Cobalt

Interpretation on the Google Cloud Platform and Its Wide Cloud Services

Sajid R.U., Islam S., Rakib A.B., Kaur A.

International Journal of Security and Privacy in Pervasive Computing, 2022, цитирований: 2, doi.org, Abstract

Cloud computing is growing wide and first-rate promising technology. There are three forms of cloud computing: infrastructure as a service (IaaS), software as a service (SaaS), and platform as a service (PaaS). There are many cloud service providers. Among these, AWS (Amazon Web Service), Azure (Microsoft Cloud), IBM Cloud, Oracle Cloud, and VMware are immensely popular. In this paper, the authors study the Google Cloud Platform (GCP) and a few principally used popular services. Google Cloud Platform could be a cloud provider; they supply servers and services that are used on-demand and at scale. Google Cloud Platform is the fastest growing cloud service supplier now.

Impact of Cryptographic Key on Scalable Computing

Pradhan P.L.

International Journal of Security and Privacy in Pervasive Computing, 2022, цитирований: 0, doi.org, Abstract

The research has contributed to the development of the cryptographic control on the proposed RTS that aims to determine the high-performance computing at optimal cost and time to be invested into dynamic cryptographic control that decides on the major components of real-time operating system resources. Furthermore, the mechanism optimizes the cost, and resources are supposed to optimize the operating system risks. We have to optimize the technology and resource cost and maximizes the productivity and business (throughput) while improving the high performance of the operating system as per business requirement for the multiple locations. This proposed cryptographic control on the real-time system provides high computational services around the clock. The objective should be defined in such a way that the processor, memory, and encryption key are always utilized at minimal cost with high availability of data and services as per business and resource management.

A Optimized Taxonomy on Spot Sale Services Using Mathematical Methodology

Tiwari A., Garg R.

International Journal of Security and Privacy in Pervasive Computing, 2022, цитирований: 3, doi.org, Abstract

In reality, the most appropriate cloud standards are significant ideas for application administrations. OSCCS technique calculation gives a spot-like market in virtual space to the end clients. The OSCCS gives an on-spot showcasing framework in the virtual universe of processing. As fluffy hypothesis is giving the specific outcomes and close to correct outcomes that is the reason that authors have taken the idea of fluffy unpleasant set hypothesis in their OSCCS approach. This sort of approach depends on the determination of the best ideal cost and season of asset allotment to an end client by the suppliers in virtual advertising. The allotments of assets depend on powerful on-request demand upkeep so the end-client gets the cloud administration on a business premise like in continuous shopping advertising on events. By the OSCCS deals approach framework, an end client can get the assistance at the ideal expense. The OSCCS calculation is mimicked in cloud test systems.

Home Automation and Application With Bolt IoT

Kakne A.S., Chouragade P.M.

International Journal of Security and Privacy in Pervasive Computing, 2022, цитирований: 0, doi.org, Abstract

Even with advancement of communications technologies, home automation and application have received major attention. Today's digital world is mostly reliant on the internet so that there is a need to design such a solution to make more efficient from unauthorized components to safeguard the data that may work in wireless mode alone. This system provides guidance towards operational operations specifically surveillance on the areas and its structure and managing assets over the internet utilizing web applications employing IoT techniques. Home automation is a vital unit which must meet the main criteria like user interface and safety. In the current situation, the complete process depends on the Bolt IoT platform, a home automation system where it can access and manage house devices remotely from anywhere. The user may use this system to operate different equipment like LEDs, fans, or DC motors as well as to keep an eye on the environment's temperature. In addition, the Bolt IoT module enables cloud connectivity to the system, and sensor data is communicated to the cloud.

A Systematic Survey of Automatic Loan Approval System Based on Machine Learning

Sharma V., Sharma R.

