Mehmet Ufuk CaglayanÇağlayan, Mehmet Ufuk2025-10-0620222061-20792061-212510.36244/ICJ.2022.4.102-s2.0-85147091828http://dx.doi.org/10.36244/ICJ.2022.4.10https://gcris.yasar.edu.tr/handle/123456789/5908https://doi.org/10.36244/ICJ.2022.4.10This paper reviews research from several EU Projects that have addressed cybersecurity using techniques based on Machine Learning including the security of Mobile Networks and the Internet of Things (IoT). These research projects have considered IoT Gateways and their design security and performance the security of digital health systems that are interconnected across Europe to provide health services to pople who travel through the EU and related issues of the energy consumption and sustainability in Information and Communication Technologies (ICT) and their cybersecurity. The methods used in much of these research projects are based on Machine Learning both for attack detection and dynamic attack mitigation as well as performance analysis and measurement techniques based on applied probability models.Englishinfo:eu-repo/semantics/openAccessCybersecurity, Secure Mobile Networks, Machine Learning, IoT Gateways, Secure Health Informatics, Attack Detection, Cyber-Attack Mitigation, IoT Massive Access Problem, Adaptive Network Routing, ICT SustainabilityRANDOM NEURAL-NETWORK, SIGNALING STORMS, EHEALTH DATA, SECURITY, ATTACKS, PERFORMANCE, GREEN, QOSSecure Health InformaticsAttack DetectionIoT GatewaysCyber-Attack MitigationIoT Massive Access ProblemSecure Mobile NetworksICT SustainabilityMachine LearningCybersecurityAdaptive Network RoutingReview