UWPEE: Using UAV and wavelet packet energy entropy to predict traffic-based attacks under limited communication, computing and caching for 6G wireless systems

The development of 6G has enhanced the communication capabilities of Internet of Things (IoT) devices. However, in wireless system, due to cost constraints, only a few devices have the communication capability of 6G, and the rest can only communicate with the Internet through self-organized networks. Due to simple hardware, these IoT devices have low capacities of communication, computing and caching. And they are vulnerable to all kinds of attacks. One of harmful attacks is traffic-based attack such as on–off attack, Denial of Service (DoS) attack which consumes the limited energy of IoT devices and wreaks havoc on data-based applications. However, there is no effective way to obtain the truth traffic of IoT devices, which makes it difficult for the cloud to secure the communication of IoT devices and manage the state of network. To ensure reliable communication, a novel approach to detect traffic-based attack by Unmanned Aerial Vehicle (UAV) and Wavelet Packet Energy Entropy (UWPEE) is proposed. In UWPEE scheme, UAV is sent to collect the truth traffic from IoT devices. Then wavelet packet energy entropy is innovatively adopted to detect attacks. Finally, the trust of IoT devices is determined according to their entropy. The experimental results show that UWPEE scheme can effectively identify traffic-based attacks with an accuracy rate of 84.47% and an average recognition efficiency of 4.89 for malicious nodes. Meanwhile, compared with the greedy algorithm, the flight path of the UAVs is reduced by 15.44%.