International Journal of Communication Networks and Information Security (IJCNIS)
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1021 research outputs found
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Efficient Dual-Level Encryption for Securing Data in HDFS Using Hybrid User-Defined Function (HUDF)
No full textBig Data is a new class of technology that gives businesses more insight into their massive data sets, allowing them to make better business decisions and satisfy customers. Big data systems are also a desirable target for hackers due to the aggregation of their data.The Hadoop Distributed File System (HDFS) stores massive data in the Hadoop framework. Since HDFS does not safeguard data privacy, encrypting the file is the right way to protect the stored data in HDFS but takes a long time. In this paper, regarding privacy concerns, we use different compression-type data storage file formats with the proposed hybrid user-defined function (HUDF)based on an XOR-Onetime pad with AES to securedata in HDFS. In this way, we provide a dual level of encryptionby maskingselective data and whole data in the file. Our experiment demonstrates that this scheme offersoverall data security and also faster processing time than the conventional methods. The proposed HUDF with ORC, Zlib (Z) file format (HUDF-ORC-Z) gives 9-10% better performanceresults than 2DES and other method. Finally, we efficiently utilized the space, improved query processing time,and decreased data load timewith the Hive engine
FABRICATION AND INVESTIGATION OF BANANA FIBER AND JUTE FIBER REINFOERCED COMPOSITE MATERIAL
No full textIn the current scenario Automobile industry focuses on enhancing the strength and reducing the weight of body parts. The fuel efficiency and emission regulation of two wheelers are two important issues in these days. The best way to increase the fuel efficiency without sacrificing safety is to employ fiber reinforced composite materials used for the two wheeler. In this study two wheeler mudguard which is used to protect the mud and rain water placed on front and rear wheel is considered for investigations. Mudguard is the one of the part having more weight and in my work, the existing steel/ABS plastic mudguard replace with composite mudguard. The fabrication of composite material is made up of Epoxy resin with banana and jute reinforced polymer is carried out and weight of the mudguard will reduce. In this work, fabrication of Banana and jute fiber composite material is completed and its mechanical properties like hardness, tensile strength etc., are calculated and analyzed. Experimental testings are conducted before and after curing with four different sample ratios. The maximum values are obtained for the sample ratios (40:60, 50:50)
 
Impact of Dynamic Technological Advancement on the SaaS-Based Solution Delivery Process in Software Industry: A survey
No full textTo keep up with rapid technological advancements and evolving business needs, the enterprise software industry prioritizes customer-centricity and adopts Industry 5.0 principles. In this article, we have reviewed the available research literature and interviewed stakeholders associated with the SaaS-based supply chain solution industry, emphasizing the practical challenges technical solution providers face when transitioning from on-premises solutions to cloud-based infrastructure while aligning with industry revolutions. One of the primary challenges we uncovered is effectively integrating these principles into software solutions and implementing Industry 5.0 approaches in the SaaS software delivery process. Addressing customers' dynamic requirements requires a workforce that continually learns and creates a knowledge base that aligns with new demands, for which a lack of suitable end-user technical documentation related to SaaS customization acts as a bottleneck. Furthermore, customers often face challenges when adopting innovative solutions inspired by the dynamic industry revolution. Building consistent customer engagement and establishing open communication channels for future solution roadmaps pose ongoing challenges for SaaS technology providers. This article discusses the end-to-end transformation required to enhance an organization's capabilities. The study findings can benefit critical organizational stakeholders, including change management leadership, policymakers, and decision-makers, in making informed decisions.
