The cyber risks of automated delivery

Once the stuff of science fiction, automated delivery is now a daily reality, transforming logistics at a remarkable speed. Drones, autonomous vans, and sidewalk robots are no longer futuristic experiments but practical tools reshaping how goods arrive at customers’ doors. These innovations promise greater efficiency, improved safety, and unmatched convenience, especially in solving the costly and complex “last-mile” delivery challenge.

Yet this transformation comes with a paradox. The same digital systems that make automated delivery possible also expose it to serious cybersecurity risks. To protect this vital part of modern e-commerce, organizations must pair innovation with robust security measures.

The increasing prevalence of automated delivery

The use of autonomous vehicles for deliveries is increasing globally, following successful trials in several regions.

Drone delivery expansion

The commercial drone delivery sector is experiencing explosive growth in 2025. The delivery drones market is currently valued at $1.08 billion and is forecasted to reach $4.4 billion by 2030. The growth reflects rapid regulatory liberalization, expanding beyond-visual-line-of-sight (BVLOS) approvals, and growing consumer demand for efficient delivery services. Physical deployment is accelerating rapidly, with the volume of package delivery drones projected to grow from 32,456 units in 2024 to 275,703 units by 2030.

Major corporations are leading this transformation through extensive trial programs. Amazon’s drone delivery initiatives, authorized by the Federal Aviation Administration (FAA), exemplify the corporate commitment to making automated delivery ubiquitous. 

Autonomous vehicle integration

Self-driving cars, autonomous delivery vans, and robotic delivery systems are rapidly transitioning from conceptual designs to practical implementations. Autonomous vehicles operate by synthesizing sophisticated technologies, including sensors, cameras, GPS, radar, light imaging detection and ranging (LiDAR), and advanced computing systems. Their ability to communicate with each other and the surrounding infrastructure creates an interconnected ecosystem that enhances operational efficiency.

The role of autonomous vehicles in last-mile delivery encompasses various forms, from large autonomous vans handling neighborhood routes to small sidewalk robots delivering individual packages directly to customers’ doors. This final stretch represents the most expensive and critical phase of delivery logistics, where automation offers the greatest potential for cost reduction and efficiency improvement.

Impact on logistics and e-commerce

Automated delivery systems offer unprecedented speed and efficiency, fundamentally redefining traditional delivery concepts. These technologies enable companies to reduce delivery times, lower operational costs, and provide more flexible service options to customers.

However, the extensive reliance on Internet connectivity and complex digital systems makes these devices inherently vulnerable to cyberattacks. The interconnected nature of automated delivery networks creates multiple entry points for potential security breaches, making cybersecurity a paramount concern for companies deploying these technologies.

Cyberthreats to automated delivery systems

Like any device connected to the Internet, autonomous vehicles are susceptible to cyber threats.

Inherent vulnerabilities and risks

The interconnected nature of automated delivery systems creates numerous cybersecurity risks spanning complex software networks, hardware components, and communication systems. As with all networked computing devices, increased connectivity often results in a heightened risk of cyberattack, with increased automation exacerbating any risk by increasing opportunities for adversaries to implement successful attacks.

Major threats to autonomous vehicles include remote hacking, sensor manipulation, data breaches, and denial-of-service (DoS) attacks. Cyberattacks targeting automated delivery systems pose substantial financial risks in commercial environments due to potential property damage and service disruption.

Key cyberattack vectors

• Connectivity and data exposure: While the ability of autonomous vehicles to share data enhances their functionality, it also opens up the possibility of cyberattacks, potentially leading to access to critical systems or the theft of sensitive information. Malicious actors can exploit connectivity features to gain access to operational intelligence, customer data, and delivery routes.
• Vehicle-to-Everything (V2X) communication manipulation: Future attacks on autonomous vehicles will increasingly target vehicle-to-everything (V2X) technology related to communication rather than other simpler elements of the vehicles. V2X communication protocols, including vehicle-to-vehicle (V2V), vehicle-to-infrastructure (V2I), and vehicle-to-pedestrian (V2P) communications, are crucial for ensuring safety and efficiency. However, attackers can exploit these channels to cause accidents, create congestion, or disrupt operations.
• Software and firmware exploitation: Complex software systems governing autonomous vehicles and drones can harbor bugs or vulnerabilities that hackers exploit to take control of vehicles, disrupt operations, modify AI algorithms, or deviate from programmed routes. There is significant risk to public safety, as hackers can hijack software vulnerabilities and access unauthorised vehicle systems to alter critical functions.
• Physical security and tampering: Beyond digital threats, autonomous delivery systems are vulnerable to physical tampering, where attackers can alter hardware components, such as sensors or cameras, to mislead vehicles about their surroundings, thereby increasing accident risks and compromising delivery security.
• AI decision-making risks: Automated delivery systems utilize AI for real-time decision-making. If attackers manipulate the data fed to AI systems, however, it could lead to unsafe or incorrect actions, such as misidentifying obstacles or selecting incorrect routes.
• Communication link vulnerabilities: The security of autonomous vehicles requires securing the communication between AI algorithms and sensors (such as LiDAR and radar), addressing both external threats (e.g., remote hacks) and internal threats (e.g., vulnerabilities within the vehicle’s own software or sensor systems). Unprotected communication links are susceptible to jamming or spoofing attacks.
• Supply chain vulnerabilities: Automated delivery systems rely on components and software from various manufacturers. A compromise at any point in the supply chain, such as a malicious software update from a third-party vendor, can introduce vulnerabilities into the entire fleet.

