Bio-Inspired Approaches to Safety and Security in IoT-Enabled Cyber-Physical Systems

Abstract

Internet of Things (IoT) and Cyber-Physical Systems (CPS) have profoundly influenced the way individuals and enterprises interact with the world. Although attacks on IoT devices are becoming more commonplace, security metrics often focus on software, network, and cloud security. For CPS systems employed in IoT applications, the implementation of hardware security is crucial. The identity of electronic circuits measured in terms of device parameters serves as a fingerprint. Estimating the parameters of this fingerprint assists the identification and prevention of Trojan attacks in a CPS. We demonstrate a bio-inspired approach for hardware Trojan detection using unsupervised learning methods. The bio-inspired principles of pattern identification use a Spiking Neural Network (SNN), and glial cells form the basis of this work. When hardware device parameters are in an acceptable range, the design produces a stable firing pattern. When unbalanced, the firing rate reduces to zero, indicating the presence of a Trojan. This network is tunable to accommodate natural variations in device parameters and to avoid false triggering of Trojan alerts. The tolerance is tuned using bio-inspired principles for various security requirements, such as forming high-alert systems for safety-critical missions. The Trojan detection circuit is resilient to a range of faults and attacks, both intentional and unintentional. Also, we devise a design-for-trust architecture by developing a bio-inspired device-locking mechanism. The proposed architecture is implemented on a Xilinx Artix-7 Field Programmable Gate Array (FPGA) device. Results demonstrate the suitability of the proposal for resource-constrained environments with minimal hardware and power dissipation profiles. The design is tested with a wide range of device parameters to demonstrate the effectiveness of Trojan detection. This work serves as a new approach to enable secure CPSs and to employ bio-inspired unsupervised machine intelligence.

Intrusion detection method for internet of things based on the spiking neural network and decision tree method

“…The SNN has been utilized by IDS to detect attacks on IoT devices by researchers due to its usage of less energy and achieving minimum latency in comparison with DNN. For instance, Johnson et al [28] used SNN and "glial cell" to detect the Trojan attack via using agreeable firing or "spiking rate" on IoT hardware devices. So, when the spiking rate value is not in the acceptable range that means the Trojan detection of the IoT device otherwise, no attack is identified in the IoT device.…”

Bio-Inspired Internet of Things: Current Status, Benefits, Challenges, and Future Directions

“…The proliferation of Information and Communication Technologies (ICTs) early in the 21st century has led to a revolution in our daily lives in which we are able to perform many tasks that were considered difficult with the use of available technologies at that time [ 1 ]. Progressively, this ICT has given birth to many advanced technologies, of which IoT can be considered as one such major technology [ 2 , 3 , 4 , 5 ]. Over the years, this IoT has been affiliated with many of the domains that are deemed important for human survival, such as agriculture, manufacturing, transportation, and healthcare [ 6 , 7 , 8 , 9 ].…”

“…Overall, the IoT is an ecosystem of connected devices that communicate with each other and exchange data. The integration of the IoT and the worldwide web has led to the creation of new kinds of services and applications in different domains, such as real-time surveillance, plant disease diagnosis, remote healthcare, real-time disease diagnosis, precision agriculture, air quality monitoring, and so on [ 1 , 2 , 3 , 4 , 5 , 12 , 13 , 14 , 15 , 16 ]. In general, IoT facilitates us to connect our digital belongings to the worldwide web, anytime, anywhere in the world [ 17 , 18 , 19 , 20 , 21 ], as depicted in Figure 1 .…”

“…Connecting and coordinating a large number of devices, managing data flows, and ensuring efficient data processing and analysis require robust systems and architectures. Thus, scaling up IoT deployments can be challenging, particularly when dealing with legacy systems and integrating with existing IT infrastructure [ 3 ].…”

“…In general, these bio-inspired solutions, also known as biomimetic or nature-inspired solutions, refer to the development of technologies, strategies, and designs that draw inspiration from biological systems found in nature [ 3 , 4 ]. These solutions aim to solve complex problems by emulating or adapting principles, structures, processes, and behaviors observed in living organisms.…”