 
Identification and analysis of factors affecting the development of small and medium businesses in Iraq
No full textThe main goal of this research is to identify and analyze the factors affecting the development of small and medium businesses in Iraq. This research is placed in the mixed group (qualitative-quantitative) in terms of practical purpose and in terms of paradigm. In order to analyze the data in the qualitative part, the inductive content analysis method was used, and in the quantitative part, pairwise (binary) comparisons with the AHP technique were used to rank the categories. The study population of this research includes faculty members, entrepreneurship experts and small and medium business owners in Iraq, who were selected through theoretical and targeted sampling. According to the knowledge of the researcher and considering the objectives of the research, interviews were conducted with 32 academic staff members, experts and experts of entrepreneurship and business development in Iraq. Collecting research data in the qualitative part with two documentary-library methods, field observation and interview, and in the quantitative part through the pairwise comparison questionnaire. The results showed that after analyzing and coding the information obtained from the interview, 14 main categories were extracted, which were classified from the most important to the least important categories after ranking. These categories in order of importance are as follows: human capital management, market and marketing, technology and innovation, policies and laws, support, organizational culture, networking and social capital, risk management, research and development, access to resources, access to infrastructure, environmental sustainability, security and establishment and positive economic status
Network Stability Based Multicriteria Weighted MPRs Selection Algorithm for Mobile Ad Hoc Networks
No full textManets are self-governing networks using several mobile nodes, which communicate together through wireless media, without the necessity of prior infrastructure. Therefore, due to highly dynamic and unconfident environments, Manets are weak to guarantee link lifetime, security, reliability and stability. Since, mobility, energy and security are the main factors for improved performance in the network. Paths and relay devices with enhanced stability and security are considered as critical subjects. The study suggests an improved process based on a Multicriteria purpose consistent with numerous systems of measurement. These systems of measurement are energy level, trust measure and mobility of mobile nodes. The concept is to select improved Multipoint relays (MPRs) able to transmit data efficiently, and increase lifetime and reachability. The proposed improvement supports the routing and the selection of paths. The selection of the greatest effective relay nodes can enhance the classification performance. The scheme is based on the OLSR protocol and performance results are defined using the network simulator (NS3) with different movement models. The results showed significant improvements in MCW_OLSR. The proposed version enhances network proficiency for different mobile environments
An Ensemble Based Astrological Prediction Model for Profession and Marriage Using Machine Learning Strategies
No full textThe fascination with astrology, an ancient and conventional form of prediction, continues to grow despite the absence of universal astrological prediction rules or principles globally. While accuracy is not guaranteed, astrologers prioritize offering high-quality services over establishing universal standards. In contrast, machine learning yields superior outcomes across diverse applications through its capacity to handle large, noisy, complex datasets via classification and prediction. This paper aims to present a scientific method that addresses the shortcomings of traditional astrology, identifies universal prediction rules, and employs classification techniques—Neural Network (NN), Import Vector Machine (IVM), Random Forest (RF), and Iterative Boosting—to validate the reliability of astrology in predicting profession and marriage outcomes. We computed Correctly Classified Instances (CCI), Incorrectly Classified Instances (ICI), Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), and Relative Absolute Error (RAE) using cross-validation with 10, 12, and 14 folds. Additionally, we evaluated F-Measure, Precision, True Positive Rate, False Positive Rate, and area values for MCC, ROC, and PRC. For three-class labeling of professor, businessman, and doctor, we determined the true positive rates, false positive rates, accuracy, F-measure, PRC, and ROC area. We gathered birthdate, birthplace, and time of birth data from one hundred individuals across these professions, creating horoscopes using software. Data analysis involved building a datasheet in .csv format and employing the Weka tool to assess various parameters, including classifier accuracy, to identify the most effective classification method
The Role of Wireless Telemedicine and e-Health in Modern Healthcare: Challenges and Innovations
No full textTelemedicine and e-health have transformed modern healthcare by getting over geographical holes and enhancing the delivery of medical services. This review examines the evolution, current trends, applications, benefits, and challenges associated with wireless telemedicine and e-health. From its early telephone interviews to the integration of advanced technologies like computer based intelligence and wearable devices, telemedicine has persistently evolved to meet the demands of contemporary healthcare. Despite its numerous advantages, including improved access to care and effective persistent disease management, telemedicine faces challenges related to security, technological restrictions, and regulatory issues. This review synthesizes current research to provide a comprehensive understanding of these technologies, featuring developments and areas for future development
Framework for Integrating AI-Based Teleradiology Solutions into Modern Healthcare Ecosystem for Predictable Response Time, Enhanced Connectivity, Patient Empowerment, Flexibility and Innovation
No full textBackground: The integration of AI-based teleradiology solutions into the modern healthcare ecosystem is becoming increasingly essential to improve diagnostic accuracy, reduce response times, and enhance patient care. As healthcare systems evolve, the need for advanced technological solutions that ensure connectivity, flexibility, and innovation has never been more critical.
Objective: This paper aims to develop a strategic framework for integrating AI-based teleradiology solutions that focus on achieving predictable response times, enhancing connectivity, empowering patients, and fostering flexibility and innovation in healthcare delivery.
