SRLL: Improving Security and Reliability with User-Defined Constraint-Aware Logic Locking

As chip fabrication costs rise, designers have shifted to a fabless and outsourced development model which opens up the possibility for IP piracy. To address these challenges, logic locking methods modify designs to limit functionality to authorized users that present a valid secret key. However, existing techniques often face limitations in resilience against advanced attacks and do not provide solutions to achieve user-defined constraints and goals. In this article, we propose SRLL, a user-defined constraint-aware logic locking technique that aims to improve the security and reliability of hardware designs. SRLL bridges the gap between exact and approximate attacks and allows the user to balance the resiliency against satisfiability-based, machine-learning-based, and constant propagation attacks while securing design constraints provided by the user. To enable this, we limit the locking functions to the non-critical path components and insert key gates at specific nodes, introducing a new set of critical parameters specifically designed to prevent target attacks. Finally, we obfuscate the netlist to hide inserted key gates and locking functions. Results show that SRLL maintains strong resiliency by exponentially increasing the required number of distinguishing input patterns, the complexity of finding these patterns, and adding sufficient structural complexity to the design. We evaluate SRLL using ISCAS ’85, MCNC ’91, and ITC ’99 benchmarks, demonstrating resiliency with low overhead against modern attacks, including SAT, AppSAT, OMLA, SAIL, and SCOPE.

Authors

Institutions

Publication Details

Journal
ACM Journal on Emerging Technologies in Computing Systems
Published
2024-12-23
DOI
https://doi.org/10.1145/3709139
Citations
1
Primary Topic
Physical Unclonable Functions (PUFs) and Hardware Security
Type
article
Field-Weighted Citation Impact
0.49

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

SRLL: Improving Security and Reliability with User-Defined Constraint-Aware Logic Locking

Mona Hashemi, Siamak Mohammadi, Trevor E. Carlson
1 citations
ACM Journal on Emerging Technologies in Computing Systems
Physical Unclonable Functions (PUFs) and Hardware Security
0.49
article

SRLL: Improving Security and Reliability with User-Defined Constraint-Aware Logic Locking

Mona Hashemi, Siamak Mohammadi, Trevor E. Carlson
article en
1 citations

Abstract

As chip fabrication costs rise, designers have shifted to a fabless and outsourced development model which opens up the possibility for IP piracy. To address these challenges, logic locking methods modify designs to limit functionality to authorized users that present a valid secret key. However, existing techniques often face limitations in resilience against advanced attacks and do not provide solutions to achieve user-defined constraints and goals. In this article, we propose SRLL, a user-defined constraint-aware logic locking technique that aims to improve the security and reliability of hardware designs. SRLL bridges the gap between exact and approximate attacks and allows the user to balance the resiliency against satisfiability-based, machine-learning-based, and constant propagation attacks while securing design constraints provided by the user. To enable this, we limit the locking functions to the non-critical path components and insert key gates at specific nodes, introducing a new set of critical parameters specifically designed to prevent target attacks. Finally, we obfuscate the netlist to hide inserted key gates and locking functions. Results show that SRLL maintains strong resiliency by exponentially increasing the required number of distinguishing input patterns, the complexity of finding these patterns, and adding sufficient structural complexity to the design. We evaluate SRLL using ISCAS ’85, MCNC ’91, and ITC ’99 benchmarks, demonstrating resiliency with low overhead against modern attacks, including SAT, AppSAT, OMLA, SAIL, and SCOPE.

ACM Journal on Emerging Technologies in Computing SystemsVol. 21(1)
National University of Singapore (SG), University of Tehran (IR), Institute for Research in Fundamental Sciences (IR)
National Research Foundation, Institute for Research in Fundamental Sciences
Openalex Percentile: Top 33%
Physical Unclonable Functions (PUFs) and Hardware Security
0.49
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.