1.

Record Nr.

UNISA996466458303316

Titolo

Constructive Side-Channel Analysis and Secure Design [[electronic resource] ] : 8th International Workshop, COSADE 2017, Paris, France, April 13-14, 2017, Revised Selected Papers / / edited by Sylvain Guilley

Pubbl/distr/stampa

Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017

ISBN

3-319-64647-8

Edizione

[1st ed. 2017.]

Descrizione fisica

1 online resource (X, 299 p. 127 illus.)

Collana

Security and Cryptology ; ; 10348

Disciplina

005.8

Soggetti

Computer security

Data encryption (Computer science)

Management information systems

Computer science

Architecture, Computer

Computer science—Mathematics

Microprogramming 

Systems and Data Security

Cryptology

Management of Computing and Information Systems

Computer System Implementation

Discrete Mathematics in Computer Science

Control Structures and Microprogramming

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Nota di contenuto

Does Coupling Affect the Security of Masked Implementations -- Scaling Trends for Dual-Rail Logic Styles against Side-Channel Attacks: A Case-Study -- Dissecting Leakage Resilient PRFs with Multivariate Localized EM Attacks - A Practical Security Evaluation on FPGA -- Toward More Effcient DPA-Resistant AES Hardware Architecture Based on Threshold Implementation -- Enhanced Elliptic Curve Scalar Multiplication Secure Against Side Channel Attacks and Safe Errors -- SafeDRP: Yet Another Way Toward Power-Equalized Designs in FPGA --



On the Construction of Side-Channel Attack Resilient S-boxes -- Efficient Conversion Method from Arithmetic to Boolean Masking in Constrained Devices -- Side-Channel Analysis of Keymill -- On the Easiness of Turning Higher-Order Leakages into First-Order -- Side-Channel Attacks against the Human Brain: The PIN Code Case Study -- Impacts of Technology Trends on Physical Attacks -- Low-cost Setup for Localized Semi-invasive Optical Fault Injection Attacks - How Low Can We Go -- DFA on LS-Designs with a Practical Implementation on SCREAM -- Multiple-Valued Debiasing for Physically Unclonable Functions and Its Application to Fuzzy Extractors -- Getting the Most out of Leakage Detection - Statistical Tools and Measurement Setups Hand in Hand -- Mind the Gap: Towards Secure 1st-Order Masking in Software.

Sommario/riassunto

This book constitutes revised selected papers from the 8th International Workshop on Constructive Side-Channel Analysis and Secure Design, COSADE 2017, held in Paris, France, in April 2017. The 17 papers presented in this volume were carefully reviewed and selected from numerous submissions. They were organized in topical sections named: Side-Channel Attacks and Technological Effects; Side-Channel Countermeasures; Algorithmic Aspects in Side-Channel Attacks; Side-Channel Attacks; Fault Attacks; Embedded Security; and Side-Channel Tools.



2.

Record Nr.

UNISA996503467003316

Titolo

Advances in computer graphics : 39th computer graphics international conference, CGI 2022, virtual event, September 12-16, 2022, proceedings / / Nadia Magnenat-Thalmann [and six others], editors

Pubbl/distr/stampa

Cham, Switzerland : , : Springer, , [2022]

©2022

ISBN

3-031-23473-1

Descrizione fisica

1 online resource (590 pages)

Collana

Lecture notes in computer science ; ; Volume 13443

Disciplina

006.6869

Soggetti

Computer graphics

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Note generali

Includes index.

Nota di contenuto

Intro -- Preface -- Organization -- Contents -- Image Analysis and Processing -- Multi-granularity Feature Attention Fusion Network for Image-Text Sentiment Analysis -- 1 Introduction -- 2 Related Work -- 2.1 Text Sentiment Analysis -- 2.2 Image Sentiment Analysis -- 2.3 Multimodal Sentiment Analysis -- 3 Our Proposed Model -- 3.1 Model Overview -- 3.2 Feature Learning Layer -- 3.3 Interactive Information Fusion Layer -- 3.4 Interactive Information Fusion Layer -- 4 Experimental Results -- 4.1 Dataset Description -- 4.2 Baselines -- 4.3 Experimental Results and Analysis -- 5 Conclusions -- References -- Toward Efficient Image Denoising: A Lightweight Network with Retargeting Supervision Driven Knowledge Distillation*-12pt -- 1 Introduction -- 2 Proposed Method -- 2.1 Lightweight U-shaped Denoising Network: LUNet -- 2.2 Retargeting Supervision Driven Knowledge Distillation -- 3 Experimental Results -- 3.1 Experimental Settings -- 3.2 Quantitative and Qualitative Results -- 3.3 Ablation Studies -- 4 Conclusions -- References -- A Pig Pose Estimation Model for Measuring Pig's Body Size -- 1 Introduction -- 2 Related Work -- 2.1 Measuring Animal Body Size -- 2.2 Key Point Identification -- 2.3 Attention Mechanism -- 3 Our Approach -- 3.1 Our Network Header -- 3.2 Down-Sampling Module -- 3.3 Selection of Key Points -- 4 Experiments -- 4.1 Dataset -- 4.2 Results on Image and Video -- 4.3 Results on Combining Attention Mechanism -- 4.4 Results on Using



