# Security Implications for Ultra-Low Power Configurable SoC FPAA Embedded Systems
## 1 Security Implication of Sensor Nodes Empowered by SoC FPAA Devices  
Energy constrained IoT systems, such as wearable devices, are already sensor rich and processing/computation constrained. Many portable and wearable devices are constrained by their energy-efficiency. The digital energy efficiency wall [1] constrains the amount of signal processing possible at energy constrained nodes. One rarely has any computational resources left to consider network security, leaving devices exposed. Fortunately, many of these devices have infrequent wireless communication with very constrained command structures, but they still exhibit a system vulnerability, particularly when monitoring or controlling physical infrastructure. Cloud-based computing removes issues of real-time embedded (e.g., fixed point arithmetic) to be done on some far away (and supposedly free) server using MATLAB style coding. As these devices rarely have any local computation, they have capability available for range of security functions, similar to larger devices. The host system must constantly transmit and receive data to perform these computations. The network connectivity must have a minimum quality at all times otherwise performance noticeably drops. These devices require high levels of security as they are completely dependent on the network for their operation. The cloud computation still has energy and infrastructure costs somewhere. As a product scales to the consumer market, these assumption that cloud is nearly free as well as always accessible often breaks down. Physical computing approaches enable at least a factor of 1000 improvement in computational energy efficiency empowering a new generation of local computational structures for embedded IoT devices. Such approaches allow significant computation on these embedded platforms (Figure 0(a)), making them less dependent or nearly independent of network operation. Physical computing utilizes operations over continuous-value and/or continuous-time spaces. Analog computing enables bothimproved computational efficiency (speed and/or larger complexity) of 1000\(\times\) or more compared to digital solutions (as predicted by [2]), as well as potential improvements in area efficiency of 100\(\times\). Without using physical computation, the embedded processor and wireless transceiver energy constraints make the sensor node a simple, low-speed data acquisition node. Although ultra-low power Physical computing could have huge impacts for network of small autonomous sensor nodes (Figure 1b), these same ultra-low power physical-computing enabled nodes often require secure operation against attack (Figure 1d). Analog Computing has emerged through the innovation of the large-scale Field Programmable Analog Arrays (FPAA) devices (e.g., SoC FPAA [3]). Although FPAAs (Figure 1c) are a recent technology (e.g., [3]), widespread adoption of these devices eventually requires some level of security measures against malicious users. The following sections begin the discussion of security opportunities for, multiple vulnerabilities of (Figure 1d), and issues using, FPAA devices for small embedded IoT platforms. Security, and resulting privacy concerns [4], particularly as people believe they are being watched [5], are a fundamental concern of small, low-power ubiquitous computing nodes [6]. We start by reviewing FPAAs as physical computing devices for low-power embedded applications (Section 2). These FPAAs enable devices for low-power context-aware computation (Section 3), particularly in their utilization of communication, the typical path for insecure operation. The conversation moves to secure FPAA devices (Section 4), showing positive FPAA Security attributes (Section 4.1), and addressing FPAA  
Figure 1: Embedded configurable physical computation. Small sensor nodes require energy efficient computation, computation enabled through physical computing approaches, and yet still need to find a way to be secure.