AI-Driven Cyber Security for Brands and Users on Social Media Advertisement
This research paper explores the domain of arti- ficial intelligence (AI)-powered cyber security and its crucial importance in protecting companies and users from new cyber threats and attacks in the world of social media advertising. The present study commences by offering a thorough examination of the dynamic terrain of social media advertising, emphasizing its profound impact on brand communication and tactics for engaging with consumers. The growing significance of social media advertising for organizations has concurrently drawn the attention of unscrupulous individuals who aim to exploit weak- nesses, hence emphasizing the indispensability of implementing strong cyber security protocols. This proposed study examines the impact of artificial intelligence (AI) on enhancing cyber security measures within the realm of social media advertising. Through the utilization of AI-powered solutions, both companies and users have the ability to anticipate, detect, and address emerging cyber risks with exceptional accuracy and swiftness. This article exam- ines the use of AI-powered tools and approaches in the domains of threat detection, fraud protection, and content moderation. These applications aim to enhance the safety and reliability of brands and users inside their respective environments. The argument put forth supports a proactive stance towards security, highlighting the significance of including AI-driven tools and techniques as a fundamental element within a comprehensive cybersecurity framework. Through this action, companies have the ability to safeguard their digital existence, maintain their standing, and nurture their client connections, while individuals can partake in a social media environment that is characterized by enhanced safety and heightened security.
Authors
- Muhammad Tayyab
- Kaushal Kishore Mishra (ORCID: https://orcid.org/0000-0001-6466-0575)
- Femina Sardana
- Abdullah
Institutions
- Chandigarh University (IN)
- Taylor's University (MY)
Publication Details
- Published
- 2024-11-20
- DOI
- https://doi.org/10.1109/icetas62372.2024.11119873
- Citations
- 1
- Primary Topic
- Impact of AI and Big Data on Business and Society
- Type
- article
- Field-Weighted Citation Impact
- 0.49