Our Network Header -- 5 Conclusion -- References -- Topology-Aware Learning for Semi-supervised Cross-domain Retinal Artery/Vein Classification*-12pt -- 1 Introduction -- 2 Method -- 2.1 Overview -- 2.2 Spatial Transformation Module -- 2.3 Regional Mixing Module -- 2.4 Loss Function -- 3 Experimental Results -- 3.1 Datasets -- 3.2 Implementation Details -- 3.3 Artery/Vein Classification Performance.

4 Conclusion -- References -- Face Super-Resolution with Better Semantics and More Efficient Guidance -- 1 Introduction -- 2 Method -- 2.1 Overview of the Proposed Framework -- 2.2 Better Semantic Prior -- 2.3 More Efficient Guidance -- 2.4 Loss Functions -- 3 Experiments -- 3.1 Implementation Details -- 3.2 Comparisons with the State-of-the-Arts -- 3.3 Ablation Study -- 4 Conclusion -- References -- Graphs and Networks -- Layout and Display of Network Graphs on a Sphere*-12pt -- 1 Introduction -- 2 Related Work -- 3 Visualization Pipeline -- 4 Graph Visualization Algorithms -- 4.1 Layout - Adaptation of Fruchterman-Reingold Algorithm -- 4.2 Quantitative Evaluation -- 4.3 Visualizing Spheres in Paraview -- 4.4 Mathematical Basis for Visualizing Arcs in Paraview -- 5 Browser-Based Visualization -- 6 Conclusion -- References -- Joint Matrix Factorization and Structure Preserving for Domain Adaptation*-12pt -- 1 Introduction -- 2 Related Work -- 3 Proposed Method -- 3.1 Notations -- 3.2 Problem Formulation -- 3.3 Optimization -- 4 Experiments -- 4.1 Datasets Description -- 4.2 Results -- 4.3 Parameter Sensitivity and Ablation Study -- 5 Conclusion -- References -- Graph Adversarial Network with Bottleneck Adapter Tuning for Sign Language Production*-12pt -- 1 Introduction -- 2 Related Work -- 2.1 Sign Language Production -- 2.2 Transfer Learning -- 2.3 Graph Convolutional Network -- 3 Method -- 3.1 Adapter-Based Contextual Representation -- 3.2 Channel-Wise Target Length Predictor -- 3.3 Cross-modal Sign Pose Generator -- 3.4 Spatial-Temporal Graph Convolutional Discriminator -- 3.5 Loss Function -- 4 Experiments -- 4.1 Datasets -- 4.2 Training Settings -- 4.3 Evaluation Metrics -- 4.4 Quantitative Evaluation -- 4.5 Visual Comparison -- 4.6 Ablation Study -- 5 Conclusion -- References -- Estimation and Feature Matching.

Facial Landmarks Based Region-Level Data Augmentation for Gaze Estimation*-12pt -- 1 Introduction -- 2 Related Works -- 2.1 Gaze Estimation -- 2.2 Data Augmentation -- 3 Proposed Method -- 3.1 Facial Landmarks Based Region Mask -- 3.2 Non-eye Regions Data Augmentation -- 4 Experiments -- 4.1 Experimental Setup -- 4.2 Performance Comparison -- 4.3 Ablation Studies -- 5 Conclusions -- References -- An Efficient Dense Depth Map Estimation Algorithm Using Direct Stereo Matching for Ultra-Wide-Angle Images*-12pt -- 1 Introduction -- 2 Patch Matching Stereo -- 2.1 Camera Projection Model -- 2.2 Patch Matching Stereo for Ultra-Wide-Angle Images -- 3 Experimental Results -- 3.1 The TUM VI Benchmark -- 3.2 Comparisons -- 3.3 The Oxford RobotCar Dataset -- 4 Conclusion -- References -- Ad-RMS: Adaptive Regional Motion Statistics for Feature Matching Filtering -- 1 Introduction -- 2 Related Works -- 3 Method -- 3.1 Adaptive Regional Division -- 3.2 Regional Motion Statistics -- 4 Experiment -- 4.1 Evaluation -- 4.2 Dataset and Input Data -- 4.3 Parameters -- 4.4 Comparative Analysis of Results -- 5 Summary -- References -- 3D Reconstruction -- Visual Indoor Navigation Using Mobile Augmented Reality -- 1 Introduction -- 2 Related Work -- 2.1 Indoor Navigation System -- 2.2 Positioning and Navigation Technology -- 3 Research Content and Methodology -- 3.1 Plane and Point Cloud Detection and Visualization -- 3.2 Indoor Map Construction -- 3.3 Map Download and Self-positioning -- 3.4 Path Planning and Display -- 4 Experiment -- 5 Analysis of Results --



