Autonomous vehicles (AVs) have revolutionized the automotive industry by leveraging data to perceive and interact with their environment effectively. Data safety is essential for supporting AV decision-making and ensuring reliability in complex environments. AVs continuously collect data from multiple sources like LiDAR, RADAR, cameras, and ultrasonic sensors to monitor road conditions, traffic signals, and pedestrian movements. An effective data classification framework is crucial for managing vast amounts of information and securing AV systems against cyber threats. This paper proposes a comprehensive framework for AV data classification, categorizing data by sensitivity, usage, and source. By integrating a review of the literature, real-world cases, and practical insights, this study introduces a novel data classification model and explores sensitivity criteria. The findings aim to assist industry stakeholders in creating secure, efficient, and sustainable AV ecosystems.

Managed Service Providers (MSPs) have increasingly become prime targets for cyberattacks due to their privileged access across multiple client environments. Utilizing a qualitative thematic synthesis and an Open-Source Intelligence (OSINT) methodology, this study examines a purposive sample of major MSP-targeted cyber incidents from 2020 to 2025 to identify common attack patterns, exploited vulnerabilities, and operational impacts on downstream clients, particularly small and medium-sized businesses. Analysis of publicly reported incidents reveals a clear trend toward attacks leveraging centralized management platforms, remote access tools, and multi-tenant architectures, resulting in cascading disruptions from limited initial compromise. The synthesis highlights extortion-driven ransomware, supply chain compromises, and the exploitation of unpatched edge devices as dominant threats. To counter these systemic risks, this study outlines contextualized mitigation strategies such as zero trust principles, strict identity controls, tenant isolation, and continuous monitoring tailored to balance security requirements with MSP operational constraints. While these strategies are evidence-informed and grounded in observed trends, they remain proposed solutions that require further empirical validation. The findings emphasize the critical need for proactive, collaborative security practices among MSPs, clients, and regulators to manage evolving cyber threats effectively.