xchange keys with every access point as they hand over which could be an overhead on both the network and the device. 7.5.3.3 Security Challenge Although blockchain boosts the security of MEC networks, they are not immune to attacks by quantum computers. Current cryptography methods used in blockchain are easily breakable by quantum computing. Quantum key distribution methods can be used to improve the resistance to quantum computing attacks. As an open system, MEC is vulnerable to distributed denial-of-service (DDoS) attacks. Blockchain cannot provide immunity to such types of attack. DDoS attacks overload the MEC servers and decrease the probability of satisfying the QoS of customers. Orchestrators should be provided with AI algorithms to predict DDoS attacks and detect malicious users to deny their access to the resources. RESEARCH OPPORTUNITIES: BLOCKCHAIN AND EDGE COMPUTING IN HEALTHCARE 7.6.1 ENSEMBLE LEARNING AND BLOCKCHAIN FOR DECISION-MAKING Ensemble learning combines predictions from different machine learning to get more accurate results. Ensemble learning has proved to have a superior performance in various fields, including healthcare [31]. Edge could use predictions from end devices and sensor analytics in an ensemble model to send a more reliable diagnosis to the cloud and decrease the chances of sounding false alarms. A more interesting scenario is an emergency response in a smart city where the protocol followed is decided by information from hospitals, environment or factory sensors, wearables, and police. Each entity may send its data on a different MEC server, and data shared across these entities is restricted to protecting each entity's privacy. Decisions can be made by the MEC server using ensemble learning on predictions and information sent from each entity. Therefore, actions are taken autonomously without the need to share data across entities. In their current form, blockchain can record transactions that all nodes can verify. This model is suitable for asset exchange but not for decis