International Journal of Security and Privacy in Pervasive Computing, 2022, цитирований: 1, doi.org, Abstract

The banking sector is an integral part of an economy as it helps in capital formation. One of the most critical issues of banks is the risk involved in loan applications. Employing machine learning to automate the loan approval process is a significant advancement. For this topic, all classification algorithms have been tested and assessed in previous researches; however, it is still unclear which methodology is best for a particular type of dataset. It is still difficult to identify which model is the most effective. Since each model is dependent on a certain dataset or classification approach, it is critical to create a versatile model appropriate for any dataset or attribute collection. The aim of the study is to provide detailed analysis of previous studies and to propose a predictive model for automatic loan prediction using four classification algorithms. Exploratory data analysis is performed to obtain correlation between various features and to get insights of banking datasets.

Analysis of a Multiple-Shift Computer-Based Examination Evaluation System

A. H.

International Journal of Security and Privacy in Pervasive Computing, 2022, цитирований: 0, doi.org, Abstract

Conducting the exam in different shifts means the variation in the difficulty level of the different shifts of the exam. Various recruitment bodies adopt normalization process to solve this issue. This paper contains a detailed study of the normalization process carried out by the recruitment bodies. The study also includes the effect of normalization in the candidate's score and it depends on the difficulty level of the shift in which the candidate appears in the exam. This work can be further enhanced by comparing the different methods adopted by similar recruitment/selection organization and adopting the best, more appropriate approach to improve the system. This analysis will help in improving the evaluation system and make the system more robust and accurate. So that a more accurate merit list can be prepared and all the stakeholders can be reassured. It is very important to make the system transparent, so that the stakeholders have a clear understanding of the system and at the same time they should be aware of the advantages and disadvantages of the system.

Recognition of Alphanumeric Patterns Using Backpropagation Algorithm for Design and Implementation With ANN

Aggarwal A., Gaba S., Chawla S., Arya A.

International Journal of Security and Privacy in Pervasive Computing, 2022, цитирований: 2, doi.org, Abstract

The artificial neural network has been called for its application as alphanumeric characters recognizing the network. The idea is to maintain the obsolete data available in hard copy form and to convert that data into digital form. Some specific bit patterns that correspond to the character are trained using the network. The numbers of input and output layer neurons are chosen. As there are many ways to do but in this the algorithm used for training the network is called the Backpropagation Algorithm using the delta rule. The testing and training patterns are provided for which weights are calculated in the program and patterns are recognized and analysis is done. The effect of variations in the hidden layers is also observed with pattern matrices.

An Optimistic Security Model for Improving Cyber Security Using Adaptive Algorithms to Prevent SQL Injection Attacks

Raju P.S., Rao P.V.

International Journal of Security and Privacy in Pervasive Computing, 2021, цитирований: 1, doi.org, Abstract

Throughout today's economic and social life, the use of web-based services (such as e-commerce, online banking, and web-based communications, to name a few) has become a common habit. Countless applications operate worldwide on millions of servers, and their numbers are steadily increasing. It has become a focus of attackers and hackers for the attacks because of the huge growth of internet usage. It is necessary for all companies to develop and protect their applications in order to maintain their credibility and keep their products relevant for users. Web applications have brought in new classes of computer security vulnerabilities, such as SQL injection (SQLIA), and it has exceeded previously prominent vulnerability classes in recent years. SQL injection is the instance of the broader class of vulnerabilities that are based on input validation. The primary purpose of this research is to study the vulnerabilities of SQL injection and to propose an optimistic security model for secure data transmission. In this work, the authors proposed an adaptive algorithm to prevent SQL injections.

Applications of Big Data in Disaster Management

Sushrut M.

