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The proliferation of application specific cyber-physical systems coupled withthe emergence of a variety of attacks on such systems (malware such as Miraiand Hajime) underlines the need to secure such networks. Most existing securityefforts have focused on only detection of the presence of malware. Howevergiven the ability of most attacks to spread through the network once theyinfect a few devices, it is important to contain the spread of a virus and atthe same time systematically cleanse the impacted nodes using the communicationcapabilities of the network. Toward this end, we present Airmed - a method andsystem to not just detect corruption of the application software on a IoT node,but to self correct itself using its neighbors. Airmed's decentralizedmechanisms prevent the spread of self-propagating malware and can also be usedas a technique for updating application code on such IoT devices. Among thenovelties of Airmed are a novel bloom-filter technique along with hardwaresupport to identify position of the malware program from the benign applicationcode, an adaptive self-check for computational efficiency, and a uniformrandom-backoff and stream signatures for secure and bandwidth efficient codeexchange to correct corrupted devices. We assess the performance of Airmed,using the embedded systems security architecture of TrustLite in the OMNeT++simulator. The results show that Airmed scales up to thousands of devices,ensures guaranteed update of the entire network, and can recover 95% of thenodes in 10 minutes in both internal and external propagation models. Moreover,we evaluate memory and communication costs and show that Airmed is efficientand incurs very low overhead.

Airmed: Efficient Self-Healing Network of Low-End Devices