Demo Data from EDBT 2026 / reviewers in the wild / expert
Shabnam Larimian
dblp:241/4273
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2019
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Systems, architecture and hardware · 1
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Network and information security
1 paper |
Hardware security and side channels · 100% |
Topics — the 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Hardware security and side channels › hardware security primitives
physical unclonable function |
0.4 | 1 | 2019 | ChipSecure: A Reconfigurable Analog eFlash-Based PUF with Machine Learning Attack Resiliency in 55nm CMOS · DAC 2019 |
Hardware security and side channels › hardware security primitives › physical unclonable function
modeling attack resistance |
0.1 | 1 | 2019 | ChipSecure: A Reconfigurable Analog eFlash-Based PUF with Machine Learning Attack Resiliency in 55nm CMOS · DAC 2019 |
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2019 | ChipSecure: A Reconfigurable Analog eFlash-Based PUF with Machine Learning Attack Resiliency in 55nm CMOSabstractWe exploit randomness in static I-V characteristics and reconfigurability of embedded flash memories to design very efficient physically unclonable function. Leakage current and subthreshold slope variations, nonlinearity, nondeterministic tuning error, and sneak path current in the redesigned commercial flash memory arrays are exploited to create a unique digital fingerprint. A time-multiplexed architecture is designed to enhance the security and expand the challenge-response pair space to 10211. Experimental results demonstrate 50.3% average uniformity, 49.99% average diffuseness, and native <5% bit error rate. The analysis of the measured data also shows strong resilience against machine learning attacks and possibility for extremely energy efficient, 0.56 pJ/b operation. Mohammad Reza Mahmoodi, Hussein Nili, Shabnam Larimian, Xinjie Guo, Dmitri B. Strukov |
DAC | 3 |