Papers by Sanjeev Kumar Mandal
International Journal of Network Security & Its Applications, Nov 30, 2017
In a distributed system, authentication protocols are the basis of security to ensure that these ... more In a distributed system, authentication protocols are the basis of security to ensure that these protocols function properly. Passwords are one of the most common authentication protocol used nowadays. Because of low entropy of passwords make the systems vulnerable to password guessing attacks. This paper presents a simple scheme that strengthens password-based authentication protocols and helps prevent dictionary attacks, replay attacks and man in the middle attacks etc. The proposed scheme presents a new password authentication protocol by using the user and server system identification/serial number. Here there is no possibility to store the user passwords so an attacker who gets the password cannot use it directly to gain immediate access and compromise security.
International Journal of Research in Engineering and Technology, 2013
Data security and Access control is a challenging research work in Cloud Computing. Cloud service... more Data security and Access control is a challenging research work in Cloud Computing. Cloud service users upload there private and confidential data over the cloud. As the data is transferred among the server and client, the data is to be protected from unauthorized entries into the server, by authenticating the user's and provide high secure priority to the data. So the Experts always recommend using different passwords for different logins. Any normal person cannot possibly follow that advice and memorize all their usernames and passwords. That is where password managers come in. The purpose of this paper is to secure data from unauthorized person using Security blanket algorithm.
A Secure Encryption Mechanism to Manage Your Password with Asymmetric Key
Design Engineering, May 21, 2021
Mathematical Problems in Engineering, Sep 29, 2022
Heart disease has reached to the number one position in last decade in terms of mortality rate, a... more Heart disease has reached to the number one position in last decade in terms of mortality rate, and more wretchedly, heart attack has a ected life in 80% of the cases. Cardiac arrest is an incurable incongruity that requires special treatment and cure. It has been a key research area for many years, and the number of researchers across the globe is devoted toward nding the optimal solution to avoid the ill-e ect of this disease. Along with predicting heart disease, if focus moves towards prevention of heart attack as well, then this could result in major life saver area for masses. is research work is fully devoted toward nding out the probability of heart attack so that people can take preventive measure before it hit the wall. is research proposed the neural fuzzy inference system (NFIS) to represent the training data formed from the n-dimensions of functions. e NFIS consists of error computing module to improve the learning instructions when the errors have been measured, initially the membership functions are de ned, and the parameters of membership functions are activated and learnt through when needed for an operation. e proposed methodology has experimented with sample test cases on Cleveland heart disease dataset from University of California Irvine (UCI) repository with the integration of supporting dependable and nondependable parameters, causing-factors, and datamatrices. is research has integration more than 13000 fuzzi cation rules to generate best decision-making, normalization process, planting techniques to create the feasibility to compute the heart attack probability and achieved 94 percentage of accuracy. is research can be extendable to build auto-altering and advise system with integration hardware peripheral circuit devices.
International Journal of Advanced Computer Science and Applications, 2023
The detection of diabetic retinopathy eye disease is a time-consuming and labor-intensive process... more The detection of diabetic retinopathy eye disease is a time-consuming and labor-intensive process, that necessitates an ophthalmologist to investigate, assess digital color fundus photographic images of the retina, and discover DR by the existence of lesions linked with the vascular anomalies triggered by the disease. The integration of a single type of sequential image has fewer variations among them, which does not provide more feasibility and sufficient mapping scenarios. This research proposes an automated decision-making ResNet feed-forward neural network methodology approach. The mapping techniques integrated to analyze and map missing connections of retinal arterioles, microaneurysms, venules and dot points of the fovea, cottonwool spots, the macula, the outer line of optic disc computations, and hard exudates and hemorrhages among color and back white images. Missing computations are included in the sequence of vectors, which helps identify DR stages. A total of 5672 sequential and 7231 non-sequential color fundus and blackand-white retinal images were included in the test cases. The 80 and 20 percentage rations of best and poor-quality images were integrated in testing and training and implicated the 10-ford cross-validation technique. The accuracy, sensitivity, and specificity for testing and analysing good-quality images were 98.9%, 98.7%, and 98.3%, and poor-quality images were 94.9%, 93.6%, and 93.2%, respectively.
