Battery (sub)systems are used in many systems (systems-of-systems) in the Internet of Things (IoT) ranging from everyday ones (e.g., mobile systems, home appliances, etc.) to safety-critical and/or mission-critical ones (e.g., electrical vehicles, unmanned aerial vehicles, autonomous underwater vehicles, etc.). As these systems become more interconnected with each other and their environments and batteries become more energy dense, the safety risks of using batteries increase. To guarantee effectiveness and prevent potential safety threats (i.e., failure, overheating, explosion), it is not only crucial to ensure that batteries are functioning correctly (via safety circuits and battery management system), but to also prevent security threats that specifically target the battery system from different parts of these systems. A security analysis is necessary for system manufacturers and users to understand what threats and solutions exist for battery system security. In University of Florida, Gainesville, FL 32611, USA this paper, we present a security perspective on battery systems, where we use a layered approach to analyze vulnerabilities, threats, and potential effects. We divide the battery system into the Physical, Battery Management System, and Application layers and use mobile systems and cyber-physical systems as case studies for IoT applications. We then highlight and discuss some existing solutions and mention the potential research directions on battery system security.

The paper introduces a novel authentication scheme for Advanced Metering Infrastructure (AMI) of smart grid using Ring Oscillator Physically Unclonable Functions (ROPUFs). The scope of the design covers the communication between the utility company (UC) and the smart meter (SM) network. The scheme is based on hardware-oriented security and can be implemented on existing smart meters. Authentication keys of 64 bits are used for security level 1 (L1) communication. The size of keys can increase up to 1024 bits for security level 5 (L5). The cryptographic keys used in this scheme are extremely difficult to model by adversaries as each key is used only once. These authentication keys are generated from ROPUF response bits using the Hamming code. The design of the scheme ensures fault tolerance as Ring Oscillator (RO) comparison pairs with high frequency differences are selected to prevent bit flips and only 10% discrepancy is tolerated in parity bits. The proposed scheme is highly secure and efficient in terms of latency and data storage. As a proof of concept, two different machine learning algorithms, Support Vector Machine (SVM) and Multigene Genetic Programming (MGGP), are used to show that the scheme cannot be modeled by adversaries.

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