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AI IN CYBER DEFENSE: PRIVACY RISKS, PUBLIC TRUST, AND POLICY CHALLENGES Azizi, Abdullah; Mohammadi, Mohammad Qias; Samadzai, Abdul Wahid
Jurnal Ilmiah Dinamika Sosial Vol 9 No 1 (2025)
Publisher : Universitas Pendidikan Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38043/jids.v9i1.6278

Abstract

The rapid integration of Artificial Intelligence (AI) into cybersecurity systems, particularly AI-based cyber defense systems, is reshaping the landscape of digital security. This study explores the social impacts of these systems, focusing on privacy, security, and public trust. The purpose of this research is to examine the effects of AI-driven cybersecurity on individuals and society, addressing concerns such as privacy risks, security breaches, and trust in digital platforms. A systematic literature review (SLR) methodology was employed, synthesizing relevant academic studies, conference proceedings, and reports from credible databases, including IEEE Xplore, ACM Digital Library, and ScienceDirect. The results reveal that while AI-based systems improve threat detection and response times, they also raise significant concerns about data privacy, surveillance, and the potential for algorithmic bias. Additionally, the integration of AI in cyber defense has prompted debates on the ethical implications of automated decision-making and the transparency of these systems. In conclusion, while AI offers transformative benefits in cybersecurity, careful attention is required to balance its advantages with ethical and privacy considerations. This study emphasizes the need for ethical frameworks and public awareness to ensure that AI-based systems are deployed in a manner that fosters trust and protects citizens' rights.
Enhancing Customer Awareness of Cybersecurity Threats in E-Banking: A Study on the Role of AI-based Risk Communication Tools Hakimi, Musawer; Kohistani, Ahmad Jamy; Sahnosh, Faqeed Ahmad; Samadzai, Abdul Wahid; Enayat, Wahidullah
Jurnal Ilmiah Manajemen & Bisnis Vol 10 No 1 (2025)
Publisher : Universitas Pendidikan Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38043/jimb.v10i1.6762

Abstract

With online banking on the rise, cybersecurity issues still occupy users' and financial institutions' minds. This study examines users' awareness of cybersecurity threats and their trust in artificial intelligence (AI) technology for fraud detection and risk communication in e-banking. A mixed-method design of quantitative survey of 384 users and qualitative interview of 20 participants was used to reflect broader insights. The survey quantified demographics, awareness of security protocols, and confidence in AI technology. Findings show that while users are very well aware of what to anticipate from repeated online threats and are careful with login passwords, they always fail to take the initiative concerning security practices like the changing of passwords. Overall, participants were confident in the application of AI systems, especially the efficiency and pace at which AI identifies fraud versus human agents. Skepticism was found for the effectiveness of chatbots based on AI. Statistical modeling showed that trust in AI strongly correlated with prior experience in cybersecurity, high rates of technology usage, and knowledge of online banking, with education level and age making little impact. The qualitative information further underscored the importance of personalized and clear communication from AI systems, suggesting that the way such machines talk to individuals can make or break trust. The study concludes by suggesting that user education at financial institutions should be enhanced, as well as developing AI systems with a method that employs personal communication approaches. The integration of human support with AI can potentially plug awareness gaps and improve security results across different user segments within the e-banking environment.
Generative AI in Enhancing Hydroponic Nutrient Solution Monitoring Hakimi, Musawer; Suranata, I Wayan Aditya; Ezam, Zakirullah; Samadzai, Abdul Wahid; Enayat, Wahidullah; Quraishi, Tamanna; Fazil, Abdul Wajid
Jurnal Ilmiah Telsinas Vol 8 No 1 (2025)
Publisher : Universitas Pendidikan Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38043/telsinas.v8i1.6242

Abstract

Generative AI for IoT Hydroponics Monitoring System for Smallholder Farmers in Developing Regions This is in an effort to support AI-based narrative feedback for real-time decision-making with reference to sensor data (TDS/EC, temperature) and plant context-the pertinent data are species and age. The system, therefore, consists of an ESP32 sensor device; a Flutter mobile application; and the cloud services being offered via Thingsboard and the Gemini API. A systematic approach was undertaken, including design, implementation, integration, and usability testing. The results show effective real-time data collection and secure communication, with accurate AI feedback validated by expert judgment. The results exhibited how AI and IoT could collude in aiding smart agriculture. Future work will concentrate on enhancing the accuracy of the model based on ground truth data and improving the accessibility of the platform.