Preserving Data Confidentiality in Internet of Things

The Internet of Things (IoT) is a network of linked physical objects worldwide, communicating via the Internet to one another. IoT expects the interconnection between a few trillions of intelligent things and the collected information offers a lot of private information needs to be analyzed and transmitted. So the provision of security to the information is a major challenge for many current and future applications of IoT. Basically, the main components of IoTs are Smartphone, Wireless Sensor Networks (WSNs), Radio Frequency Identification (RFID), etc. The design and implementation of security and privacy management system for these things are driven by considerations such as good performance, information tampering, low power consumption, threat robustness and an end to end security. Security systems in IoT offer unauthorized access to information or other things by providing protection against modification or damage. In this paper, we propose a hybrid algorithm designed to preserve data confidentiality in IoT. Proposed algorithm design is a combination of Message Digest algorithm (MD5), Elliptic Curve Cryptography (ECC) and Advanced Encryption Standard (AES) algorithms. The hybrid algorithm uses the concept of sharing geotag by destination IoT node to source node. Encryption involves three phases: Generation of fixed-length hash value i.e., hash function, encryption, and key generation. MD5 hash algorithm accepts plain text at the source IoT node as input and returns output a fixed length digest value. This value is encrypted using AES algorithm. Then ECC algorithm is applied to generate the encryption key. ECC offers a small key size and secured as compared to conventional cryptographic algorithms. We have simulated and analyzed the performance metrics of the proposed hybrid algorithm in terms of encryption time, memory utilization, end to end delay and decryption time w.r.t. varying file sizes as compared to AES encryption algorithm.