2022 IEEE International Symposium on the Physical and Failure Analysis of Integrated Circuits (IPFA)最新文献

LADA methodologies to localize embedded memory failure 定位嵌入式内存故障的LADA方法

2022 IEEE International Symposium on the Physical and Failure Analysis of Integrated Circuits (IPFA) Pub Date : 2022-07-18 DOI: 10.1109/IPFA55383.2022.9915715

B. Yeoh, M.H. Thor, L.S. Gan, Y. Chan, S. Goh

引用次数: 1

Semantic-Masked Intensity Augmentation for Deep Learning-based Analysis of FPGA Images 基于深度学习的FPGA图像分析的语义掩码强度增强

2022 IEEE International Symposium on the Physical and Failure Analysis of Integrated Circuits (IPFA) Pub Date : 2022-07-18 DOI: 10.1109/IPFA55383.2022.9915735

Deruo Cheng, Yee-Yang Tee, Jingsi Song, Yiqiong Shi, Tong Lin, B. Gwee

{"title":"Semantic-Masked Intensity Augmentation for Deep Learning-based Analysis of FPGA Images","authors":"Deruo Cheng, Yee-Yang Tee, Jingsi Song, Yiqiong Shi, Tong Lin, B. Gwee","doi":"10.1109/IPFA55383.2022.9915735","DOIUrl":"https://doi.org/10.1109/IPFA55383.2022.9915735","url":null,"abstract":"The emergence of data science and deep learning has enabled the automated recognition of circuit elements from the microscopic images of delayered Integrated Circuit (IC) devices, and has greatly improved the efficiency of overall functional analysis flow for hardware security. However, due to the high complexity of delayering the manufactured IC devices and the imaging imperfections in modern ICs, the acquired microscopic images usually contain unforeseeable variations even for the same types of circuit elements. As a result, the deep learning model which is typically trained with a very limited set of labelled images suffers from inefficacy on generalizing to unseen images, which further causes errors for subsequent analysis. Data augmentation techniques, which virtually introduce data variations and increase the data amount by applying different image transformations, are thus widely used during the training of deep learning models for IC image analysis. In this paper, we propose a Semantic-Masked Intensity Augmentation (SMIA) technique with a deep-learning-based framework to analyze the microscopic images acquired from a delayered Field-Programmable Gate Arrays (FPGA) device. Different from the commonly-used intensity augmentation techniques which apply transformations to the image pixels according to their original intensities, our proposed SMIA considers the semantic context of the image pixels by applying different intensity transformations according to pixel-level semantic masks. With experiments on segmenting metal lines from the metal layer images of a targeted FPGA, our proposed SMIA demonstrates better performance and higher stability than the existing intensity augmentation techniques.","PeriodicalId":378702,"journal":{"name":"2022 IEEE International Symposium on the Physical and Failure Analysis of Integrated Circuits (IPFA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122721037","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

A scalable & comprehensive resilience concept against optical & physical IC backside attacks 针对光学和物理IC背后攻击的可扩展和全面弹性概念

2022 IEEE International Symposium on the Physical and Failure Analysis of Integrated Circuits (IPFA) Pub Date : 2022-07-18 DOI: 10.1109/IPFA55383.2022.9915714

