Spotting Cryptojacking in IoT: A Time Series and GNN Approach

Cryptojacking, the sneaky act of using other people's devices for mining cryptocurrency, is a big problem, especially in wireless sensor networks (WSN) and Internet of Things (IoT) devices. Researchers have found a smart way to fight this by combining time series analysis with graph neural networks (GNNs). This method helps predict and detect these attacks using a dataset called "Cryptojacking Attack Timeseries Dataset." The results are impressive, with models like ARIMA and GNN showing high accuracy. However, when combined, the ensemble method dropped a bit to 90. 97%. But don't worry, this approach makes the system more reliable and adaptable, which is crucial for spotting new attack trends in different network conditions. The research is a big step forward in making IoT and WSN safer from these sneaky miners.