Green security optimization using low-complexity clustering for cell-free network

Cell-free massive MIMO (CF-mMIMO) networks are notable for their flexibility, low deployment cost, and user-centric service model, making them highly suitable for emerging applications such as the Internet of things (IoT), vehicular networks, and robotic communications. However, these advantages also bring significant security challenges. In particular, the limited hardware capabilities and stringent power constraints of distributed access points (APs) hinder the implementation of complex security mechanisms, leaving the network vulnerable to eavesdropping attacks. This paper investigates physical-layer security (PLS) strategies to counter eavesdropping threats in CF networks, while jointly analyzing the impact of these strategies on energy consumption. To this end, we propose a green, low-complexity secure transmission framework based on dynamic AP clustering, aiming to maximize the secrecy energy efficiency (SEE) of the system. Monte Carlo simulations validate that the proposed method significantly improves the system SEE while ensuring all legitimate users maintain baseline secrecy rate even under eavesdropper threats.