Systems and associated methods for detecting a set of spectrum sensing falsification (SSF) attacks in a geographic database (GDB) driven cognitive radio (CR) system. Viewing the GDB as a type of non-orthogonal compressive sensing (CS) dictionary, the composite power spectral density (PSD) estimate at a candidate CR is approximated by a small number of sensor nodes listed in the GDB. In a dense CR network, the PSD estimate at a CR may contain a composite mixture of spectrally overlapping signals. An implementation of an optimized, greedy algorithm orthogonal matching pursuit (OMP) returns a set of sensor nodes which are suspected to be in the vicinity of the CR. A sufficient match between the PSD estimate reported by a candidate CR and the PSD that is sparsely approximated from the SNs in its area provides confidence (trust) metrics which may be used to detect potential SSF attacks.
Spectrum sensing falsification detection in dense cognitive radio networks