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  • Search: isPartOf:"Generative AI for Web Engineering Models"
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chapter 21
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Rehman, Abdul 5 Jhanjhi, N. Z. 4 Shah, Imdad Ali 4 Farooq, Sumair 3 Mahadevappa, Poornima 3 Naeem, Muhammad 3 Siraj, Muzzammil 3 Tayyab, Muhammad 3 Ali, Shoukat 2 Arbab, Saira Khurram 2 Bhambri, Pankaj 2 Brohi, Sarfraz Nawaz 2 Khan, Nasrullah 2 Miran, Safdar 2 Muzammal, Syeda Mariam 2 Rana, Rachna 2 Abdali, Ahmad Shah 1 Ahmad, Bilal 1 Alansari, Zainab 1 Ashraf, Humaira Z. 1 Darwish, Dina 1 Devadas, Raghavendra M 1 Ebrahim, Mansoor 1 Gujjar J., Praveen 1 Hakeem, Arsalan 1 Hameed, Khizar 1 Hiremani, Vani 1 Hussain, Fida 1 Hussain, Imtiaz 1 Khan, Aurangzeb 1 Khan, Muneeba 1 Liaquat, Adil 1 Mehboob, Asim 1 Mumtaz, Majid 1 Muzammal, Syeda Mariam Mariam 1 Nawaz, Sarfraz 1 Preethi 1 Rizwan, Farzeen 1 Sapna, R. 1 Siddiqui, Hina Al Fatima 1
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Generative AI for Web Engineering Models 21
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The Role of Generative AI in Enhancing Web Engineering Efficiency and Business Innovation
Liaquat, Adil; Khan, Nasrullah; Siraj, Muzzammil; … - In: Generative AI for Web Engineering Models, (pp. 223-240). 2024
This study explores the impact of generative AI on web engineering and its part in driving business invention. By automating coding, design, and conservation tasks, generative AI enhances web development effectiveness, reducing time and trouble for inventors. The exploration employs a mixed-...
Persistent link: https://www.econbiz.de/10015537006
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Security Concerns: Machine Learning Approaches in the Modern Era and Web Engineering
Ashraf, Humaira Z. - In: Generative AI for Web Engineering Models, (pp. 241-268). 2024
This primarily aims to evaluate the ML approaches and web applications for authentication. Using machine learning, issues can be solved, and computers can carry out tasks. It attempts to understand the relationships between the data and automatically learns from the presented information. The...
Persistent link: https://www.econbiz.de/10015537007
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Introduction to Machine Learning Models for Web Engineering Concepts
Hussain, Fida; Arbab, Saira Khurram - In: Generative AI for Web Engineering Models, (pp. 269-284). 2024
The rapid-fire expansion of the Internet has deeply integrated into diurnal life, challenging nonstop updates to web armature to manage vast data and cover stoner sequestration. This chapter explores security enterprises like phishing, data breaches, and payment gateway vulnerabilities,...
Persistent link: https://www.econbiz.de/10015537008
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Generative AI-Driven Security Frameworks for Web Engineering: Innovations and Challenges
Rana, Rachna; Bhambri, Pankaj - In: Generative AI for Web Engineering Models, (pp. 285-296). 2024
The advent of Generative AI has triggered a paradigm shift across several domains, resulting in ground-breaking advances in text, picture, video, audio, and code production. However, this technical advancement has also increased cyber security intimidations, as hackers increasingly use...
Persistent link: https://www.econbiz.de/10015537009
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Introduction to Generative AI in Web Engineering: Concepts and Applications
Mahadevappa, Poornima; Muzammal, Syeda Mariam; Tayyab, … - In: Generative AI for Web Engineering Models, (pp. 297-330). 2024
Generative AI is transforming the art and science of web engineering by automating content generation, design and development through models like GAN, VAE or Transformers. These models can produce authentic text like a writer and other media, including images, so developers would save more time...
Persistent link: https://www.econbiz.de/10015537010
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Exploring Security Challenges in Generative AI for Web Engineering
Muzammal, Syeda Mariam; Mahadevappa, Poornima; Tayyab, … - In: Generative AI for Web Engineering Models, (pp. 331-360). 2024
Web engineering is being transformed rapidly by Artificial Intelligence (AI), particularly by Generative AI (GenAI), through its potential for automation in content creation, source code generation, design creation, and optimization. Along with the tremendous benefits that the integration of...
Persistent link: https://www.econbiz.de/10015537011
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Generative AI for Web Engineering Models in Physical Therapy
Siddiqui, Hina Al Fatima; Khan, Nasrullah; Miran, Safdar; … - In: Generative AI for Web Engineering Models, (pp. 361-378). 2024
This study explores the integration of generative artificial intelligence (AI) into web- grounded physical remedy operations through a mixed- styles approach, combining both quantitative and qualitative data. Aquasi-experimental design was employed to compare the efficacity of AI- enhanced...
Persistent link: https://www.econbiz.de/10015537012
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AI-Powered Threat Detection in Business Environments: Strategies and Best Practices
Tayyab, Muhammad; Hameed, Khizar; Mumtaz, Majid; … - In: Generative AI for Web Engineering Models, (pp. 379-436). 2024
The use of artificial intelligence (AI) in cybersecurity is a need due to the outpacing of conventional security measures by the fast growth of cyber threats. Exploring the function of machine learning (ML), deep learning (DL), and natural language processing (NLP) in recogniz- ing and reacting...
Persistent link: https://www.econbiz.de/10015537013
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Generative AI and Web Applications: Addressing Security Issues and Challenges
Arbab, Saira Khurram; Rizwan, Farzeen - In: Generative AI for Web Engineering Models, (pp. 437-456). 2024
The primary aim of this chapter is to focus on Generative AI and web-based applications. Further, we address the security issues and challenges. In today's digital era, web-based applications have become indispensable tools in web engineering. From social media platforms to online banking...
Persistent link: https://www.econbiz.de/10015537014
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Generative AI With Natural Language Processing for the Web
Darwish, Dina - In: Generative AI for Web Engineering Models, (pp. 457-470). 2024
NLP converts human language to computer understandable language is known as Natural Language Processing (NLP), though various diversified models have suggested so far, yet the need for a generative predictive model which can optimize depending upon the nature of problem being addressed is still...
Persistent link: https://www.econbiz.de/10015537015
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