Device implant attack detection for the Smart Grid Infrastructure

The Smart Grid Infrastructure (SGI) is a crucial platform for providing stakeholders of the the electricity grid with intelligent data for sustained and smooth operations. As with every emerging infrastructure, the effects of malicious attacks by the adversary class cannot be overlooked. More so if the extent of damage that may be caused through such attacks can affect large user bases of such technology. A typical SGI may consist of disparate and heterogeneous devices, cooperating and exchanging customer-specific data (readings), in hierarchical manner (from consumer devices to centralized servers through smart meters and data concentrators/aggregators). The interconnection of all such devices (both through wireless and wired channels) to the Internet, exposes the SGI to threats that do indeed exist, and have transpired into malicious attacks against critical information resources during the past two decades. One attack category that may be identified for the SGI is the device implant attack, wherein rogue devices may be installed within a consumer´s premises so as to report falsified readings to the smart meter. In this paper, a collaborative approach towards timely detection of such attacks through pattern reconstruction and verification is proposed. The scheme is capable of detecting anomalous readings within a consumer´s household, with minimal communication and processing overhead imposed.