More and more digitized techniques and network connectivity are deployed to advanced manufacturing to enable remote system monitoring and automated production; however, this trend also leads to the traditional assumption of security in manufacturing not holding true any longer. For instance, the option of remote access makes advanced manufacturing infrastructures vulnerable to various security attacks from physical devices to cyberspace. Existing literature that addresses the attacks in advanced manufacturing is mainly at the network level. In this work, we study the role of hardware security in the process of advanced manufacturing. More specifically, our analysis focuses on the security vulnerability of sensors, local data processing nodes, and the interface implementation for standardized communication protocols. Unique attack examples such as hardware Trojan, interface sniffing, and fraudulent data injection attacks are provided in this work to highlight the unique challenges of attack detection and mitigation in advanced manufacturing.

Satellite has become an elementary contrivance for contemporary communication system. For the limitation to access and costly affair in the real satellite, a can sized satellite can be built which consists of all the real systems of a space satellite. In this work, a complete design and mechanism of a CanSat from assembling the payload to development of ground station has been proposed. Moreover, abiding by the design rules of building parachute, a parachute is developed for the drop test, which has been done successfully with all the sensors transmitting their corresponding data to a customized ground station. Additionally, a special approach is also contemplated and examined known as comeback mission of the CanSat by which the CanSat can be returned to the ground station automatically using Haversine rule of distance and heading. A custom ground station has actually been designed which has connection with the server and it automatically generates a CSV (Comma Separated Value) file for post processing of the data. Our results exhibit that proposed method can be a reliable solution of CanSat comeback mission and it also paves the way of making the system more immaculate by real data simulation.

Real-time health monitoring systems generate a large volume of sensing data, requiring tremendous processing time and storage space. Orthogonal to existing approximate computing mechanisms, this work proposes a Feature-Driven Approximation (FDApx) method to address the pressing need for fast data processing and a limited storage budget in wearable health monitoring devices. The proposed FDApx method reverses the features interested in high-level applications to derive approximation thresholds to retain feature-critical information, rather than aimlessly storing and transmitting all raw data. Case studies in an insole sensing system for fall risk assessment show that FDApx can reduce the data size by up to 87% over raw data and up to 85% over 2-bit precision reduction-based approximation. The approximation from FDApx only results in up to a 2% deviation in swing time; in contrast, the approximation based on precision reduction causes a 30% deviation in the same gait feature1.

Multi-tenant Field-Programmable Gate Arrays (FPGAs) are vulnerable to voltage-drop attacks, which could jeopardize the safety and reliability of FPGA utilization. Existing countermeasures deploy numerous sensors to detect fault attacks and mitigate attacks by sacrificing other FPGA tenants’ normal operations. To address those limitations, we propose an accumulated Hamming distance-based local attack mitigation (AHDLAM) method to precisely pinpoint attack locations with a new assessment metric and multi-stage localization process. Furthermore, a dynamic partial reconfiguration-based attack mitigation technique is proposed to reduce the cost of eliminating malicious FPGA logic. Experimental results show that our method reduces the number of on-chip sensors by 92.7% and lowers the attack mitigation granularity by up to 87.5%, compared to existing works. The partial reconfiguration technique reduces the attack mitigation time by 78% than the baseline.

Temperature sensors play an important role in modern monitoring and control applications. When more and more sensors are integrated into internet-connected systems, the integrity and security of sensors become a concern and cannot be ignored anymore. As sensors are typically low-end devices, there is no built-in defense mechanism in sensors. It is common that system-level defense provides protection against security threats on sensors. Unfortunately, high-level countermeasures do not differentiate the root of cause and treat all anomalies with system-level recovery processes, resulting in high-cost overhead on delay and power consumption. In this work, we propose a secure architecture for temperature sensors with a transducer and a signal conditioning unit. The proposed architecture estimates the sensor data with statistical analysis and generates a residual signal for anomaly detection at the signal conditioning unit. Moreover, complementary current–temperature characteristics are exploited to generate a constant current reference for attack detection at the transducer level. Anomaly detection at the signal conditioning unit and attack detection at the transducer unit make the temperature sensor attack resilient to intentional and unintentional attacks. Simulation results show that our sensor is capable of detecting an under-powering attack and analog Trojan from a significant signal vibration in the constant current reference. Furthermore, the anomaly detection unit detects anomalies at the signal conditioning level from the generated residual signal. The proposed detection system is resilient against any intentional and unintentional attacks, with a detection rate of 97.73%.

In-Sensor Computing (ISC) systems emerge as a promising alternative to save energy on massive data transmission, analog-to-digital conversion, and ineffective processing. While the new paradigm shift of ISC systems gains increasing attention, the highly compacted systems could incur new challenges from a hardware security perspective. This work conducts a literature review to highlight the research trend of this topic and then performs comprehensive analyses on the root of security challenges. To the best of our knowledge, this is the first work that compares the security challenges of traditional sensor-involved computing systems and emerging ISC systems. We conduct a comprehensive analysis of ISC’s design phases to identify significant vulnerabilities and attack surfaces. Furthermore, new attack scenarios are predicted for board-, chip-, and device-level ISC systems. Three proof-of-concept demos are provided to reveal the consequences of the attacks for three different levels. Our findings emphasize the urgent necessity for sophisticated defense mechanisms and inspire researchers to work on new countermeasure designs against unique hardware security threats in ISC systems.