Conversational Artificial Intelligence

  • 17h 49m
  • Anand Rajavat, K. Sakthidasan Sankaran, Kotagiri Srividya, Mary Sowjanya Alamanda, Rajesh Kumar Chakrawarti, Romil Rawat, Sanjaya Kumar Sarangi
  • John Wiley & Sons (US)
  • 2024

This book reviews present state-of-the-art research related to the security of cloud computing including developments in conversational AI applications. It is particularly suited for those that bridge the academic world and industry, allowing readers to understand the security concerns in advanced security solutions for conversational AI in the cloud platform domain by reviewing present and evolving security solutions, their limitations, and future research directions.

Conversational AI combines natural language processing (NLP) with traditional software like chatbots, voice assistants, or an interactive voice recognition system to help customers through either a spoken or typed interface. Conversational chatbots that respond to questions promptly and accurately to help customers are a fascinating development since they make the customer service industry somewhat self-sufficient. A well-automated chatbot can decimate staffing needs, but creating one is a time-consuming process. Voice recognition technologies are becoming more critical as AI assistants like Alexa become more popular. Chatbots in the corporate world have advanced technical connections with clients thanks to improvements in artificial intelligence. However, these chatbots’ increased access to sensitive information has raised serious security concerns. Threats are one-time events such as malware and DDOS (Distributed Denial of Service) assaults. Targeted strikes on companies are familiar and frequently lock workers out. User privacy violations are becoming more common, emphasizing the dangers of employing chatbots. Vulnerabilities are systemic problems that enable thieves to break in. Vulnerabilities allow threats to enter the system, hence they are inextricably linked. Malicious chatbots are widely used to spam and advertise in chat rooms by imitating human behavior and discussions, or to trick individuals into disclosing personal information like bank account details.

About the Author

Romil Rawat, PhD, is an assistant professor at Shri Vaishnav Vidyapeeth Vishwavidyalaya, Indore. With over 12 years of teaching experience, he has published numerous papers in scholarly journals and conferences. He has also published book chapters and is a board member on two scientific journals. He has received several research grants and has hosted research events, workshops, and training programs. He also has several patents to his credit.

Rajesh Kumar Chakrawarti, PhD, is a professor and the Dean of the Department of Computer Science & Engineering, Sushila Devi Bansal College, Bansal Group of Institutions, India. He has over 20 years of industry and academic experience and has published over 100 research papers and chapters in books.

Sanjaya Kumar Sarangi, PhD, is an adjunct professor and coordinator at Utkal University, Coordinator and Adjunct Professor, Utkal University, Bhubaneswar, India. He has over 23 years of academic experience and has authored textbooks, book chapters, and papers for journals and conferences. He has been a visiting doctoral fellow at the University of California, USA, and he has more than 30 patents to his credit.

Anand Rajavat, PhD, is Dean of Shri Vaishnav Vidyapeeth Vishwavidyalaya University and a professor and Director of Shri Vaishnav Institute of Information Technology of Shri Vaishnav Vidyapeeth Vishwavidyalaya University, Indore, India. He has over 22 years of teaching and industry experience, and he has authored or co-authored more than 110 publications. He has been a reviewer on numerous journals and has won numerous awards.

Mary Sowjanya Alamanda, PhD, is an associate professor in the Department of Computer Science and Systems Engineering at Andhra University College of Engineering, Visakhapatnam, India. She has four patents to her credit and has published more than 80 research publications in scholarly journals and conferences.

Kotagiri Srividya, PhD, is an associate professor and Head of the Department of Computer Science at the GMR Institute of Technology, Rajam, India. He has 18 years of teaching experience.

K. Sakthidasan Sankaran is a professor in the Department of Electronics and Communication Engineering at Hindustan Institute of Technology and Science, India. He is a reviewer and an editorial board member for several scholarly journals, and he has published more than 70 papers. He also has three books to his credit.

In this Book

  • A Glance View on Cloud Infrastructures Security and Solutions
  • Artificial Intelligence Effectiveness for Conversational Agents in Healthcare Security
  • Conversational AI: Security Features, Applications, and Future Scope at Cloud Platform
  • Unsupervised BERT-Based Granular Sentiment Analysis of Literary Work
  • Extracting and Analyzing Factors to Identify the Malicious Conversational AI Bots on Twitter
  • Evolution and Adoption of Conversational Artificial Intelligence in the Banking Industry
  • Chatbots: Meaning, History, Vulnerabilities, and Possible Defense
  • Conversational Chatbot-Based Security Threats for Business and Educational Platforms and Their Counter Measures
  • Identification of User Preference Using Human–Computer Interaction Technologies and Design of Customized Reporting for Business Analytics Using Ranking Consistency Index
  • Machine Learning for Automatic Speech Recognition
  • Conversational Artificial Intelligence at Industrial Internet of Things
  • Performance Analysis of Cloud Hypervisor Using Network Package Workloads in Virtualization
  • Evaluation of Chabot Text Classification Using Machine Learning
  • Enhanced Security in Chatbot
  • Heart Disease Prediction Using Ensemble Feature Selection Method and Machine Learning Classification Algorithms
  • Conversational AI: Dialoguing Most Humanly With Non-Humans
  • Counterfeit Pharmaceutical Drug Identification
  • Advanced Security Solutions for Conversational AI
  • Security Threats and Security Testing for Chatbots
  • ChatBot-Based Next-Generation Intrusion Detection System
  • Conversational Chatbot With Object Recognition Using Deep Learning and Machine Learning
  • Automatic Speech Recognition Design Modeling
  • The Future of Modern Transportation for Smart Cities Using Trackless Tram Networks
  • Evaluating the Performance of Conversational AI Tools: A Comparative Analysis
  • Conversational AI Applications in Ed-Tech Industry: An Analysis of Its Impact and Potential in Education
  • Conversational AI: Introduction to Chatbot’s Security Risks, Their Probable Solutions, and the Best Practices to Follow
  • Recent Trends in Pattern Recognition, Challenges and Opportunities
  • A Review of Renewable Energy Efficiency Technologies Toward Conversational AI
  • Messaging Apps Vulnerability Assessment Using Conversational AI
  • Conversational AI Threat Identification at Industrial Internet of Things
  • Conversational AI—A State-of-the-Art Review
  • Risks for Conversational AI Security
  • Artificial Intelligence for Financial Inclusion in India
  • Revolutionizing Government Operations: The Impact of Artificial Intelligence in Public Administration
  • Conversational AI and Cloud Platform: An Investigation of Security and Privacy
  • Chatbot vs Intelligent Virtual Assistance (IVA)
  • Digital Forensics with Emerging Technologies: Vision and Research Potential for Future
  • Leveraging Natural Language Processing in Conversational AI Agents to Improve Healthcare Security
  • NLP-Driven Chatbots: Applications and Implications in Conversational AI
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