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DNA based cryptography to improve usability of authenticated access of electronic health records
The quality of health care has been drastically improved with the evolution of Internet. Electronic health records play a major role in interoperability and accessibility of patients data which helps in effective and timely treatment irrespective of the demographic area. The proposed model is to ensure and monitor maternal health during pregnancy and to create awareness alerts (options include messages, voice alerts or flash the system) based on the individual health record. The system aims to prevent maternal death due to medical negligence and helps to make recommendations to prevent future mortality based on medical history and take appropriate action. Authentication is a critical aspect considering the trade-off between usability and security whereas data breach and related cybercrime are major concerns in health care. The proposed model uses DNA based authentication techniques to ensure usability and confidentiality of electronic data, Aadhaar to prevent unauthorized access to patients data in case of emergency without affecting availability. 2018, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering. -
A secure image-based authentication scheme employing DNA crypto and steganography
Authentication is considered as one of the critical aspects of Information security to ensure identity. Authentication is generally carried out using conventional authentication methods such as text based passwords, but considering the increased usage of electronic services a user has to remember many id-password pairs which often leads to memorability issues. This inspire users to reuse passwords across e-services, but this practice is vulnerable to security attacks. To improve security strength, various authentication techniques have been proposed including two factor schemes based on smart card, tokens etc. and advanced biometric techniques. Graphical Image based authentication systems has received relevant diligence as it provides better usability by way of memorable image passwords. But the tradeoff between usability and security is a major concern while strengthening authentication. This paper proposes a novel twoway secure authentication scheme using DNA cryptography and steganography considering both security and usability. The protocol uses text and image password of which text password is converted into cipher text using DNA cryptography and embedded into image password by applying steganography. Hash value of the generated stego image is calculated using SHA-256 and the same will be used for verification to authenticate legitimate user. 2015 ACM. -
An online signature method using DNA based bio-hash for positive identification and non-repudiation
This work focuses on using biological data as a unique feature to generate e-Signature. DNA, the blue print of life is of unique nature. The signature created using biological data will be difficult to repudiate in the scenario of a legal dispute. Applications of human DNA are not limited to molecular biology, with the advents of fast growing technologies it is possible to inject DNA into e-Signature for positive identification. The proposed methodology uses Signature DNA as a unique biological feature for the registrant. This work has various phases, the first phase includes creating the Signature DNA using hybridized unique DNA segments of the individual (Registrant) which is the unique identification of the user and difficult to duplicate and repudiate. It generates a Bio-Hash of the Signature DNA. The DNA-Hash generated serves for positive identification of the user which computed with the hash of the e-Document and a random value serve as a Bio-Sign (e-Signature) for the e-Document in the second phase. Bio-Sign converted into QR code with a link to the e-Sign service providers website will ensure usability for verification. In the verification phase the verifier scans the QR code which connects to the e-Service provider's web link. The service provider computes and verifies the document and ensures the e-Signature is valid or not to the verifier. If the signer repudiates the signature, positive identification using DNA helps to achieve Non-Repudiation, the last phase. In the scenario of a legal dispute, the registrant cannot repudiate as the authorities can provide positive identification using the DNA Signature for greater assurance. The proposed technique ensures authentication, integrity and Non-Repudiation with Zero knowledge scenario to the verifier. 2017 IEEE. -
Anticounterfeiting Method for Drugs Using Synthetic DNA Cryptography