International Journal of Security and Privacy in Pervasive Computing, 2021, цитирований: 0, doi.org, Abstract

Disasters can be both manmade or natural, but the consequences have been atrocious and require swift action to manage the devastating impact. The digital footprint is being left behind at a huge rate in the modern world. The overwhelming digital interactions across the technology-oriented world has necessitated the need of an efficient way to organise and utilise them for a better tomorrow. With ease of access to the internet and high percentage of e-literacy rates, involvement of the citizens of the world in the digital arena is increasing at an impeccable exponential rate. This data is generated at the rate of a quintillion bytes per day and has a total probability to increase furthermore. This paper was synthesized in an effort to consolidate the existing technology in handling the crisis with innovation. In this context, the paper has talked about the utility of big data and the related technological concepts, which help to monitor or detect the hazard, mitigate the efforts in tackling it, and systemize the post-disaster recovery process statistically.

Proposed Abelian ACM Method Optimizing

Asthana A., Pradhan P.L.

International Journal of Security and Privacy in Pervasive Computing, 2021, цитирований: 1, doi.org, Abstract

This proposed UFS ACM is the best preventive control around the world for heterogeneous applications on multiple hardware and software. The subject and object can be able to map, integrate, synchronize, and communicate through reading, writing, and executing over a UFS on the complex web infrastructure. We have to investigate the basic concepts behind access control design and enforcement and point out different security requirements that may need to be taken into consideration as per business, resources, and technology available to us. This paper has to formulate and implement several access control mechanisms, methods, and models on normalizing them step by step, which has been highlighted in the proposed model for present and future requirements. This research paper contributes to the development of an optimization model that aims to determine the optimal cost, time, and maximize the quality of services to be invested into security model and mechanisms deciding on the measure components of UFS.

Low Power Restoration Circuits Reduce Swing Voltages of SRAM Cell With Improved Read and Write Margins

Kumar V., Rawat R.M.

International Journal of Security and Privacy in Pervasive Computing, 2021, цитирований: 0, doi.org, Abstract

This paper examines the factors that affect the static noise margin (SNM) of static random access memories which focus on optimizing read and write operation of 8T SRAM cell which is better than 6T SRAM cell using swing restoration for dual node voltage. New 8T SRAM technique on the circuit or architecture level is required. In this paper, comparative analysis of 6T and 8T SRAM cells with improved read and write margin is done for 130nm technology with cadence virtuoso schematics tool.

Optimal Cloud Service Provider Selection Based on QoS Metrics

Arunambika T., Senthil Vadivu P.

International Journal of Security and Privacy in Pervasive Computing, 2021, цитирований: 0, doi.org, Abstract

There are thousands of providers obtainable in the market, and more and more are being added to the service list every day. All of these providers claim that the services given to them are distinctive and hassle-free. To check their claim, the cloud service broker (CSB) verifies the quality of service (QoS) of the cloud service providers (CSPs) and the level of user needs. Depending on the requirements of the cloud consumer (CC), CSB allocates a CSP to it. This paper proposed optimal cloud service provider selection (OCSPS) based on QoS metrics. The CC would handovers the demand to the CSB for optimal CSP selection using QoS. Once the CSP selection process is complete, the outcomes would become back to the CC. Entire demands created to CCs are saved in the request buffer (RB) in the CSB. When a specific request is fulfilled, the subsequent demand would take from this RB. The experimental result shows that the proposed OCSPS algorithm takes less time for CSP ranking and optimal CSP selection.

Performance Comparison of Image Processing Techniques on Various Filters

Singh S., Sharma A., Aggarwal A.

International Journal of Security and Privacy in Pervasive Computing, 2021, цитирований: 1, doi.org, Abstract

Image processing plays a crucial role in a large number of applications including fields of medical, watermarking in images, spatial data analysis applications. When images are static, generally, users can get good performance, though processing of real-time images are dependent on various parameters like efficacy of algorithm and filtering techniques. Researchers have observed high variation in performance during processing of real-life images; therefore, efficient filtering techniques play a vital role in determining the implemented processing algorithm's performance as well as the quality of captured images taken into consideration. Thus, the focus of this study is to discuss various widely used filtering techniques and efficient performance analysis in outdoor environmental scenarios. A real-time efficiency system is made to conclude each filter type's effectiveness in different environmental conditions with comparison and evaluation, highlighting merits and demerits of different algorithms based on application needs along with external factors.