Cybersecurity solutions and best practices

Organizations must adopt a multifaceted approach to cybersecurity, viewing it as an integral aspect of every development step rather than an add-on feature. Implementing ‘secure by design’ principles ensures that hardware and software are built to be inherently less vulnerable from the ground up.

Embracing zero-trust architecture requires authentication and authorization for every digital interaction, regardless of the location within the network. Utilizing layered defense mechanisms creates a robust security posture that can withstand multiple attack vectors simultaneously.

Key technical solutions

• Strong encryption: Essential for securing data exchanged between vehicles, infrastructure, and cloud services, particularly in V2X communication. Public Key Infrastructure (PKI) ensures secure, authenticated, and encrypted communications. Quantum cryptography offers future-proof, theoretically unhackable security methods for highly sensitive operations.
• Secure software development and updates: Prioritizing secure coding practices minimizes software vulnerabilities from the development stage. Supporting secure over-the-air (OTA) updates enables prompt patching of discovered weaknesses. Implementing ‘cyber hardening’ by incorporating security considerations at each step of the development pipeline reduces attack surfaces.
• AI and machine learning model protection: Protecting AI systems from tampering and adversarial attacks that could manipulate input data is crucial for maintaining the operational integrity of these systems. This includes securing training data, implementing model validation protocols, and monitoring for unusual patterns of AI behavior.
• Intrusion detection and prevention systems (IDPS): Integrating IDPS enables continuous monitoring of suspicious activity and prevents unauthorized access attempts. Existing countermeasures include intrusion detection systems (IDSs) that implement real-time threat recognition systems enhanced by machine learning to improve detection accuracy and response times.
• Physical security enhancements: Employing biometric authentication, such as facial recognition and fingerprint scanning, ensures only authorized individuals can access and control devices. Using geofencing to set virtual geographical boundaries restricts drones and autonomous vehicles from high-risk areas.
• Redundancy systems: Implementing duplicate components ensures crucial control systems remain operational even if certain aspects are compromised. This approach involves isolating affected components for recovery while maintaining service continuity.

Operational and regulatory measures

• Incident response plans: Developing comprehensive incident response plans helps mitigate damage, reduce recovery time, and incorporate learnings from security breaches. Organizations must establish clear protocols for responding to various types of cyberattacks.
• Regulatory compliance: Adhering to cybersecurity standards, such as ISO 27001 and NIST guidelines, and data privacy regulations, including GDPR and CCPA, ensures baseline security requirements. Compliance with AI regulation policies related to transparency and accountability prevents unlawful operations.
• Human-centric training: Providing continuous training on cybersecurity best practices for all personnel involved in drone and autonomous vehicle operations raises overall security awareness and response capability across the organization.
• Collaboration: Fostering collaboration among technology companies, cybersecurity experts, and governmental bodies helps establish industry standards, share best practices, and evolve regulations in tandem with the emergence of new technologies.

Making automated delivery systems more secure

As automated delivery services continue to revolutionize commerce and logistics, robust cybersecurity becomes absolutely paramount for sustainable operations. Managing cyber threats requires a comprehensive, multifaceted approach that combines technical solutions, including secure communication protocols and regular software updates, with stringent regulatory adherence and continuous monitoring systems.

Ultimately, cybersecurity in automated delivery serves as the backbone of sustainable automation and a critical differentiator for companies competing in this dynamic sector. Organizations that prioritize security from design through deployment will be best positioned to capitalize on the tremendous opportunities while protecting their customers, assets, and reputation from growing cyber threats.