Call for Abstract
Edited Book on
“ Conversational AI ”
Publisher -Wiley
The Publisher will send the Book for Indexing: Scopus and offered to Web of Science
Book is under Publication Phase - Expected to Get Online by Feb-2023
Book Published
https://onlinelibrary.wiley.com/doi/abs/10.1002/9781394200801.ch24
Edited Book on “Conversational AI”
Mail your full Chapter at - rawat.romil@gmail.com
The book will be published under the Wiley-Scrivener imprint and will be indexed by Scopus and offered to Web of Science.
Important Guidelines for Chapter Preparation
Chapter Template - https://www.scrivenerpublishing.com/guidelines.php
Note that all chapters will be put through similarity software and publisher’s guidelines are an overall similarity index of less than 15% (with maximum 3% from any single source). Each Chapter should have Minimum of 18 Pages.
Reviewing Policy: The editor(s) will engage 2 single blind peer-reviewers to assess originality, clarity, usefulness, and adherence to scope of project.
Submission Guidelines and Link
All Chapters must be original and not simultaneously submitted to another journal or conference.
Important Dates:
Last Date of Chapter Submission: 5-February-2023
Acceptance : 15-February-2023
Full Chapter Submission with Corrections: 25 5-February-2023
Mail your Abstract at - rawat.romil@gmail.com
Details
About the topic
Natural language processing (NLP) and machine learning (ML) techniques are frequently combined with more traditional, static kinds of interactive technology, such chatbots, to create conversational AI. Through interactions that resemble human communication, this combo responds to users. Static chatbots simply provide the user a set of prepared responses and are rule-based. In contrast, a conversational AI model employs ML to learn new facts for further encounters and NLP to analyse and understand the meaning of human speech. NLP transforms a sizable amount of unstructured human linguistic input into a structured data format so that computers may comprehend it and use it to decide what to do and what to say. Consider the two NLP subfields of natural language understanding (NLU) and natural language generation (NLG) for a deeper grasp of NLP.
Conversational AI with Explainable AI models, such as chatbots, can assist minimise the labour of IT departments by providing solutions such as self-service chatbots that allow users to reset passwords and do other user identity operations. Chatbots are artificial communication systems that are getting more popular, but not all of their security concerns have been addressed. Conversational AI refers to the set of technologies that enable computers and machines to construct automated messaging and speech-enabled apps. This allows humans and machines to interact in a human-like manner. Alexa is one of several current chatbots that has a voice recognition system and can answer difficult questions. Voice recognition technologies are becoming more important as AI assistants become more popular. Because chatbot technology is in charge of gathering and securing personal information, hackers and other dangerous software are naturally drawn to it. Despite the growing potential of cyber-attacks, businesses have implemented conversational chatbots and automatic response software on their websites and social media platforms. Chatbots are widely used in customer support operations by platforms like Facebook, WhatsApp, and WeChat. While conversational AI will likely benefit business operations, it can also be used by hackers as a means of redirecting their cyber attacks. AI systems already have a wealth of information on humans, allowing them to better understand what types of arguments are most effective for each person. When combined with conversational AI's incredible human-like ability to converse with you, it's a prescription for disaster. Spam calls, fraudulent attempts, and phishing attacks are all possible outcomes.
About the book
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, who respond to their questions promptly and accurately 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 become more popular like Alexa. Chatbots in the corporate world have advanced, technical connections with clients, thanks to improvements in artificial intelligence. Contrary to this belief, these chatbots’ increase in 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 it frequently locks workers out. User privacy violations are becoming more common, emphasizing the dangers of employing chatbots. Vulnerabilities are systemic problems that enable thieves to breach 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 behaviour and discussions, or to trick individuals into disclosing personal information like bank account details.
Authors can submit any number of chapters and can use Chapter topic of their work, relating towards Book Theme.
Tentative Topics but not limited to:
· Advances in Explainable AI with Adaptive and Intelligent Assistant Systems Security models for Chabot.
· Automatic Speech Recognition Design Modeling .