International Journal of Advanced Computer Science and Applications
The cardiovascular disease (CD) is a widespread, dangerous sickness involving an excessive rate o... more The cardiovascular disease (CD) is a widespread, dangerous sickness involving an excessive rate of demise that necessitates quick piousness for care and cure. There are numerous diagnostic methods, such as angiography, available to diagnose heart disease (HD). ML is an extremely leading option for scientists for discovering prediction-based explanations for heart disease, and several machine learning algorithms are discovered to find the leading key results in community assistance. Researchers are presented with numerous conventional approaches, and various supportive algorithmic sequences formulated through the artificial neural network (NN) family, such as adaptive, convolutional, and de-convolutional NN, and various extended versions of hybrid combinations, originate with suitable outcomes. This research integrated the design and computational analysis of a unified model through a genetic algorithm-based Neural Fuzzy Hybrid S ystem, which is formulated for CD prediction. It included a dual hybrid model to forecast CD and measure the degree of a healthy heart, as well as more precise heart attack complications. S tage 1 of the study's implications integrates the two stages and plans HD prediction using patient data. The input was processed in stages. First, the data was delivered in pre-processing mode. Next, the mRMR algorithm was used to select features. Finally, the model was trained using a variety of ML algorithms, including S VM, KNN, NB, DT, RF, LR, and NN. The results were compared, and based on those findings, the model was tuned to produce the best results. In stage 2, HA possibilities and occurrences are determined by FuzIS intelligence using data from the first stage, which includes more than 13000 pre-generated rules of fuzzy implications. These rules cover both normal-level and dangerouslevel cases, and the medical parameters are integrated and tuned to produce membership functions that are then sent to the model. It is composed with the comparison of a unified system, which consists of Genetic algorithms, Neural networks, and Fuzzy Inference systems. In the experiment, gaussian MF sketched the continuous series of data, enabling the inference system to generate a good accuracy of 94% in calculating the problem probability.
International Journal of Advanced Computer Science and Applications
This study focuses on predicting and estimating possible stock assets in a favorable real-time sc... more This study focuses on predicting and estimating possible stock assets in a favorable real-time scenario for financial markets without the involvement of outside brokers about broadcast-based trading using various performance factors and data metrics. Sample data from the Y-finance sector was assembled using API-based data series and was quite accurate and precise. Prestigious machine learning algorithmic performances for both classification and regression complexities intensify this assumption. The fallibility of stock movement leads to the production of noise and vulnerability that relate to decision-making. In earlier research investigations, fewer performance metrics were used. In this study, Dickey-Fuller testing scenarios were combined with time series volatility forecasting and the Long Short-Term Memory algorithm, which was used in a futuristic recurrent neural network setting to predict future closing prices for large businesses on the stock market. In order to analyze the root mean squared error, mean squared error, mean absolute percentage error, mean deviation, and mean absolute error, this study combined LSTM methods with ARIMA. With fewer hardware resources, the experimental scenarios were framed, and test case simulations carried out. Keywords-Dickey-Fuller test case (DF-TC); recurrent neural network (RNN); root mean square error (RMSE); long short-term memory (LSTM); machine learning (ML); auto-regressive integrated moving average (ARIMA) I. Regressor based Hybrid simulation. Chun-Hao Chen et.al. Gautam Srivastava et.al. Wen M et.al. Md. Mobin Akhtar et.al. Pei-Yuan Zhou et.al.
International Journal of Advanced Computer Science and Applications
The detection of diabetic retinopathy eye disease is a time-consuming and labor-intensive process... more The detection of diabetic retinopathy eye disease is a time-consuming and labor-intensive process, that necessitates an ophthalmologist to investigate, assess digital color fundus photographic images of the retina, and discover DR by the existence of lesions linked with the vascular anomalies triggered by the disease. The integration of a single type of sequential image has fewer variations among them, which does not provide more feasibility and sufficient mapping scenarios. This research proposes an automated decision-making ResNet feed-forward neural network methodology approach. The mapping techniques integrated to analyze and map missing connections of retinal arterioles, microaneurysms, venules and dot points of the fovea, cottonwool spots, the macula, the outer line of optic disc computations, and hard exudates and hemorrhages among color and back white images. Missing computations are included in the sequence of vectors, which helps identify DR stages. A total of 5672 sequential and 7231 non-sequential color fundus and blackand-white retinal images were included in the test cases. The 80 and 20 percentage rations of best and poor-quality images were integrated in testing and training and implicated the 10-ford cross-validation technique. The accuracy, sensitivity, and specificity for testing and analysing good-quality images were 98.9%, 98.7%, and 98.3%, and poor-quality images were 94.9%, 93.6%, and 93.2%, respectively.