Methodology: The study employs a qualitative approach, analyzing existing literature and case studies on AI in healthcare, teleradiology, and digital health solutions. The framework was developed by synthesizing insights from industry best practices, expert opinions, and technological trends.
Findings: The proposed framework highlights the critical components necessary for successful integration, including AI-powered triage systems, cloud-based solutions for enhanced connectivity, patient-centric tools for empowerment, and modular AI systems for flexibility. Key challenges such as regulatory compliance, data privacy, and resistance to change are also addressed, with strategies proposed for mitigation.
Conclusion: Integrating AI-based teleradiology solutions into the healthcare ecosystem can significantly improve diagnostic processes, reduce response times, and enhance patient care. The strategic framework provides a comprehensive guide for healthcare providers, policymakers, and technology developers to achieve these objectives while addressing potential challenges. Continuous evaluation and adaptation are crucial to maintaining the relevance and effectiveness of these solutions in the evolving healthcare landscape
Optimized Energy-Efficient Reliable Routing for Mobile Wireless Sensor Networks
No full textIn wireless sensor network (WSN), energy optimization is critical. Since resources, especially energy, are limited. This work introduces a new energy-efficient protocol for routing for WSNs to guarantee dependable data transfer to base stations (BS).These protocols follows a Clustered and hierarchical structure with clusters heads (CH), deputy CH nodes, and ordinary sensor nodes in each cluster, accounting for mobility in both the BS and the sensor nodes. A CH panel concept is presented wherein the BS chooses possible CH nodes, hence saving time and energy. To improve reliability, the protocol seeks to maintain a certain throughput level at the base station. According to the networks structure, transfer data from cluster heads nodes to the base station can be alternatively direct or multi- hops, using various pathways to boost dependability
Data to Decision-Making: An Analysis of Business Analytics Applications
No full textIn the ever-evolving business landscape, leveraging data for decision-making is crucial for staying competitive and improving operational efficiency. This paper, titled "Data to Decision-Making: An Analysis of Business Analytics Applications" explores how business analytics acts as a vital bridge between raw data and actionable insights, transforming strategies and operations across various sectors. Business analytics utilizes advanced tools and methods to examine data, uncover patterns, and provide insights that aid in making well-informed decisions. The paper provides an in-depth look at the different types of business analytics—descriptive, predictive, and prescriptive—and their specific applications. Descriptive analytics focuses on summarizing and interpreting past data to understand previous performance. Predictive analytics uses statistical techniques and machine learning to forecast future trends and outcomes. Prescriptive analytics takes it further by offering actionable recommendations based on data insights to guide strategic decisions and planning.
The research underscores the application of business analytics across multiple sectors, such as marketing, finance, operations, human resources, healthcare, retail, sports, and e-commerce. In the marketing domain, business analytics is instrumental in customer segmentation, assessing campaign effectiveness, and conducting market basket analysis, which results in more focused and efficient marketing strategies. In finance, it is crucial for managing risks, detecting fraud, and forecasting financial trends, contributing to the stability and development of financial institutions. In operational contexts, business analytics enhances supply chain optimization, inventory management, and quality control, resulting in improved efficiency and reduced costs. Human resources departments benefit from analytics through better talent acquisition, employee performance analysis, and strategic workforce planning. The healthcare sector uses analytics for optimizing patient care, predicting disease outbreaks, and improving hospital operations.Retailers leverage analytics for sales forecasting, customer behavior analysis, and store layout optimization, driving enhanced customer experiences and increased sales. In sports, analytics supports performance evaluation, injury prevention, and fan engagement, contributing to better team performance and fan satisfaction. E-commerce businesses use analytics for personalizing user experiences, dynamic pricing, and analyzing customer lifetime value, which helps in maximizing revenue and customer loyalty.
The paper also discusses the challenges of implementing business analytics, including concerns about data privacy, the complexity of integrating analytics with existing systems, and the demand for specialized skills and training. Additionally, it explores future trends in business analytics, including advancements in artificial intelligence, real-time analytics, and the development of more sophisticated predictive models.
In conclusion, this research underscores the transformative power of business analytics in enabling data-driven decision-making across various industries. By leveraging analytics effectively, organizations can derive valuable insights, streamline operations, and meet strategic goals. This paper seeks to clarify how business analytics can be utilized to make impactful decisions, thereby fostering organizational success and growth