COVID-19

Taneja P., Arora M., Mendiratta A., Aggarwal A., Kumar S.

International Journal of Security and Privacy in Pervasive Computing, 2021, цитирований: 0, doi.org, Abstract

The world is going through one of the worst pandemics ever seen. After concurrent lockdowns, as the government is easing out, more people are on the verge of risking their lives. This leads to a need for a system that not only provides a user with relevant updates regarding this disease but is essentially a useful tool that can be used to provide a safest path between a source and a destination. Most of the people now are equipped with smart devices. Since the spread is nowhere near its termination and the world is having a lot of breakdowns be it in the form of economic disruption or sociological imbalance due to this, though the government is already working hard on detecting and declaring hotspot zones, there is no real-time evaluation of potentially crowded zones that can be a source of disease synthesis too. There is a need for a system that can notify its users regarding any kind of potentially harmful zones, and since getting on the road is more than a necessity now, a safe route provisioning system is also a dire need of the situation in order to stop the spread.

A Study

Jain S., Aggarwal A., Mittal S.

International Journal of Security and Privacy in Pervasive Computing, 2020, цитирований: 1, doi.org, Abstract

Chikungunya, an infection which is difficult to treat, took a toll on Delhi in year 2016. In that scenario, detection and prevention of vector-borne diseases outbreak in Delhi have been a major cause of concern for government. For analyzing this epidemic outbreak, the authors have utilized the unstructured data generated through Twitter. Twitter is a social media platform that generates vast amount of epidemic-related information every day. This information is used to analyze the effect of epidemic outbreak in Delhi region. In this paper, the authors discussed an associated study of various machine learning techniques for analyzing and mining social media information. In this, the authors have also categorized and explore the steps involved in social media textual data to provide a pictorial view of the ongoing outbreak. Finally, the article discussed the challenges faced for mining social media data.

COVID-19

Kanungo S., Sharma D., Aggarwal A.

International Journal of Security and Privacy in Pervasive Computing, 2020, цитирований: 1, Обзор, doi.org, Abstract

The novel corona or COVID-19 disease spread from Wuhan city of China. The virus spread rapidly around the different countries, and now there are 6,040,609 confirmed cases across the globe. People inflected with virus are suffering from respiratory problems, blood clotting, etc. It is evident to be more dangerous for older persons and those who are already facing other serious illnesses. The virus spreads mainly through droplets of saliva or discharge from the nose of infected person when he coughs or sneezes. The purpose of this review is to focus on social and economic impact of COVID-19 in India and how the world will change because of this pandemic and what will be the ‘new normal' with and after this pandemic. This deadly virus has put the globe on alert because of its the high mortality rate and expansion of new number of cases rapidly. Until now, four lockdown phases had helped India to prevent the spike in the curve of new cases, but currently the authors are witnessing steeper rise in new corona cases every day.

Analysis of Big Data Using Two Mapper Files in Hadoop

Malhotra J., Sethi J.K., Mittal M.

International Journal of Security and Privacy in Pervasive Computing, 2020, цитирований: 0, doi.org, Abstract

Nowadays, a large amount of valuable uncertain data is easily available in many real-life applications. Many industries and government organizations can exploit this data to extract valuable information. This information can help the managers to enhance their strategies and optimize their plans in making decisions. In fact, various private companies and governments have launched programs with investments and funds in order to maximize profits and optimize resources. This vast amount of data is called big data. The analysis of big data is important for future growth. This paper depicts big data analytics through experimental results. In this paper, data for New York stock exchange has been analyzed using two mapper files in Hadoop. For each year, the calculation of maximum and minimum price of every stock exchange and the average stock price is done.

Evaluating the Impact of DDoS Attacks in Vehicular Ad-Hoc Networks

Adhikary K., Bhushan S., Kumar S., Dutta K.