Counterfeited products are a significant problem in both developed and developing countries and has become more critical as an aftermath of COVID-19, exclusively for drugs and medical equipment's. In this paper, an innovative approach is proposed to resist counterfeiting which is based on the principles of Synthetic DNA. The proposed encryption approach has employed the distinctive features of synthetic DNA in amalgamation with DNA encryption to provide information security and functions as an anticounterfeiting method that ensures usability. The scheme's security analysis and proof of concept are detailed. Scyther is used to carry out the formal analysis of the scheme, and all of the modeled assertions are verified without any attacks. 2022 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. -
Comparing Developmental Approaches for Game-Based Learning in Cyber-Security Campaigns
Digital game-based learning (DGBL) has been viewed as an effective teaching strategy that encourages students to pick up and learn a subject. This paper explores its viability to help increase the reach and efficiency of the existing cybersecurity awareness spreading campaigns that find adolescent students as their demographic. This work intends to reinforce the benefits of multimedia learning in schools and universities with the use of video games and further find the ideal type and genre of game that can be developed to spread awareness about cybersecurity to students in grades 8th to 12th (tailored towards the Indian context). Game genres were compared on the basis of having a simple gameplay loop, being easy for instructors to train themselves in, being inclusive to special needs children, being able to be published as an independent title, and having very low hardware specification requirements. Ideally, the paper proposes that this game would be a single-player experience that would follow a game-based learning approach to maximize the game's reach. Once identified, the model of the game was assessed using already existing implementations. Finally, the ideal model, a single-player visual novel is proposed. A future iteration of the paper will implement the proposed model of game design and perform an analysis of the effects the video game had on the learning experience of the students surveyed. 2023 IEEE. -
Toxic heavy metal ion detection by fluorescent nanocarbon sensor derived from a medicinal plant
In the twenty-first century, the importance of environmental pollution sensing cannot be overstated. Cadmium is a well-known poisonous heavy metal that seriously endangers human health. In terms of screening for poisons and diagnosing illnesses, the sensitive and focused detection of cadmium in cells is crucial. In this work, we developed Green fluorescent Carbon nanomaterial (Carbon nanomaterial) synthesized from a novel precursor, Justicia Wynaadensis, by the most eco-friendly, cost-effective hydrothermal method, which acts as a fluorescent probe for Cadmium fluorescence sensing technique with the concentration range of 1 nM1 M. The sensor displays remarkable linear detection with a 5.235 nM detection limit. 2022 The Author(s) -
Morphological Characterization of Selected Aliphatic and Aromatic Hydrocarbons.
In the last few years considerable interest has been aroused in the study of amorphous carbon. Amorphous carbon has a wide range of properties that are primarily controlled by the different bond hybridizations possible in such materials. This gives different properties like high strength, flexibility etc. Due to these properties, they are used in thin film technology and in nanoscale electronic devices. Films can range from those with high transparency and are hard and diamond-like, through to those which are opaque, soft and graphitic-like. Application areas include field emission cathodes, electronic devices, medical and optical coatings. Hence study of different carbon structures has been of great interest for many researchers. Several techniques have been used to study various sources of carbon. Hydrocarbons are the most abundant sources of carbon. The majority of hydrocarbons found, naturally occur in crude oil and the decomposition of these give hydrogen and carbon. Incomplete combustion of hydrocarbons leads to the production of polycyclic aromatic hydrocarbons. Hydrocarbon combustion therefore mainly have aromatic and aliphatic chains of carbon. Hydrocarbons are by far the most widespread precursors among carbon sources employed in the production of carbon nanotubes and carbon nanosphers. In the present study diesel soot, camphor soot and coal has been used as precursors for nanomaterials. Impurities in the samples can reduce efficiency of production. Mineral matter encompasses dissolved salts in the pore water and inorganic elements associated with the organic compounds, as well as crystalline and non-crystalline mineral particles. Quantitative analysis of minerals and other inorganics contributes to defining coal quality. Therefore a study on effects of bio and base leaching on coal samples are also done. XRD is one of the majorly used techniques to deduct the various structural parameters like interlayer spacing of crystalline (d002) structure, crystallites size (La, Lc), aromaticity (fa), number of layers of carbon atoms per aromatic