posted by organizer: AIES21 || 2576 views || tracked by 2 users: [display]

UMOD 2021 : Understanding and Mitigating Online Deception (Frontiers in Artificial Intelligence) - ISSN: 2624-8212

FacebookTwitterLinkedInGoogle

Link: https://www.frontiersin.org/research-topics/17902/understanding-and-mitigating-online-deception#overview
 
When N/A
Where N/A
Submission Deadline Dec 30, 2021
Categories    manipulation   online deception   ethics   privacy
 

Call For Papers

Special issue: "Understanding and Mitigating Online Deception"
Journal: Frontiers in Artificial Intelligence - AI for Human Learning and Behavior Change

Electronic ISSN: 2624-8212
Indexed in: PubMed Central (PMC), Google Scholar, DOAJ, CrossRef, Digital Biography & Library Project (dblp), CLOCKSS, OpenAIRE

Topic editors: Esma Aïmeur (University of Montreal, Canada), Jean-Gabriel Ganascia (Université Pierre et Marie Curie, France), Lada Timotijevic (University of Surrey, UK), and Claude Kirchner (Institut National de Recherche en Informatique et en Automatique, France)

Scope: Speaking at the Web Summit technology conference in Lisbon, Tim Berners-Lee listed some of the current problems of the Web: fake news, privacy issues, collection, and abuse of personal data as well as the way people are profiled and then manipulated. Indeed, the initial optimism about the positive potentials of the Internet and social media has given way to concerns that people are being manipulated through the constant harvesting of personal information and through the control over the information they see can online that are based on the categories they are classified into. Even though online users, in general, report a high concern for their privacy, they tend to have privacy-compromising online behavior. This privacy-compromising behavior is not accidental and is often the result of crafty and sly manipulation of the users by deceivers with malicious objectives.

The digital, including in particular Artificial Intelligence (AI), is essential in the fight against online deception attacks such as spearphishing, web cache deception, practical cache poisoning, marketing or economical dark patterns , whether deployed as a countermeasure to automatically identify and mitigate such attacks or simply to help and guide the user to steer away from online threats. Indeed, the main advantage of AI is its adaptability, and learning from data to detect attacks and personalize the protection to the user’s needs and preferences. However, this might be its weakness as well. Specifically, AI could be biased (e.g. reflecting the biases that might be in the data), it might be used for mass surveillance purposes, or it might guide people towards behavior which is not necessarily beneficial for them, unintentionally or even purposefully, steering them away from better choices and alternatives. Consequently, it is imperative to develop new policy frameworks and ethical guidelines to govern the development and the deployment of such AI platforms.

The goal of this Research Topic is to (1) provide an understanding of the landscape of online deception, (2) highlight how AI is the perfect vehicle to provide personalized privacy and online deception awareness, and (3) detail how to develop responsible and ethical AI applied solutions. For so doing, we welcome theoretical and applied submissions that address, but are not limited to the following subtopics:

Types and mechanisms of deception:
- Phishing.
- Fake news, and AI-generated fake videos.
- Unethical persuasive technologies.
- Unethical behavior (system’s, designer’s, user’s, company’s).
Psychological factors predicting susceptibility to deception:
- Trust.
- Cognitive biases.
- Social influence.
- Vulnerability.
- Personalization for malicious purposes
- Psychological/social impacts (e.g. manipulation, social exclusion, threats to autonomy, identity, etc.).
Artificial Intelligence (AI) solutions:
- Chatbots and recommender systems as awareness tools .
- Detecting/mitigating AI bias solutions.
- AI-enabled online security companions.
- Frameworks for developing responsible AI.
Mitigation:
- Ethical and social implications of AI-powered security solutions.
- Legal and policy instruments: risk management, governance, ethical and policy frameworks.
- Applications and case studies of online deception.

PUBLISHING FEES: https://www.frontiersin.org/about/publishing-fees

FEE SUPPORT INITIATIVE: https://frontiers.qualtrics.com/jfe/form/SV_51IljifwFBXUzY1

*Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.

Related Resources

IEEE-Ei/Scopus-ITCC 2025   2025 5th International Conference on Information Technology and Cloud Computing (ITCC 2025)-EI Compendex
Security 2025   Special Issue on Recent Advances in Security, Privacy, and Trust
ICSTTE 2025   2025 3rd International Conference on SmartRail, Traffic and Transportation Engineering (ICSTTE 2025)
ASIACCS 2025   The 20th ACM ASIA Conference on Computer and Communications Security - deadline 2
IEEE-Ei/Scopus-CNIOT 2025   2025 IEEE 6th International Conference on Computing, Networks and Internet of Things (CNIOT 2025) -EI Compendex
IJMPICT 2024   International Journal of Managing Public Sector Information and Communication Technologies
Book 2025   Call for book Chapters Mitigating the Risks of AI Deepfakes
MATHCS 2024   2nd International Conference on Mathematics, Computer Science & Engineering
CVAI 2026   2026 International Symposium on Computer Vision and Artificial Intelligence (CVAI 2026)
Canadian AI 2025   38th Canadian Conference on Artificial Intelligence