Wireless Communications and Mobile Computing
In today’s world, people study and evaluate trading stocks to make informed decisions, based on a... more In today’s world, people study and evaluate trading stocks to make informed decisions, based on available financial data and market information. Previous researchers relied on trend identification before making any decision to buy or sell stocks but fail to make accurate decisions due to complex systems. Some studies showed analysis to apply to stop loss on every stock transaction that got wrong levels due to limited features scaling that relied on single indicators without checking the performance metrics such as mean, standard deviation, and value at risk. Some existing models are based on theoretical implementation and they possess inaccurate success in real-time stock market transactions. Earlier risk management techniques were based on fundamental statistics of the company performance based on specific quarters that propose the future expects in the positive direction that is not every true which results in huge financial loss. Previous researchers failed to consider dynamic ri...
A Structured Protective Cohesive Health Care Information System Using Security And Storage Mechanism In Cloud
International Journal of Engineering Trends and Technology
A Secure Encryption Mechanism to Manage Your Password with Asymmetric Key
Design Engineering, May 21, 2021
A Secure Integrated Architecture of Digital Library Using Authentication and Auditing Methods in Cloud
Cloud shows a primary protagonist in emerging information technology era, which provides several ... more Cloud shows a primary protagonist in emerging information technology era, which provides several security and auditing methods to various resources and services in cloud that leads to save money adding accessibility to end users. This paper deals the cloud security concern includes data leakage, data availability, user authentication, data integrity during sharing of information in cloud. Cloud computing appeals various threats, web based attacks and vulnerabilities, so there is a need of authentic authorized people should be able to access the confidential data for enhancing security level and data correctness in cloud. Conversely, sharing of cloud information is vulnerable to cloud attacks which carry irreparable severe losses to users. This paper makes innovative integrated digital library methods provides the combination of user authentication mechanism, k-means cluster based audit mechanism and multilevel data availability on different storages with protected information flow c...
A General Approach of Database Scheme and Its Comparative Study
The usage of database originates back to the early 60s. Since then its growth is determined in di... more The usage of database originates back to the early 60s. Since then its growth is determined in different aspects. Different demands of every era give database a new bunch of challenges. To overcome these challenges, researchers come up with different ideas and methods. These various combinations enhance features of database and this way database starts evolving from one period to another. Due to this reason the database that we had in 1960 is completely different from what we have now. This review paper briefly explains the types of database and the database services provided by Firebase.
The field of information security is a vast area which is continually evolving and expanding rela... more The field of information security is a vast area which is continually evolving and expanding relative to network data and global communication security. This literature review contrasts the research that has been published in the area of cryptography and authentication protocols, by providing a comparative and analytical study to secure the web servers and services.
: Today’s world is depend on internet and its application where transmitting data through network... more : Today’s world is depend on internet and its application where transmitting data through network communication via mail, social group, online banking etc., Hence there comes the requirement of securing the information is a must and so cryptography techniques are employed such as symmetric key and asymmetric key techniques. In this paper, few symmetric and asymmetric key encryption techniques are reviewed, compared and tested with cryptography tools to check its security strength.
A Proposed Robust Computational Network Modelling to Optimally Investigate Gene Data
2021 2nd Global Conference for Advancement in Technology (GCAT), 2021
Extracting informative contents of clinical importance from gene expression is challenging in bio... more Extracting informative contents of clinical importance from gene expression is challenging in bioinformatics. However, reviewing existing literature reviews found that almost all the frequently adopted techniques for analyzing gene expression data are associated with problems. Therefore, the proposed system offers a cost-effective framework that contributes to a simplified text mining approach with a novel design of gene-network analysis followed by optimization to incorporate novelty in this field.
Mathematical Problems in Engineering
Heart disease has reached to the number one position in last decade in terms of mortality rate, a... more Heart disease has reached to the number one position in last decade in terms of mortality rate, and more wretchedly, heart attack has affected life in 80% of the cases. Cardiac arrest is an incurable incongruity that requires special treatment and cure. It has been a key research area for many years, and the number of researchers across the globe is devoted toward finding the optimal solution to avoid the ill-effect of this disease. Along with predicting heart disease, if focus moves towards prevention of heart attack as well, then this could result in major life saver area for masses. This research work is fully devoted toward finding out the probability of heart attack so that people can take preventive measure before it hit the wall. This research proposed the neural fuzzy inference system (NFIS) to represent the training data formed from the n-dimensions of functions. The NFIS consists of error computing module to improve the learning instructions when the errors have been measu...
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Papers by Sanjeev Kumar Mandal