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‘Curse of Dimensionality’ and the trade-off between high detection rate and less false alarm rate make the design of an efficient and robust Intrusion Detection System, an open research challenge. In this way, we present Hyper Clique—Improved Binary Gravitational Search Algorithm based Support Vector Machine (HC-IBGSA SVM), an efficient and adaptive intrusion detection technique to improve the performance of SVM in terms of detection rate and false alarm rate. HC-IBGSA SVM employs hyper clique property of hypergraph, novel mutation operator, and Newton–Raphson inspired position update function to fasten the search for an optimal solution and to prevent premature convergence. Further, HC-IBGSA uses a weighted objective function to maintain the trade-off between maximizing detection rate and minimizing the false alarm rate and the optimal number of features. The experimental evaluations were …