Enhanced Elliptic Curve- Diffie Hellman Technique with Bigdata Analytics for Satellite Image Security Enhancement in Internet of Things Systems

With the emergence of cloud eco-system and technologies like Internet of Things (IoT), bit data analytics became essential to reap benefits of maintaining large volumes of data. As there is amalgamation of different devices, protocols, standard and use cases linked to IoT, there is increasing risk of security. IoT applications are vulnerable due to lack of security standards at global level. There is need for continuous efforts to provide end-to-end security in IoT applications. Sensor networks associated with IoT are resource constrained but produce large volumes of data or big data. In such environment, more light weight security primitives. Elliptic Curve Diffie Hellman (ECDH) is one such lightweight scheme for secure key exchange among connected devices. Nevertheless, ECDH is found vulnerable to attacks. To address this problem, we proposed a scheme known as E-ECDH (ECDH+SIGH) which is an enhanced version of ECDH. Our scheme is designed to enhance security level in IoT use cases. To evaluate our scheme, we used an IoT use case meant for anomaly detection in healthcare context. This application is in distributed environment where cloud infrastructure, IoT platform and Message Queue Telemetry Transport (MQTT) protocol are involved. Our experimental study showed that E-ECDH improves level of security in given IoT application and found to be better than existing security schemes.