An architecture for confidentiality self-management in the Internet of Things

With the growth of the IoT ecosystem, IoT data confidentiality is becoming a critical issue, posing various concerns for customers. Using cryptographic methods to ensure data confidentiality is one of the most common ways for mitigating data confidentiality attacks. Since traditional encryption approaches need important CPU and memory capacity as well as increasing time and energy consumption, researchers have developed a variety of lightweight cryptographic algorithms to provide IoT environments with solutions that take into consideration IoT resources limitations while offering adapted security level. Managing lightweight cryptographic features in an IoT ecosystem is extremely difficult due to the large number of objects, the nature of IoT devices that do not accept the implementation of all possible lightweight solutions, the heterogeneity of the captured data, and the energy required for these lightweight solutions. To address this problem, we propose a novel IoT framework in which lightweight cryptographic features are self-managed according to the Autonomic Computing paradigm in order to ensure IoT data confidentiality while enhancing IoT system performance and extending IoT device lifetime.