievement, although with some gaps in implementation. JEL classification: H53, J43, P25 The Author(s) 2021. -
Optimization of Biodiesel Production from Waste Cooking Oil by Box Behnken Design Using Response Surface Methodology
Interest in Biodiesel production has grown over the years due to concerns related to the environment, and the solutions include deriving energy from waste as the replacement for diesel, a petroleum-derived fuel. Biodiesel has been accepted as a "green fuel" as it is a renewable, non-toxic, safe and biodegradable energy material. The utilisation of waste cooking oil (WCO) by converting it into biodiesel is one of the promising alternatives to diesel. An attempt to optimise the biodiesel production from WCO (a waste material) has been made via this study. The process adopted was Trans-esterification of pretreated WCO, and the optimization of biodiesel production was carried out by Box-Behnken method using a response surface methodology. The variations between the analytical and experimental results were within acceptable limits. The response surface methodology resulted in an optimum yield of 96.88% (analytical), which was validated through an experiment within an acceptable error of 0.58%. 2021,International Journal Of Renewable Energy Research.All rights reserved. -
Integrated Home-Based Palliative Care in Motor Neuron Disease: A Case Report from Low- Middle Income Country
In many international care guidelines, multidisciplinary palliative care forms a key to optimum management in Motor Neuron Disease (MND). We describe the home-based palliative care interventions for a client with MND and his family from a Low and Middle-income country context. This report also discusses the advantages and challenges of the same with suggestions for sustaining the quality of care for neuro palliative conditions. 2021 Taylor & Francis Group, LLC. -
A Novel Threshold based Method for Vessel Intensity Detection and Extraction from Retinal Images
Retinal vessel segmentation is an active research area in medical image processing. Several research outcomes on retinal vessel segmentation have emerged in recent years. Each method has its own pros and cons, either in the vessel detection stage or in its extraction. Based on a detailed empirical investigation, a novel retinal vessel extraction architecture is proposed, which makes use of a couple of existing algorithms. In the proposed algorithm, vessel detection is carried out using a cumulative distribution function-based thresholding scheme. The resultant vessel intensities are extracted based on the hysteresis thresholding scheme. Experiments are carried out with retinal images from DRIVE and STARE databases. The results in terms of Sensitivity, Specificity, and Accuracy are compared with five standard methods. The proposed method outperforms all methods in terms of Sensitivity and Accuracy for the DRIVE data set, whereas for STARE, the performance is comparable with the best method. 2021. All Rights Reserved. -
Mindfulness: An emotional aid to the glass ceiling experiences
We have progressed to a phase where there is very little difference between men and women, but the reality in many countries is that women are looked down as the inferior gender and not given career opportunities to explore. They are not let into the decision-making roles at the organization even when they have an equal qualification, experience and skill. They are placed low in the hierarchy which allows them to witness the functions at the higher level of the organization but restricts them from participating in them. There are a lot of factors like cultural, socio-demographic factors and society itself that influence this disparity in the organization. These contributory factors create the glass ceiling phenomenon at the workplace, thereby generating emotional and psychological imbalances in women employees. This is a conceptual paper aiming to explore the concept and impact of mindfulness, and various concepts of mindfulness could be used as an emotional aid to treat the psychological effects of the glass ceiling. It further explains some of the mindful concepts like mindful walking, mindful life and mindfulness-based stress reduction technique in treating some of the psychological and emotional issues like depression, anxiety, frustration, traumatic experiences, adjustment issues, addiction, stress, low self-esteem, low self-confidence and aggression. It also elucidates adopting mindfulness techniques in real organizational scenarios where women are constantly discriminated because of their gender and opportunities are taken away. 2021 The Author(s). This open access article is distributed under a Creative Commons Attribution (CC-BY) 4.0 license.