Abstract
In today’s world m-Health (also termed as Mobile Health) is an integral part of the healthcare industry. M-health uses various kinds of mobile devices such as mobile phones, personal digital assistants, tablets, laptops, and wireless-based arrangements to collect and transfer run-time medical data between patients and healthcare institutions. The entire process of the m-healthcare system is dependent on a cloud system. As a result of services provided through the cloud platform, it is observed that network equipment is likely prone to different types of attacks in the system. The most extensively used of these attacks are Distributed Denial of Services (DDoS) attack which can halt the network service instantly and prevent the accessing of sensitive data. The attack can destroy the privacy and security of the data by injecting wrong information into it. The most crucial way in the battle against DDoS attacks is the fast detection and taking apart of network traffic. A novel DDoS detection algorithm is proposed for the early detection of the attack in the system. The DDoS preventive algorithms are designed efficiently to restrict the access of attackers in the system. Further, the effect of the different types of DDoS attacks with their preventive approach experimented in the cloud-based simulation environment. The maximum success of the attacker concerning time is also analyzed as a part of the research paper.
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Ray, S., Mishra, K.N. & Dutta, S. Detection and prevention of DDoS attacks on M-healthcare sensitive data: a novel approach. Int. j. inf. tecnol. 14, 1333–1341 (2022). https://doi.org/10.1007/s41870-022-00869-1
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DOI: https://doi.org/10.1007/s41870-022-00869-1