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The integrity of global elections is increasingly under threat from artificial intelligence (AI) technologies. As AI continues to permeate various aspects of society, its influence on political processes and elections has become a critical area of concern. This is because AI language models are far from neutral or objective; they inherit biases from their training data and the individuals who design and utilize them, which can sway voter decisions and affect global elections and democracy. In this research paper, we explore how AI can directly impact election outcomes through various techniques. These include the use of generative AI for disseminating false political information, favoring certain parties over others, and creating fake narratives, content, images, videos, and voice clones to undermine opposition. We highlight how AI threats can influence voter behavior and election outcomes, focusing on critical areas, including political polarization, deepfakes, disinformation, propaganda, and biased campaigns. In response to these challenges, we propose a Blockchain-based Deepfake Authenticity Verification Framework (B-DAVF) designed to detect and authenticate deepfake content in real time. It leverages the transparency of blockchain technology to reinforce electoral integrity. Finally, we also propose comprehensive countermeasures, including enhanced legislation, technological solutions, and public education initiatives, to mitigate the risks associated with AI in electoral contexts, proactively safeguard democracy, and promote fair elections.
The integrity of global elections is increasingly under threat from artificial intelligence (AI) technologies. As AI continues to permeate various aspects of society, its influence on political processes and elections has become a critical area of concern. This is because AI language models are far from neutral or objective; they inherit biases from their training data and the individuals who design and utilize them, which can sway voter decisions and affect global elections and democracy. In this research paper, we explore how AI can directly impact election outcomes through various techniques. These include the use of generative AI for disseminating false political information, favoring certain parties over others, and creating fake narratives, content, images, videos, and voice clones to undermine opposition. We highlight how AI threats can influence voter behavior and election outcomes, focusing on critical areas, including political polarization, deepfakes, disinformation, propaganda, and biased campaigns. In response to these challenges, we propose a Blockchain-based Deepfake Authenticity Verification Framework (B-DAVF) designed to detect and authenticate deepfake content in real time. It leverages the transparency of blockchain technology to reinforce electoral integrity. Finally, we also propose comprehensive countermeasures, including enhanced legislation, technological solutions, and public education initiatives, to mitigate the risks associated with AI in electoral contexts, proactively safeguard democracy, and promote fair elections.
Modern organizations have migrated from localized physical offices to work-from-home environments. This surge in remote work culture has exponentially increased the demand for and usage of Virtual Private Networks (VPNs), which permit remote employees to access corporate offices effectively. However, the technology raises concerns, including security threats, latency, throughput, and scalability, among others. These newer-generation threats are more complex and frequent, which makes the legacy approach to security ineffective. This research paper gives an overview of contemporary technologies used across enterprises, including the VPNs, Zero Trust Network Access (ZTNA), proxy servers, Secure Shell (SSH) tunnels, the software-defined wide area network (SD-WAN), and Secure Access Service Edge (SASE). This paper also presents a comprehensive cybersecurity framework named Zero Trust VPN (ZT-VPN), which is a VPN solution based on Zero Trust principles. The proposed framework aims to enhance IT security and privacy for modern enterprises in remote work environments and address concerns of latency, throughput, scalability, and security. Finally, this paper demonstrates the effectiveness of the proposed framework in various enterprise scenarios, highlighting its ability to prevent data leaks, manage access permissions, and provide seamless security transitions. The findings underscore the importance of adopting ZT-VPN to fortify cybersecurity frameworks, offering an effective protection tool against contemporary cyber threats. This research serves as a valuable reference for organizations aiming to enhance their security posture in an increasingly hostile threat landscape.
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