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Research Paper

Phishing Web Detection using Machine Learning Technique

Everyone is addicted to the internet these days. All of us have made reservations, recharged, shopped, and banked online. Phishing is a type of online threat to websites. Phishing, according to the original website, is an illegal attempt to collect information such as a credit card number, login ID, and password. We presented a successful machine learning-based phishing detection technique in this research. Overall, the experimental findings demonstrated that the suggested method performs best when used in combination with support vector machine classifiers, detecting 95.66% of phishing attempts and matching websites with just 22.5% of novel functionality. When compared to many popular phishing datasets from UCI's repository, the suggested method yields encouraging results. For machine learning-based phishing detection, the suggested method is, therefore, the one that is favoured and utilized.

Published by: Samiksha Sachin Karanjkar, Shruti Jadhav, Vrushali Pimpale, Rahul Navale

Author: Samiksha Sachin Karanjkar

Paper ID: V10I6-1316

Paper Status: published

Published: November 26, 2024

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Research Paper

Ingredients for Transforming from Wild to a Workable Multigenerational Team!!!An Appraisal Study

The objective of this paper is to exhibit the study of the work variables influenced by multigenerational diversity and to understand how the cohorts would respond to them. An initial independent examination of the characteristics of the generation cohorts and work variables was done. A detailed listing of work variables followed by classifying them on the basis of their impact was done. The work variables are classified as Organizational, Group and Individual variables, which are highly influenced by multigenerational diversity. This paper intends to bring out the study done on the group category of work variables, which have affected the manner in which the team cohorts had reacted thereby inducing a sequel of events. The researcher collected data from secondary sources and through interviews among IT Project managers of large, medium and small projects and arrived at the identification of the work variables that are influenced by multigenerational diversity.

Published by: Ranjana Magdalene, Dr. K Chitra

Author: Ranjana Magdalene

Paper ID: V10I6-1313

Paper Status: published

Published: November 25, 2024

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Review Paper

AI-Powered Talent Acquisition Platform

Recruitment processes are frequently inefficient and time-intensive, often plagued by manual resume screening, mismatches between candidates and jobs, and delays in scheduling interviews. This paper discusses the creation of an AI-driven Talent Acquisition Platform that incorporates Generative AI technologies to transform recruitment practices. The platform automates key functions such as extracting candidate information, accurately matching resumes with job descriptions, optimizing the onboarding process, and facilitating efficient interview scheduling. The integration of GEN AI models also offers real-time analytics to deliver actionable insights. This study examines how these advancements improve recruitment precision, decrease the time-to-hire, and enhance the overall hiring experience for both employers and job seekers. The paper provides a detailed look at the platform's system architecture, implementation strategies, and performance metrics, with a focus on scalability, data security, and user interaction.

Published by: Srushti Ganar, Prof. Pooja More, Anuja Birajdar, Pragati Birhade

Author: Srushti Ganar

Paper ID: V10I5-1356

Paper Status: published

Published: November 25, 2024

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Research Paper

A Review of Distributed Denial of Service Attack Techniques and Mitigation Strategies

This report extensively analyzes Distributed Denial of Service (DDoS) attacks, focusing on their motives, methodologies, and impacts across various sectors. It classifies different DDoS attack types, examining those targeting specific network layers and emphasizing unique attack patterns within cloud environments. The study also reviews trends highlighting the rising frequency of these attacks in government, finance, and online gaming sectors. To counteract these threats, the report outlines a range of preventive and mitigation strategies. It covers traditional methods like IP blacklisting, filtering, and firewalls, as well as advanced solutions involving real-time traffic monitoring and machine learning for dynamic anomaly detection. The effectiveness of cloud-based defenses, application-layer security practices, infrastructure resilience, and the integration of blockchain technologies are also explored. This comprehensive analysis ultimately aims to provide insights into the evolving landscape of DDoS attacks, advocating for a multi-layered approach to enhancing cybersecurity.

Published by: Shantanu Gupta, Sivakumar V, Anish Rout, Devanshu Madnani

Author: Shantanu Gupta

Paper ID: V10I6-1277

Paper Status: published

Published: November 25, 2024

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Research Paper

Analysis of Underground Circular and Rectangular Water Tanks by using Stiffener

This paper presents an analysis of a circular water tank using the finite element method (FEM). The tank's wall is examined for parameters such as moment and hoop tension at various levels, considering the effects of hydrostatic and soil pressures, along with the use of stiffeners. Additionally, the wall of a rectangular water tank is analyzed for vertical and horizontal moments at different levels, subjected to similar pressures. The analysis is performed using the FEM software STAAD-Pro V8i. For both tank types, the wall is modeled with its bottom fixed and top free. The wall is divided into several 4-node rectangular (quadrilateral) plate elements, and vertical beam elements are added up to the full height of the tank. The tank is then subjected to a triangularly varying hydrostatic load and soil load. Various types of stiffeners are incorporated into the tank design, and the results are compared with conventional design methods based on moment values.

Published by: Archana Dattatray Thorat, Dr. Vaibhav Vilas Shelar, Mr. Vijay Shivaji Shingade

Author: Archana Dattatray Thorat

Paper ID: V10I6-1306

Paper Status: published

Published: November 24, 2024

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Review Paper

Advanced Methods and Techniques for Enhancing Soil Quality in Civil Engineering Applications

The soil quality plays a crucial role in civil engineering, affecting the safety, durability, and stability of constructed structures. This paper explores advanced soil improvement techniques in civil engineering applications, such as foundations, road construction, and slope stabilization. Both traditional and cutting-edge methods are examined, including soil stabilization with chemicals, the use of geosynthetics, and biotechnological approaches. Additionally, this paper evaluates these techniques' environmental and economic impacts, providing a holistic view of soil enhancement practices in modern engineering.

Published by: Macchindranath Nagoji Kumbhar, Vaibhavi G. Galande, A. V. Bhanvase

Author: Macchindranath Nagoji Kumbhar

Paper ID: V10I6-1297

Paper Status: published

Published: November 24, 2024

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