lamellae(n). According to Scherrer, crystallite size varies inversely with peak width. Therefore it is a known fact that a broad hump in the spectrum indicates the presence of nano layers. These parameters are determined from the intensity profiles of the sample hydrocarbons. Also the structure of the hydrocarbon can be characterized using NMR and SEM EDS. 1H NMR spectra can yield structural information that allows classification of complex mixtures containing hundreds of aromatic, naphthenic, paraffinic, olefinic, and isoparaffinic compounds. SEM/EDS techniques allow both inorganic analysis of bulk materials and determination of chemistry and abundance of microscopic constituents. SEM analysis also gives us the size of nano particles formed in the sample. EDS allows one to identify what those particular elements are and their relative proportions. CHNS analysis gives the elemental composition of the samples. The study shows that the carbonaceous soot produced from combustion of diesel in engine show the presence of significant amount of carbon nanomaterials. The SEM micrographs indicate that nanoparticle present in diesel soot is clusters of carbon nanospheres. EDS analysis reveals the soot particles to be composed of primarily carbon and oxygen along with hydrogen. NMR spectrum of the soot reveals significant aliphatic component with predominance of methyl and methylene groups on ?and ?? positions to aromatic rings. Camphor soot XRD analysis shows presence of ordered layers of nanolayers and laso the presence of CNTs. The SEM micrographs of camphor show the presence of carbon nanostructures. The EDS analysis shows more of carbon and oxygen along with aluminium, silicon and potassium. Study of coal samples treated with biological leaching agents reveals that Penicillium spp (PE) treated sample is having more of a graphitic or ordered structure and the d002 spacing of this sample is 3.37 ?? which is close to graphite. XRD data of coal sample treated with base leaching agents confirms the turbostratic structure of coal. The SEM micrographs of the samples show that KN has more graphite like sheet structures. -
A Study of Successful Strategies of Unorganized Pharmacy Retailers - A Case of South Bangalore
PES Business Review, Vol-8 (2), pp. 15-24. ISSN-0973-919X -
Impact of User-Generated Content on Purchase Intension for Fashion Products : A Study on Women Customers in Bangalore
Indian Journal of Marketing, Vol. 46, Issue 7, pp. 23-35, ISSN No. 0973-8704 -
X -ray diffraction and microhardness studies of tin monoselenide
Tin Monoselenide (SnSe) crystals have been grown by the Physical Vapour Deposition (PVD) method. X-ray diffraction studies were carried out on the as grown crystals and the lattice parameters were found to be a=11.506 b=4.149and c=4.447 The values were found to be comparable with that reported in the PDF card for SnSe. The microhardness of the crystals has been determined by using Vickers microhardness indenter. 2011 American Institute of Physics. -
A structural approach towards reinvigorating student satisfaction in industrial training institutes a contemplating outlook
The research paper focused to conceptualize and empirically test the conceptual model of student satisfaction proposed for Indian vocational education and training (VET), precisely industrial training institutes (ITIs). Even though the upgradation of ITIs through public-private partnership (PPP) is emphasized from the previous decade, little empirical evidence exists about the quality of the institutes. Improved quality in ITIs helps in increased employability of the students and would help in meeting Indias projected skill demand of 191 million youths by 2022. Empirical data were collected from upgraded ITIs of Andhra Pradesh and Telangana states to assess student satisfaction. Student satisfaction gives the measure of student feedback on the quality of the courses. PLS-SEM was applied to develop measurement and structural models. Subsequently, statistical values were used to estimate the validity and reliability of the models. Besides, the predictive accuracy of the model was also tested. The data analysis assisted to ascertain whether to accept or reject the hypothesized relations proposed based on the conceptual model. The results proved that institute quality factors were positively correlated with student satisfaction. Eventually, it was observed that industry exposure was a significant determinant of student satisfaction followed by training facilities & equipment, trainer credibility, learning environment, and placement and counseling services. Above all being said, it can be posited that focusing on the above all quality factors would help in enhancing the quality of ITIs. 2021, Associated Management Consultants Pvt. Ltd.. All rights reserved. -
A novel African buffalo based greedy routing technique for infrastructure and cluster based communication in vehicular ad-hoc network
