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Modern building control systems adopt demand control heating, ventilation,and cooling (HVAC) for increased energy efficiency. The integration of theInternet of Things (IoT) in the building control system can determine real-timedemand, which has made the buildings smarter, reliable, and efficient. Asoccupants in a building are the main source of continuous heat and $CO_2$generation, estimating the accurate number of people in real-time usingbuilding IoT (BIoT) system facilities is essential for optimal energyconsumption and occupants' comfort. However, the incorporation of less securedIoT sensor nodes and open communication network in the building control systemeventually increases the number of vulnerable points to be compromised.Exploiting these vulnerabilities, attackers can manipulate the controller withfalse sensor measurements and disrupt the system's consistency. The attackerswith the knowledge of overall system topology and control logics can launchattacks without alarming the system. This paper proposes a building internet ofthings analyzer (BIoTA)framework\footnote{https://github.com/imtiazulhaque/research-implementations/tree/main/biota}that assesses the smart building HVAC control system's security using formalattack modeling. We evaluate the proposed attack analyzer's effectiveness onthe commercial occupancy dataset (COD) and the KTH live-in lab dataset. To thebest of our knowledge, this is the first research attempt to formally model aBIoT-based HVAC control system and perform an attack analysis.

BIoTA Control-Aware Attack Analytics for Building Internet of Things