Camouflaged Logic Gates Using Threshold-Voltage-Defined Memory Cells
This brief proposes two types of camouflaged logic gates using threshold-voltage-defined memory cells (TVD-MCs). The proposed multiplexer-select TVD-MC (MS-TVDMC) gate consists of a target logic gate, several camouflage logic gates, a multiplexer (MUX), and TVD-MCs. All logic gates and MUX are implemented with standard threshold-voltage transistors. The TVD-MC is composed of two cross-coupled inverters with low- or high-threshold-voltage transistors. When its supply voltage increases from ground to <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${V} _{\text {DD}}$</tex-math> </inline-formula>, its data become “0” or “1” according to the threshold voltages of transistors in two inverters. The target logic gate is selected with the MUX by the data stored in the TVD-MCs. The data are defined by the threshold voltages of transistors, so that it is difficult to distinguish the target logic gate from the other camouflage logic gates. The proposed logic-merged TVD-MC (LM-TVDMC) gate merges all logic gates and MUX in the MS-TVDMC gate at the transistor level. The proposed camouflaged gates significantly reduce the delay, power consumption, and leakage current compared to the conventional dynamic enhanced-TVD (DE-TVD) camouflaged gate requiring the dynamic power and delay overheads and the conventional threshold-voltage-defined (TVD) switch camouflaged gate with large <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">on</small>-resistances in switch transistors.
Authors
- Min-woo Kim
- Byung‐Do Yang (ORCID: https://orcid.org/0000-0002-5299-1075)
- Jae-Mun Oh
Institutions
- Electronics and Telecommunications Research Institute (KR)
- Chungbuk National University (KR)
Publication Details
- Journal
- IEEE Transactions on Very Large Scale Integration (VLSI) Systems
- Published
- 2025-09-01
- DOI
- https://doi.org/10.1109/tvlsi.2025.3601192
- Primary Topic
- Advanced Memory and Neural Computing
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Research Foundation of Korea