N. Herfurth, E. Amini, M. Lisker, Jean-Pierre Seifert, C. Boit

{"title":"A scalable & comprehensive resilience concept against optical & physical IC backside attacks","authors":"N. Herfurth, E. Amini, M. Lisker, Jean-Pierre Seifert, C. Boit","doi":"10.1109/IPFA55383.2022.9915714","DOIUrl":"https://doi.org/10.1109/IPFA55383.2022.9915714","url":null,"abstract":"IC security is not ensured until the chip backside is fully protected. This paper presents a comprehensive and VLSI-compatible protection structure to secure integrated circuits (ICs) against all types of physical and optical attacks targeting the IC via the chip backside. The novel method of protecting the IC structure is provided by outsourcing the protection scheme onto a dedicated protection wafer. This protection wafer is then irreversibly bonded to the IC. This process can be performed at wafer level, realising a VLSI-compatible protection scheme. An example integration based on the new approach is described and discussed in detail.The protection wafer consists of a highly doped silicon substrate forming an optical opaque layer. The protection wafer is irreversibly bonded to the IC and electrically contacted by through silicon vias (TSVs). Integrity of the wafer-stack is verified by an electro-optical process. The protection wafer contains several photon-emitting devices. Several p-n junctions on the circuit side of the protected IC sense the optical signals generated by the photon emitting devices on the protection wafer.","PeriodicalId":378702,"journal":{"name":"2022 IEEE International Symposium on the Physical and Failure Analysis of Integrated Circuits (IPFA)","volume":"76 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123218337","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Photon Emission Microscopy of Amorphous HfO2 ReRAM Cells 非晶态HfO2 ReRAM细胞的光子发射显微镜研究

2022 IEEE International Symposium on the Physical and Failure Analysis of Integrated Circuits (IPFA) Pub Date : 2022-07-18 DOI: 10.1109/IPFA55383.2022.9915718

F. Stellari, L. Ocola, E. Wu, T. Ando, P. Song

引用次数: 1

Optimizing EBAC / EBIRCH analysis in 5 nm technology 优化5nm技术的EBAC / EBIRCH分析

2022 IEEE International Symposium on the Physical and Failure Analysis of Integrated Circuits (IPFA) Pub Date : 2022-07-18 DOI: 10.1109/IPFA55383.2022.9915709

A. Rummel, Greg M. Johnson

引用次数: 0

Comprehensive Investigation of the Switching Stability in SiC and GaN Power Devices SiC和GaN功率器件开关稳定性的综合研究

2022 IEEE International Symposium on the Physical and Failure Analysis of Integrated Circuits (IPFA) Pub Date : 2022-07-18 DOI: 10.1109/IPFA55383.2022.9915772

Shun-Wei Tang, Chao-Ta Fan, Ming-Cheng Lin, Tian-Li Wu

引用次数: 0

High-Voltage a-IGZO Thin Film Transistor with the Symmetrical Stair Gate-Dielectric Structure 具有对称阶梯栅介电结构的高压a-IGZO薄膜晶体管

2022 IEEE International Symposium on the Physical and Failure Analysis of Integrated Circuits (IPFA) Pub Date : 2022-07-18 DOI: 10.1109/IPFA55383.2022.9915719

Guangan Yang, Ting-Hui Huang, Wangran Wu, Hao Tian, Zuoxu Yu, Siyang Liu, Weifeng Sun

引用次数: 0

Enhanced EBAC Detection on Gate Oxide Breakdown Isolation after High Voltage Electron Beam Irradiation 高压电子束辐照栅极氧化物击穿隔离的增强EBAC检测

2022 IEEE International Symposium on the Physical and Failure Analysis of Integrated Circuits (IPFA) Pub Date : 2022-07-18 DOI: 10.1109/IPFA55383.2022.9915744

P. T. Ng, F. Rivai, A. Quah, J. C. Alag, P. K. Tan, C. Q. Chen

引用次数: 0

Effective Defect Localization for Scan ATPG Failure through Layout Aware Analysis 基于布局感知分析的扫描ATPG故障有效缺陷定位

2022 IEEE International Symposium on the Physical and Failure Analysis of Integrated Circuits (IPFA) Pub Date : 2022-07-18 DOI: 10.1109/IPFA55383.2022.9915736

Jack Yi Jie Ng, Kok Heng Lau, C. N. Liew, L.L. Goh, Chia-Li Song, Lee Kean Yong

引用次数: 0

Gate oxide TDDB reliability under various stress in sub-16nm FinFET technology 亚16nm FinFET技术中栅极氧化物TDDB在各种应力下的可靠性

2022 IEEE International Symposium on the Physical and Failure Analysis of Integrated Circuits (IPFA) Pub Date : 2022-07-18 DOI: 10.1109/IPFA55383.2022.9915742

Xiangyu Liu, Yongsheng Sun, Junlin Huang, Xiaolu Shang, Changze Liu

引用次数: 3