The Internet of Things (IoT) is an innovative trend that promotes technological and industrial advancements. As IoT networks expand, RPL (Routing Protocol for Low-Power and Lossy Networks) becomes crucial for efficient routing but is susceptible to a number of security threats and attacks. The DIS (DODAG Information Solicitation) flooding attack is one such attack that compromises network performance. This paper introduces DISTec, a novel technique designed to detect and mitigate DIS flooding attacks in RPL-based IoT networks. DISTec employs an n x m matrix to track DIS message frequencies from nodes, analyzing deviations during the DIS_INTERVAL to identify potential attackers. The Contiki OS Cooja Simulator implemented DISTec on a network consisting of 51 legitimate nodes and one malicious node. DISTec demonstrated a detection accuracy of 98.48%. It effectively isolates attackers by discarding their malicious messages and excluding them from the DODAG, thus enhancing network stability and performance. This research highlights DISTec’s effectiveness in maintaining network integrity and reducing the impact of flooding attacks. Future work will explore additional RPL attack scenarios and integrate AI-driven techniques to further improve attack detection and network security.