Assessing Security Concerns for AI-Based Drones in Smart Cities

Introduction

AI-based drones are unmanned aerial vehicles (UAVs) that use artificial intelligence to enhance autonomy and perform complex tasks. These autonomous drones, equipped with AI algorithms, can adapt to changing environments without human intervention. The integration of AI-based drones in smart cities has the potential to revolutionize urban life, including surveillance, transportation, delivery services, and emergency response. These autonomous devices gather real-time data, analyze it, and make informed decisions, enabling efficient and proactive actions in urban environments(Do et al., 2021). AI-based drone deployment in smart cities raises security concerns due to sensitive data, cyber threats, physical safety risks, and ethical implications. This chapter provides a comprehensive understanding of security challenges and vulnerabilities, enabling the development of strategies and frameworks for evaluating and mitigating these concerns. This analysis contributes to the development of guidelines and best practices for stakeholders involved in deploying and managing AI-driven drone systems(Vashisth et al., 2021).

This chapter explores security concerns for AI-based drones in smart cities, including data privacy, cybersecurity, physical safety, and ethical implications. It proposes a framework for assessing and managing these issues, incorporating risk assessment methodologies and mitigation strategies. The chapter also presents case studies and best practices from real-world scenarios. Addressing security concerns with AI-based drones in smart cities is crucial for protecting personal privacy, preventing malicious activities, mitigating risks, and promoting ethical decision-making. This chapter is valuable for policymakers, urban planners, drone operators, and researchers seeking to harness the potential of AI-based drones while maintaining a secure and trustworthy urban environment. Smart cities aim to improve urban challenges and quality of life by addressing urban challenges. AI-based drones play a crucial role in urban planning, public safety, traffic management, and environmental monitoring. However, these advanced technologies raise security concerns that require careful evaluation and attention (Rawat et al., 2022). AI-based drones collect vast amounts of data, including sensitive information about individuals, activities, and surroundings. To maintain privacy rights and prevent harm, it is crucial to safeguard this data from unauthorized access, misuse, and breaches. Establishing robust protection mechanisms, encryption techniques, and compliance with privacy regulations are essential steps in addressing these concerns.

Cybersecurity risks are a significant concern in AI-based drones, as they are interconnected within smart city ecosystems. To mitigate these risks, securing communication channels, implementing strong authentication protocols, and regularly updating software and firmware are essential measures. Physical safety is crucial for preventing accidents and protecting both drones and citizens. Collision avoidance systems, advanced sensors, and integration with air traffic management systems can help mitigate mid-air collision risks and ensure safe operations (Alqurashi et al., 2022; Kumar & Mohanty, 2021). Establishing fail-safe mechanisms and emergency procedures minimizes system failures and enables timely response in critical situations. Ethical implications in AI-based drones are crucial, as they can impact societal values, individual rights, and fairness. Bias in AI algorithms can lead to discriminatory outcomes or profiling. Addressing these concerns requires transparency, accountability, and adherence to legal and ethical frameworks. A comprehensive framework for assessing and managing risks is essential, including risk assessment methodologies, vulnerability identification, impact evaluation, and mitigation strategies. This systematically evaluates and addresses security concerns, fostering a secure and trustworthy environment for AI-based drone operations in smart cities (Mohammed et al., 2014; Rawat et al., 2022).