International Journal of Security and Privacy in Pervasive Computing, 2020, цитирований: 4, doi.org, Abstract

The presence of either malicious vehicles or inaccessibility of network services makes vehicular ad-hoc networks (VANETs) easy targets for denial of service (DoS) attacks. The sole purpose of DoS attacks is to prevent the intended users from accessing the available resources and services. When the DoS attack is carried out by multiple vehicles distributed throughout the network, it is referred as distributed DoS (DDoS) attack. A lot of works have been done by researchers in securing the vehicular communication against the DDoS attacks. In this paper, efforts have been made to simulate the DDoS attacks in VANETs as well as to study their impact on the performance of networks. The experimental results are presented using six important metrics, which are collision, jitter, delay, packet drop, ratio-in-out, and throughput. The experimental results show that the impact of distributed DoS (DDoS) attack on networks performance is very critical and must be addressed to ensure the smooth functioning of networks.

Conversational System, Intelligent Virtual Assistant (IVA) Named DIVA Using Raspberry Pi

Bajaj D., Pramod D.

International Journal of Security and Privacy in Pervasive Computing, 2020, цитирований: 2, doi.org, Abstract

Humans are living in an era where they are interacting with machines day in and day out. In this new era of the 21st century, a virtual assistant (IVA) is a boon for everyone. It has opened the way for a new world where devices can interact their own. The human voice is integrated with every device making it intelligent. These IVAs can also be used to integrate it with business intelligence software such as Tableau and PowerBI to give dashboards the power of voice and text insights using NLG (natural language generation). This new technology attracted almost the entire world like smart phones, laptops, computers, smart meeting rooms, car InfoTech system, TV, etc. in many ways. Some of the popular voice assistants are like Mibot, Siri, Google Assistant, Cortana, Bixby, and Amazon Alexa. Voice recognition, contextual understanding, and human interaction are some of the issues that are continuously improving in these IVAs and shifting this paradigm towards AI research. This research aims at processing human natural voice and gives a meaningful response to the user. The questions that it is not able to answer are stored in a database for further investigation.

Survey of Online Identity Management Techniques on Blockchain

Gahlawat M.

International Journal of Security and Privacy in Pervasive Computing, 2020, цитирований: 0, doi.org, Abstract

Secure identity management is one of the controversial topics in the cybersecurity landscape. The user needs to rely on third-party providers for managing their personal information, which is a big security concern. Traditional identity systems typically suffer from single points of failure, lack of interoperability, and privacy issues such as encouraging mass data collection and user tracking. Blockchain technology has the potential to support novel data ownership and governance models with built-in control and consent mechanisms, which may benefit both users and businesses by alleviating these concerns. Blockchain-based systems provide the possibility for their users to insert their data in this distributed ledger. Users can trust the blockchain as it is leveraging consensus mechanisms to validate and gather the transactions in immutable blocks. The transparent and decentralized nature of the blockchain network enables the development of a non-refutable and unbreakable record of data, which is the fundamental feature of many applications, such as identity management.

Linear Regression on Internet Banking Adoption Dataset Using WEKA

Verma N.N., Pathak D.

International Journal of Security and Privacy in Pervasive Computing, 2020, цитирований: 1, doi.org, Abstract

Data mining or knowledge discovery in the database (KDD) is an excellent process to find out valuable information from a large collection of data. Data mining has successfully been used in different fields such as medical, marketing, banking, business, weather forecasting, etc. For the banking industry, data mining, its importance, and its techniques are vital because it helps to extract useful information from a large amount of historical data which enable to make useful decisions. Data mining is very useful for banking sector for better acquiring and targeting new customers and helps to analyze customers and their transaction behaviors. In the recent era, a new technology that has achieved considerable attention, especially among banks, is internet banking. Its large scope of applications, its advantages brings an immoderate change in a common human's life. Linear regression is one of the most commonly used and applied data mining techniques. Linear regression is really a very fast and simple regression algorithm and can give the best performance if the output variable of your data is a linear grouping of your inputs. In this paper, the linear regression is applied on internet banking adoption dataset in order to compute the weights or coefficients of linear expression and provides the predicted class value. The analysis here is done with the help of WEKA tool for data mining.

