High and con­stantly gro­wing data volu­mes slow down com­mu­ni­ca­tion in the Inter­net of Things (IoT). Decen­tra­li­zed orga­niza­tio­nal and archi­tec­tu­ral approa­ches for com­mu­ni­ca­tion net­works, such as edge com­pu­ting, which pro­cess data in geo­gra­phi­cal pro­xi­mity to its source or desti­na­tion, pro­mise effi­ci­ent band­width uti­liza­tion and real-time pro­ces­sing. These effi­ci­ency gains through edge com­pu­ting are also being exploi­ted in sen­si­tive and incre­asingly secu­rity-cri­ti­cal areas of appli­ca­tion, such as energy gene­ra­tion. The chall­enge here is to pro­tect the hard­ware and ser­vices used in often hete­ro­ge­neous ope­ra­ting envi­ron­ments against cyber­at­tacks. Stan­dards, pro­ces­ses, and ser­vices used in con­ven­tio­nal data cen­ters are the­r­e­fore not suitable.

The aim of the pro­ject “Cyber-phy­si­cal secu­rity using radio­me­try for the edge” (C‑ray4edge) is to deve­lop a tech­ni­cal frame­work to secure the ope­ra­tion of edge com­pu­ting. The “nor­mal ope­ra­tion” of a net­work node is recor­ded as a pro­file of its elec­tro­ma­gne­tic radia­tion. A com­pa­ri­son of pro­files at dif­fe­rent points in time is used to detect hard­ware mani­pu­la­tion. A cen­tral loca­tion can thus moni­tor a large num­ber of net­work nodes based on the pro­files crea­ted. This moni­to­ring is sup­ple­men­ted by iden­tity veri­fi­ca­ti­ons, known as trust anchors, in the hard­ware. Grea­ter sys­tem relia­bi­lity is also to be achie­ved through the deve­lo­p­ment of self-moni­to­ring and impro­ved resource management.