JOURNAL OF WEB ENGINEERING & TECHNOLOGY

Emerging Trends in Web 3 Crowdfunding Platforms: A Comprehensive Analysis

Sumant Hemant Jadhav — 2023-12-21

The transformation of crowdfunding through the integration of Web 3 blockchain technology. It analyzes the limitations of traditional crowdfunding systems, including centralization, lack of transparency, high fees, and limited accessibility. The paper delves into the innovative features of Web 3 blockchain-based crowdfunding, such as decentralization, transparency, smart contracts, and global accessibility. It examines current literature and research discoveries to offer perspectives on the advantages and difficulties associated with this method. The survey paper aims to offer a comprehensive understanding of the potential impact of Web 3 blockchain on the crowdfunding ecosystem.

Exam Eval: An Automated Model for Correcting Exam Papers Using OCR and Text Summarization

Jami Satya Vaishnavi — 2023-12-21

In the realm of education, grading and correcting exam papers can be a time-consuming and often daunting task for teachers. To streamline this process and provide more efficient feedback to students, this project aims to develop a model that leverages advanced techniques in natural language processing (NLP) and computer vision. The primary objective is to correct exam papers by summarizing the handwritten answers provided by students, incorporating Optical Character Recognition (OCR) through OpenCV for handling handwritten scripts. This model addresses the challenge of grading handwritten scripts by automatically converting the handwritten text into a machine-readable format and generating concise summaries that align with the corresponding teacher's answer summary. By harnessing OCR capabilities, the model extracts text from handwritten images and preprocesses it to improve readability and accuracy. Subsequently, text summarization techniques are applied to condense the extracted text into coherent and informative summaries. The integration of OCR with text summarization provides an efficient and automated solution for correcting handwritten exam papers, ultimately saving time and effort for teachers. This model aims to enhance the grading process, provide consistent and unbiased evaluations, and offer valuable insights into students' performance by matching their answer summaries with those prepared by the teacher.

Leveraging Emotional Intelligence Based Computer Applications to Analyze Psychological Mitigate Suicidal Ideation in Society

Nidhi Singh Chauhan — 2023-12-21

The increasing incidence of suicidal ideation is a significant societal concern that requires novel, multifaceted approaches for effective mitigation. This research delves into the promising potential of Emotional Intelligence (EI) based computer applications as tools for the detection, analysis, and mitigation of psychological suicidal ideation within our society. The crux of this study lies at the intersection of Emotional Intelligence and Artificial Intelligence (AI), where AI techniques are enriched with EI principles to yield computer applications capable of identifying, understanding, and effectively responding to the emotional states of individuals. Harnessing advanced technologies such as Natural Language Processing, Machine Learning, and Sentiment Analysis, these applications can identify nuanced signs of distress and suicidal ideation in users' digital communication, enabling prompt intervention. The paper provides an extensive review of EI and its critical role in discerning and managing emotions, setting the stage for its applicability in AI systems. The possible advantages and challenges of fusing EI with AI to tackle mental health crises, such as suicidal ideation, are comprehensively discussed, underscoring the necessity of an ethically sound and sensitive approach. Further, the study provides an insightful exploration into the methods for creating these applications and evaluates existing applications, considering their real-world effectiveness. Paramount to this discussion is a deep dive into the ethical and privacy considerations surrounding the handling of sensitive mental health data. In conclusion, the societal impacts of EI-based computer applications are examined, specifically their potential to complement existing mental health services and revolutionize mental health care. Through this research, we aim to encourage ongoing innovation and refinement in the development of EI-based AI applications, ultimately contributing to more effective, scalable, and personalized mental health care solutions.

Enhancing Online Security: Machine Learning Methods for Phishing Detection—Literature Survey

B. Bavithra — 2023-12-27

Phishing attacks represent a substantial online security threat as they mimic authentic websites to trick users into disclosing sensitive information. Detecting these malicious websites is crucial for safeguarding user data and maintaining digital trust. This summary provides insight into the application of machine learning methods in the identification of phishing websites. Machine learning, which falls under the umbrella of artificial intelligence, has proven to be a robust instrument for automating the detection of phishing websites. This approach leverages the power of algorithms and predictive models to analyse website features and user behaviour patterns. These techniques, including supervised, unsupervised, and hybrid learning methods, enable the identification of subtle indicators that are challenging to spot with traditional methods. Key features used for detection include URL characteristics, website content, SSL certificate analysis, and user interaction data. Various machine learning algorithms, such as Random Forest, Support Vector Machines, and Deep Learning, have been employed to classify websites into either legitimate or phishing categories. This abstract explores the evolution of machine learning in the fight against phishing attacks, emphasising its ability to adapt to evolving tactics employed by cybercriminals. By continuously learning from new data, machine learning models enhance accuracy and effectiveness, thereby fortifying the defence against phishing threats in the ever-changing digital landscape. This research contributes to the ongoing efforts to secure the online environment and protect users from falling victim to phishing scams.