Evaluation of the Dynamic Pricing Model in Cloud

Kandpal M., Patel K.A.

International Journal of Security and Privacy in Pervasive Computing, 2020, цитирований: 2, doi.org, Abstract

Many of the companies started moving towards cloud computing because of its characteristics like pay as you go, easy to use, scalable, multi-tenant, secure, etc. There are many cloud providers providing cloud services over the internet. There are number of pricing policies for the user. These pricing policies can be categorised as static and dynamic pricing. This paper represents the enhancement and evaluation of the proposed dynamic resource pricing model for cloud resources based on the consumer behaviour. For model evaluation, one tail two sample t-test has been used. The results show the model will be helpful to the cloud provider for profit maximisation.

UML-Based Data Warehouse Design Using Temporal Dimensional Modelling

Reddy G.S., Suneetha C.

International Journal of Security and Privacy in Pervasive Computing, 2020, цитирований: 0, doi.org, Abstract

The design of a data warehouse system deals with tasks such as data source administration, ETL processing, multidimensional modelling, data mart specification, and end-user tool development. In the last decade, numerous techniques have been presented to cover all the aspects of DW. However, none of these techniques stated the recent necessities of DW like visualization, temporal dimensions, record keeping, and so on. To overcome these issues, this paper proposes a UML based DW with temporal dimensions. This framework designs time-dependent DW that allows end-users to store history of variations for long term. Besides, it authorizes to visualize the business goals of organizations in the form of attribute tree via UML, which is designed after receiving user necessities and later reconciling with temporal variables. The implementation of proposed technique is detailed with university education database for quality improvement. The proposed technique is found to be useful in terms of temporal dimension, long-term record keeping, and easy to make decision goals through attribute trees.

A Review on Identity and Access Management Server (KeyCloak)

Divyabharathi D. N., Cholli N.G.

International Journal of Security and Privacy in Pervasive Computing, 2020, цитирований: 11, doi.org, Abstract

KeyCloak is an open source identity and access management arrangement focused on present day applications and administrations. It makes it simple to protect applications and administrations with next to zero code. The identity and access management server component provides centralized user management, authentication, and single sign-on identity brokering user federation, social login, client adapters, an admin console, and an account management console for the applications. With KeyCloak, the user management and authentication functions may be integrated with an externally managed system, such as LDAP or active directory. KeyCloak provides single sign-on infrastructure for authentication and session management. In this paper, the authors present an overview of KeyCloak that gives the objectives and features of KeyCloak and comparisons between the servers. They also present protocols of KeyCloak. Finally, benefits of KeyCloak are defined.

Design for Software Risk Management Using Soft Computing and Simulated Biological Approach

Aggarwal A., Dhindsa K.S., Suri P.K.

International Journal of Security and Privacy in Pervasive Computing, 2020, цитирований: 6, doi.org, Abstract

The process of software evaluation is one of the key tasks that are addressed by the quality assurance teams so that the risks in the software suite can be identified and can be removed with prior notifications. Different types of metrics can be used in defect prediction models, and widely used metrics are source code and process metrics. A simulated environment for the entire process shall be generated for multiple scenarios and parameters so that the results and conclusion can be depicted in an effective way. The focus of research is to develop a narrative architecture and design for software risk management using soft computing and nature-inspired approach. The proposed approach titled simulated biological reaction (SBR) is expected to have the effectual results on multiple parameters with the flavor of soft computing-based optimization. The proposed approach shall be integrating the simulation of microbiological process in different substances and elements to produce a new substance.