Al Waro'i, Muhammad Nur Abdul Latif
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Enhancing Security through Intelligent Threat Detection and Response: The Integration of Artificial Intelligence in Cyber-Physical Systems Al Waro'i, Muhammad Nur Abdul Latif
Security Intelligence Terrorism Journal (SITJ) Vol. 1 No. 1 (2024)
Publisher : Pusat Studi Politik dan Kebijakan Strategis Indonesia (POLKASI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70710/sitj.v1i1.1

Abstract

Cyber-Physical Systems (CPS) play a crucial role in critical industries such as manufacturing, transportation, energy, and healthcare by integrating the physical and digital worlds. However, the complexity and interconnectivity of CPS with the global network increase their vulnerability to cyber-attacks. This research explores the benefits of implementing artificial intelligence (AI) in the context of cyber-physical systems (CPS) to detect and respond to security threats. This study uses machine learning and deep learning techniques to analyze sensor data and system threats. The data analysis methods encompass predictive modeling and evaluating AI algorithms' performance in detecting threats. The research data is obtained from relevant literature reviews and secondary data analysis. The research findings indicate that integrating AI in CPS can enhance the success rate of threat detection, prompt response, and accuracy in threat identification. By enabling the system to learn from previous experiences, AI can reduce the number of false positives and false negatives while providing automated real-time responses to threats without human intervention. The research concludes that AI has great potential to enhance security in CPS by providing more efficient and effective solutions to address increasingly complex cyber threats. The findings of this study are expected to provide insights and recommendations that can be applied in developing CPS security systems in the future.
False Reality: Deepfakes in Terrorist Propaganda and Recruitment Al Waro'i, Muhammad Nur Abdul Latif
Security Intelligence Terrorism Journal (SITJ) Vol. 1 No. 1 (2024)
Publisher : Pusat Studi Politik dan Kebijakan Strategis Indonesia (POLKASI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70710/sitj.v1i1.5

Abstract

Deepfake technology, which leverages artificial intelligence to create hyper-realistic digital fabrications, has emerged as a significant threat across various domains, notably in terrorism. This review critically examines the exploitation of deepfakes in terrorist propaganda and recruitment, presenting a systematic analysis of the technical mechanisms behind their creation and detection, historical and contemporary propaganda methods, and their psychological impacts on audiences. The study identifies key advancements in deepfake detection technologies, such as ensemble learning and convolutional neural networks, which are crucial in distinguishing real from synthetic media. Furthermore, the review highlights the importance of public awareness and psychological resilience as vital countermeasures against deepfake manipulation. Despite technological advancements, significant challenges remain, including the development of real-time detection systems capable of operating in diverse and uncontrolled environments and a comprehensive understanding of the psychological processes affected by deepfake propaganda. The review underscores the urgent need for robust policy frameworks and international cooperation to address the ethical, legal, and security implications of deepfake technology. By integrating technical, psychological, and policy perspectives, this study provides a holistic understanding of deepfake technology's role in modern terrorism and offers insights for developing effective countermeasures. The comprehensive approach aims to contribute to the creation of robust strategies to mitigate the misuse of deepfake technology, ensuring a safer and more trustworthy digital environment.