In this modern era, the wire free replica is utilized Vehicular Ad hoc Networks (VANETs) to converse each other. Also, the VANET paradigm not required any specific fixed infrastructure. Furthermore, the vehicle in VANET framework is movable like as mobile nodes. Also, the wireless connectivity between the vehicular nodes is not stable in all cases, it often changes their structure. Research have recommended various responses to control these issues and furthermore to lessen blockage in VANET environment. Therefore, the infrastructure of a network changes frequently which results in communication overheads, energy consumption and lifetime of the nodes. Consequently, in this paper a novel African Buffalo based Greedy Routing (ABGR) technique is to improve the performance of infrastructure and cluster based communication of the node. Moreover, the routing overhead and infrastructure communication can be enhanced by this proposed protocol. Consequently, the energy consumption solution is enhanced based on the CH. Sequentially, the proposed routing protocol is compared with existing protocols in terms of end-to-end delay, throughput, Data transmission Ratio (DTR), and energy consumption and so on. Therefore, it shows that the energy utilization and lifetime of the nodes in the proposed network has been enhanced. 2021 Little Lion Scientific. -
Notions of beauty, perception and acceptance - How people perceive product advertising /
Beauty has always been an important factor in humanity. It has played a very important role in history, being recorded timeless in various arts. Needless to say it is a very important part of our world, our society and us. Though beauty can be achieved through many means, one of the most popular ways one thinks of achieving it is beauty products. These beauty products have wriggled their ways though our daily lives and have made themselves a staple through their insistent advertising which proclaim that they are the answer to all your beauty related problems. One of their proclamations is that their products help achieve perfection. -
Advancements in thiol-yne click chemistry: Recent trends and applications in polymer synthesis and functionalization
The 2022 Nobel Prize in chemistry brought the world's attention to click chemistry, a field as fascinating as its name, characterized by attractive features like high yield, stereospecificity, and broad scope. Since its inception, click chemistry has been synonymous with copper-catalyzed azide-alkyne reactions, owing to their remarkable advantages. However, as the field advanced, there has been a proactive search to develop metal-free alternatives for more biocompatible applications. This led to the extensive adoption of thiol-ene click reactions in the past decade. Yet, due to the growing requirement for polymers with complex architecture and functionality, in recent years, thiol-yne click reactions have come to the forefront with additional advantages over its ene counterparts, allowing the addition of two thiols to an alkyne. This review provides a concise overview of some of the significant developments in polymer synthesis and functionalization utilizing thiol-yne click chemistry. The focus is primarily on radical-mediated thiol-yne reactions, considering the substantial body of work in this area. Moreover, the review provides adequate discussion on other mechanistic pathways like nucleophilic and metal-catalyzed thiol-yne reactions that have gained traction recently. 2024 Elsevier Ltd -
Recent advances in electrochemical and optical sensing of the organophosphate chlorpyrifos: a review
Chlorpyrifos (CP) is one of the most popular organophosphorus pesticides that is commonly used in agricultural and nonagricultural environments to combat pests. However, several concerns regarding contamination due to the unmitigated use of chlorpyrifos have come up over recent years. This has popularized research on various techniques for chlorpyrifos detection. Since conventional methods do not enable smooth detection, the recent trends of chlorpyrifos detection have shifted toward electrochemical and optical sensing techniques that offer higher sensitivity and selectivity. The objective of this review is to provide a brief overview of some of the important and innovative contributions in the field of electrochemical and optical sensing of chlorpyrifos with a primary focus on the comparative advantages and shortcomings of these techniques. This review paper will help to offer better perspectives for research in organophosphorus pesticide detection in the future. 2022 Informa UK Limited, trading as Taylor & Francis Group. -
Assessing the Skill Sets from the NEP Policy 2020: Scale Development and Validation
