Recently, it has been proposed to deal with fusion of multi-object densities exploiting the minimum information loss (MIL) rule, which has shown its superiority over generalized covariance intersection (GCI) fusion whenever sensor nodes have low detection probability. On the contrary, GCI shows better performance than MIL when dense clutter is involved in the measurements. In this paper, we are going to study the behavior of multi-object fusion with MIL and, respectively, GCI rules in the situation wherein the sensor network is exposed to cyber-attacks. Both theoretical and numerical analyses demonstrate that MIL is more robust than GCI fusion when the multi-sensor system is subject to a packet substitution attack.
Resilience of multi-object density fusion against cyber-attacks / Lin Gao, Giorgio Battistelli, Luigi Chisci. - ELETTRONICO. - (2022), pp. 7-12. (Intervento presentato al convegno 11th International Conference on Control, Automation and Information Sciences, ICCAIS 2022 tenutosi a Hanoi, Vietnam nel 2022) [10.1109/ICCAIS56082.2022.9990117].
Resilience of multi-object density fusion against cyber-attacks
Lin Gao;Giorgio Battistelli;Luigi Chisci
2022
Abstract
Recently, it has been proposed to deal with fusion of multi-object densities exploiting the minimum information loss (MIL) rule, which has shown its superiority over generalized covariance intersection (GCI) fusion whenever sensor nodes have low detection probability. On the contrary, GCI shows better performance than MIL when dense clutter is involved in the measurements. In this paper, we are going to study the behavior of multi-object fusion with MIL and, respectively, GCI rules in the situation wherein the sensor network is exposed to cyber-attacks. Both theoretical and numerical analyses demonstrate that MIL is more robust than GCI fusion when the multi-sensor system is subject to a packet substitution attack.I documenti in FLORE sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.