· Accelerating Automated Speech Recognition On-Demand.
· Text-to-speech (TTS) stage synthesis.
· Building Domain Specific Speech Recognition Models on GPUs.
· Computer Animation and Virtual Worlds Threats system assessment using Conversational AI.
· Conversational AI for Cloud platform security.
· Conversational AI: An Security features, Applications & Future Scope at Cloud Platform.
· Artificial Intelligence effectiveness for Conversational Agents in Health Care security.
· Natural Language Processing based security applications for Conversational AI.
· Conversational AI-Based Solutions and Models For Security Testing.
· Evaluation and Improvement of Chatbot Text Classification Data using Conversational AI for Cloud platform.
· Chatbot Vs. Intelligent Virtual Assistant threat analysis.
· Methods for Security Threats analysis and Security Testing for Chatbots using Conversational AI.
· Self-destructing messages modeling by Conversational AI at Cloud Platform.
· Industries Using Chatbots cyber attack taxonomy.
· Emergence of cyber threat Conversational AI and Big Data in Healthcare.
· Conversational AI Security Development Lifecycle.
· Conversational AI based security threats for Military , business , and educational platforms.
· Text-based and Voice-based interface vulnerability modeling using Conversational AI.
· Conversational AI Bot for instant messaging protocols.
· Conversational AI for image moderation and natural-language understanding (NLU) threat analysis.
· Conversational AI threat identification at Industrial Internet of Things.
· Chabot warfare’s for cyber threat escalation.
· triggering remote access Trojan using Conversational AI.
· Messaging Apps Vulnerability assessment for Block chain Technology using Conversational AI.
· intelligent and automated conversational systems threat.
· Chatbot Attack Vector
· Risks for Conversational AI Security.
· Chatbots threats for social networking hubs and instant messaging
Keywords:
• Natural Language Processing (NLP)
• IoT
• Internet bot
• List of chatbots
• Social bot
• Software bot
• Automatic Speech Recognition ( ASR)
• Natural Language Understanding (NLU)
• Search Engines Optimization
• Quantum theory
• Twitterbot
• Virtual assistant
• Cyber crime
• Artificial Intelligence
• Machine Learning
• Neural Network
• Cryptography and Information Security
• Internet of Thing
• quantum attacks
• transactions of quantum money
• Quantum Forensics
• Algorithms and computing
• Digital Weapon
• Cyber threat intelligence
• Cyber-warfare and Hacking
• Chatbot
• Malicious chatbots
• human-computer dialogue system
• social chatbots
• ChatScript
• Cyber security
• Conversational AI
• Cloud Computing
• Conversational AI Agents
• chatbots
• voice assistants
• natural language processing
• human–computer interaction
• threat analysis.
• Virtual Assistant
• Adaptive Intelligent Assistant
• Text and Voice-based interface
• Big Data
• instant messaging
• Alexa
• Voice Recognition
• Voice Processing
• Data Science
• Analytics
• Logic
• Conversational AI
• cloud security
• chatbot security
• Encryption,
• authentication,
• processes
• protocols
Editors
Romil Rawat, Assistant Professor, Shri Vaishnav Vidyapeeth Vishwavidyalaya, Indore India - rawat.romil@gmail.com
Inquires:
Editor Details
a) Romil Rawat
https://www.linkedin.com/in/romil-rawat-537331175/
https://scholar.google.com/citations?user=lpe1g8QAAAAJ&hl=en
Shri Vaishnav Vidyapeeth Vishwavidyalaya, Indore, India
Romil Rawat is currently working as Assistant Professor in Shri Vaishnav Vidyapeeth Vishwavidyalaya, Indore, India. He attended several research programs and received research grants from USA, Germany, Italy and UK. The Author has research alignment towards Cyber Security, IoT, Dark Web Crime analysis and investigation techniques, and working towards tracing of illicit anonymous contents of cyber terrorism and criminal activities. He also chaired International Conferences and Hosted several research events including National and International Research Schools, PhD colloquium,Workshops, training programs. He also published several Research Patents.