Randomized encoding of combinational and sequential logic for resistance to hardware Trojans

Globalization of micro-chip fabrication has opened a new avenue of cyber-crime. It is now possible to insert hardware Trojans directly into a chip during the manufacturing process. These hardware Trojans are capable of destroying a chip, reducing performance or even capturing sensitive data. To date, defensive methods have focused on detection of the Trojan circuitry or prevention through design for security methods. This dissertation presents a shift away from prevention and detection to a design methodology wherein one no longer cares if a Trojan is present or not. The Randomized Encoding of Combinational Logic for Resistance to Data Leakage or RECORD process is presented in the first of three papers. This chip design process utilizes dual rail encoding and Quilt Packaging to create a secure combinational design that can resist data leakage even when the full design is known to an attacker. This is done with only a 2.28x-2.33 x area increase and 1.7x-2.24x increase in power. The second paper describes a new method, Sequential RECORD, which introduces additional randomness and moves to 3D split manufacturing to isolate the secure areas of the design. Sequential RECORD is shown to work with 3.75x area overhead and 4.5x power increase with a 3% reduction in slack. Finally, the RECORD concept is refined into a Time Division Multiplexed (TDM) version in the third paper, which reduces area and power overhead by 63% and 56% respectively. A method to safely utilize commercial chips based on the TDM RECORD concept is also demonstrated. This method allows the commercial chip to be operated safely without modification at the cost of latency, which increases by 3.9x --Abstract, page iv

Combating Data Leakage Trojans in Commercial and ASIC Applications with Time-Division Multiplexing and Random Encoding

Globalization of microchip fabrication opens the possibility for an attacker to insert hardware Trojans into a chip during the manufacturing process. While most defensive methods focus on detection or prevention, a recent method, called Randomized Encoding of Combinational Logic for Resistance to Data Leakage (RECORD), uses data randomization to prevent hardware Trojans from leaking meaningful information even when the entire design is known to the attacker. Both RECORD and its sequential variant require significant area and power overhead. In this paper, a Time-Division Multiplexed version of the RECORD design process is proposed which reduces area overhead by 63% and power by 56%. This time-division multiplexing (TDM) concept is further refined to allow commercial off the shelf (COTS) products and IP cores to be safely operated from a separate chip. These new methods tradeoff latency (5.3x for TDM and 3.9x for COTS) and energy use to accomplish area and power savings and achieve greater security than the original RECORD process

Real-Time Sensor Networks and Systems for the Industrial IoT

The Industrial Internet of Things (Industrial IoT—IIoT) has emerged as the core construct behind the various cyber-physical systems constituting a principal dimension of the fourth Industrial Revolution. While initially born as the concept behind specific industrial applications of generic IoT technologies, for the optimization of operational efficiency in automation and control, it quickly enabled the achievement of the total convergence of Operational (OT) and Information Technologies (IT). The IIoT has now surpassed the traditional borders of automation and control functions in the process and manufacturing industry, shifting towards a wider domain of functions and industries, embraced under the dominant global initiatives and architectural frameworks of Industry 4.0 (or Industrie 4.0) in Germany, Industrial Internet in the US, Society 5.0 in Japan, and Made-in-China 2025 in China. As real-time embedded systems are quickly achieving ubiquity in everyday life and in industrial environments, and many processes already depend on real-time cyber-physical systems and embedded sensors, the integration of IoT with cognitive computing and real-time data exchange is essential for real-time analytics and realization of digital twins in smart environments and services under the various frameworks’ provisions. In this context, real-time sensor networks and systems for the Industrial IoT encompass multiple technologies and raise significant design, optimization, integration and exploitation challenges. The ten articles in this Special Issue describe advances in real-time sensor networks and systems that are significant enablers of the Industrial IoT paradigm. In the relevant landscape, the domain of wireless networking technologies is centrally positioned, as expected