Distributed Denial of Service (DDoS) attacks in Internet of Things (IoT) networks are the cyber attacks launched by an attacker using a set of compromised IoT devices, called zombies. The infected devices cause the depletion of either bandwidth or resources of the victim server. Detection of DDoS attacks is a crucial defence mechanism to achieve secure IoT applications and services. In this paper, we have developed a lightweight DDoS detection mechanism for IoT networks by employing the feature engineering on network traffic charac-teristics. Entropy of Packet size interval and Expectation of Packet Size are the major parameters for performing the binary classification of incoming IoT traffic into DDoS or legitimate. The experimental results have shown that the proposed mechanism works effectively for different packet rates when compared with state-of-art mechanisms.