WAF for Serverless Application Frameworks

Pradeep Singh — 2023-10-23

In today's digital landscape, where online presence is crucial for businesses and organizations, safeguarding web applications against a myriad of cyber threats has become a paramount concern. Enter the Web Application Firewall (WAF), a formidable fortress shielding these digital gateways from malicious intrusions and attacks. Its significance transcends mere technical jargon, as it serves as a sentinel, perpetually vigilant against sophisticated hacking techniques that can compromise sensitive data and disrupt critical services. Imagine a virtual shield that inspects the virtual footprints of each incoming and outgoing web request, tirelessly scanning for any suspicious activities or abnormal patterns that could signal a potential security breach. From preventing notorious SQL injection attacks that can manipulate databases to thwarting insidious cross-site scripting attempts aiming to hijack user sessions, the WAF stands as an essential line of defence, fortifying the digital infrastructure. By leveraging advanced behavioural analysis and maintaining a repository of customizable rule sets, the WAF does not just react to known threats but anticipates emerging risks, adapting its strategies to ensure comprehensive protection. Its proactive stance not only guarantees the confidentiality and integrity of sensitive information but also plays a pivotal role in upholding the seamless accessibility of web applications, assuring users of a safe and trustworthy online experience. In a landscape where cybersecurity threats evolve at a breakneck pace, the WAF embodies resilience, perpetuating digital trust amidst the ever-shifting tides of cyber vulnerabilities. Its presence is not just a technical necessity but a testament to the commitment of organizations in safeguarding their digital ecosystems and preserving the integrity of their online operations.

Forthcoming Technological Breakthroughs in the Metaverse Development

B.M. Rajesh — 2023-10-23

The Metaverse represents an enduring and constant multiuser realm that merges the physical world with digital virtual elements. It stands as the cosmos beyond the realm of reality. The term “metaverse” refers to a shared, permanent, immersive, three-dimensional virtual environment that combines the physical and digital worlds and allows users to interact in real time while shopping, working, playing, and hanging out. Since the beginning of the internet, its quick development and the present entry into a new technological era with Metaverse have moved many human activities from the real world to the virtual one. All human necessities, from shopping to education, are now performed in a 3D virtual world where bitcoin is used for payments instead of actual money. Even art is available to buyers online in the current day. The Metaverse has led to the emergence of new professions and the expansion of the economy across numerous dimensions. People's lives are made simpler by the metaverse, yet there are certain obstacles along the road that take the form of downsides and uncertainties. The Metaverse offers India's developing e-commerce sector a big potential. The Indian e-commerce industry, estimated to reach $ 99 billion, is experiencing substantial annual growth. The e-commerce business in India has drawn growing attention from investors in Asia and other foreign markets. The idea of the Metaverse, with all of its advantages and disadvantages, is gradually changing society and people's way of life.

AI-driven Approaches in Indian Politics: A Novel Paradigm

Tharun Kumar M.D. — 2023-10-19

The intersection of artificial intelligence (AI) and politics has ushered in a new era of governance worldwide. While AI-driven approaches have gained traction in several countries, their potential within the Indian political landscape remains largely uncharted. This study endeavours to bridge this gap by introducing innovative AI-driven paradigms specifically tailored for the complexities of Indian politics. Drawing upon a comprehensive literature review and case studies, we illuminate novel applications of AI technologies, highlighting their potential to transform decision-making, engagement, and transparency in Indian politics. This study delves into the challenges and ethical considerations surrounding the adoption of AI in politics, emphasizing the importance of responsible implementation. Furthermore, it examines public perceptions and offers policy recommendations to foster trust and acceptance of AI-driven approaches. Through this exploration, we aim to provide a roadmap for policymakers, technologists, and political stakeholders seeking to harness AI's transformative capabilities for the benefit of Indian democracy. As India strives for more efficient, inclusive, and accountable governance, AI emerges as a powerful tool poised to revolutionize the nation's political landscape.

Unleashing the Power of Data Mining in Software Engineering: Applications and Case Studies

Vamsi Krishna Thatikonda — 2023-11-29

Recent times have seen the nexus of data mining and software engineering evolve into a potent force, promising to redefine both fields. This paper highlights the critical role and varies uses of data mining within the software engineering domain, backed by the latest academic resources. The deep dive reveals critical data mining methodologies, their pertinent role across different sectors, and their unique implementations within software engineering. Various organizations, including well-known ones like Facebook and Uber, have showcased a variety of applications for data mining in the realm of software engineering, such as bug prediction, software quality assurance, user behaviour analysis, code smell detection, and effective project management. Although challenges related to data quality and privacy are hurdles along the way, the main emphasis remains on the bright prospects of data mining in this field, thanks in large part to advancements in deep learning and enhanced data privacy and security measures. The potential ripple effects of these advancements on the future of software engineering also command attention. The paper ends on a hopeful note for the continued integration of data mining and software engineering, hinting at a vibrant future.