Purpose: The central aspect of this paper is the National Education Policy (NEP) 2020, an education-based policy in the Indian context. The article captured the opportunities from the perspective of the skill set it offers to its important stakeholders, students; the current research has aimed to propose and validate an instrument to measure the skill set identified from the NEP document and academic expertise, which could be used to measure students skill-based performance. Design/Methodology/Approach: The first section used EFA to establish four skill sets: Employability Skills, Communal-Based Skills, Social and Emotional Skills, and Individualistic Skills. The CFA model was further deployed to confirm the factors; the study was administered to a sample of 820 students from various commerce and management colleges from South and North Bangalore. Findings: The research results could be applied to evaluate the effectiveness of skill sets on students performance to create holistic education. Originality: The first step is to develop and validate scales for measuring skill sets under NEP 2020. Second, in accordance with the pupils order of priority, to close the gap between the talents stated and those observed. Research Limitations/Implications: The study was conducted only with students of commerce and management disciplines in Bangalore. Practical Implications: NEP has placed a greater emphasis on competency development and skill enhancement, which aids in the development of higher-order cognitive, social-emotional, and 21st-century abilities necessary for employment in the future. NEP gave greater autonomy to students to choose their learning pathway and develop skill sets, which are likely to make them job creators, thereby giving rise to the entrepreneurial culture. Social Implications: To cultivate an aspirational student body, it is critical to instill the necessary skill sets in pupils. Policymakers and decision-makers could then organize their courses using these skill sets. 2024, Associated Management Consultants Pvt. Ltd.. All rights reserved. -
Innovative Method for Detecting Liver Cancer using Auto Encoder and Single Feed Forward Neural Network
Liver cancer ranks sixth among all cancers in frequency of incidence. A CT scan is the gold standard for diagnosis. These days, CT scan images of the liver and its tumor can be segmented using deep learning and Neural Network techniques. In this proposed approach to identifying cancer cells, it's focus on four important areas: To enhance a photo by taking out imperfections and unwanted details. An ostu method is used for this purpose. Specifically, this proposed approach to use the watershed segmentation technique for image segmentation, followed by feature extraction, in an effort to isolate the offending cancer cell. After finishing the model training with AE-ELM. To do this, Extreme Learning Machine incorporates an auto encoder. To achieve effective and supervised recognition, the network's strengths of Extreme Learning Machine (ELM) are thoroughly leveraged, including its few training parameters, quick learning speed, and robust generalization ability. The auto encoder-extreme learning machine (AE-ELM) network has been shown to have a respectable recognition impact when the sigmoid activation function is used and the number of hidden layer neurons is set to 1200. According to the results of this investigation, a method based on AE-ELM can be utilized to detect the liver tumor. As compared to the CNN and ELM models, this technique achieves superior accuracy (around 99.23%). 2023 IEEE. -
An Intelligent Hybrid GA-PI Feature Selection Technique for Network Intrusion Detection Systems
The development of Network Intrusion Detection Systems (NIDS) has become increasingly important due to the growing threat of cyber-attacks. However, with the vast amount of data generated in networks, handling big data in NIDS has become a major challenge. To address this challenge, this research paper proposes an intelligent hybrid GA-PI algorithm for feature selection and classification tasks in NIDS using support vector machines (SVM). The proposed approach is evaluated using two sub-datasets, Analysis and Normal, and Reconnaissance and Normal, which are generated from the publicly available UNSWNB-15 dataset. In this work, instead of considering all possible attacks, the focus is on two attacks, emphasizing the importance of the feature selection agent in determining the optimal features based on the attack type. The experimental results show that the proposed hybrid feature selection approach outperforms existing methodologies in terms of accuracy and execution time. Moreover, the selection of features can be subjective and dependent on the domain knowledge of the researcher. Additionally, the proposed approach requires computational resources for feature selection and classification tasks, which can be a limitation for resource-constrained systems. To be brief, this research paper presents a promising approach for feature selection and classification tasks in NIDS using an intelligent hybrid GA-PI algorithm. While there are some challenges and limitations, the proposed approach has the potential to contribute to the development of effective and efficient NIDS. 2023, Ismail Saritas. 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.