References -- Cost Volume Pyramid Network with Multi-strategies Range Searching for Multi-view Stereo -- 1 Introduction -- 2 Related Work -- 2.1 Coarse-to-Fine MVS Methods -- 2.2 Depth Sampling Range -- 2.3 Cost Volume -- 3 Methods -- 3.1 Overview -- 3.2 Depth Sampling Range Estimation -- 3.3 Supervise on Cost Volume.

3.4 Loss Function -- 4 Experiment -- 4.1 Dataset -- 4.2 Implementation Details -- 4.3 Results on DTU Dataset -- 4.4 Results on BlendedMVS -- 4.5 Effectiveness of Multi-strategies -- 4.6 Ablation Study -- 5 Conclusion -- References -- Reconstructing the Surface Mesh Representation for Single Neuron -- 1 Introduction -- 2 Related Work -- 3 Method -- 3.1 Branch Identification -- 3.2 Surface Reconstruction of Neurites -- 3.3 Surface Reconstruction of the Soma -- 4 Experiments and Results -- 5 Conclusion -- References -- WEmap: Weakness-Enhancement Mapping for 3D Reconstruction with Sparse Image Sequences -- 1 Introduction -- 2 Related Work -- 3 Method -- 3.1 Initial Reconstruction -- 3.2 Generation of the Enhanced Set -- 3.3 Reconstruction with Weighted Samples -- 4 Experiments -- 4.1 Datasets -- 4.2 Experiments on the Sparse DTU Dataset -- 4.3 Experiments on the Sparse Tanks and Temples Dataset -- 5 Conclusion -- References -- Rendering and Animation -- Comparing Traditional Rendering Techniques to Deep Learning Based Super-Resolution in Fire and Smoke Animations -- 1 Introduction -- 2 Related Work -- 3 TecoGAN -- 3.1 Network Architecture for Video Super-Resolution -- 3.2 Usage -- 4 Dataset Generation -- 4.1 Creating a Smoke Simulation -- 4.2 Multiple Simulations -- 5 Evaluation -- 5.1 Creating Different Renders -- 5.2 Comparing Video Quality -- 5.3 Cross Simulation Comparison -- 6 Conclusion -- References -- Real-Time Light Field Path Tracing -- 1 Introduction -- 2 Related Work -- 3 General Pipeline and Our Implementation -- 3.1 General Pipeline -- 3.2 Our Implementation -- 4 Experiments -- 5 Results -- 5.1 Runtime -- 5.2 Quality -- 6 Conclusions -- References -- Crowd Simulation with Detailed Body Motion and Interaction -- 1 Introduction -- 2 Related Work -- 2.1 Crowd Simulation -- 2.2 Motion Matching -- 3 Overview -- 4 Hierarchical Control.

5 Agent Model -- 5.1 Visual System -- 5.2 Blackboard System -- 5.3 Decision System -- 5.4 Animation System -- 6 Co-simulation System -- 6.1 Mode Switch -- 6.2 Inverse Kinematic -- 7 Results -- 7.1 Behaviour Simulation -- 7.2 Animation Simulation -- 7.3 User Study -- 8 Conclusion and Future Work -- References -- Towards Rendering the Style of 20th Century Cartoon Line Art in 3D Real-Time -- 1 Introduction -- 2 Related Works -- 2.1 Contour Extraction -- 2.2 Line Stylisation -- 2.3 Offline Rendering -- 3 Approaches -- 3.1 Edge Marking -- 3.2 Geometry Shader Line Rendering -- 3.3 Line Weight Map -- 3.4 Editing the Line Thickness in Real-Time -- 3.5 Recording Line Thickness in Real-Time Animation -- 4 Results -- 5 Conclusion and Future Works -- References -- Detection and Recognition -- Face Detection Algorithm in Classroom Scene Based on Deep Learning -- 1 Introduction -- 2 Related Works -- 2.1 Overview of Target Detection -- 2.2 Optical Flow Method -- 3 Proposed Method -- 3.1 Model Overview -- 3.2 Network Design -- 3.3 Improved Seq NMS -- 3.4 Face Count -- 4 Experience -- 4.1 Dataset -- 4.2 Pretreatment -- 4.3 Parameter Setting -- 4.4 Result -- 5 Conclusion -- References -- GRVT: Toward Effective Grocery Recognition via Vision Transformer -- 1 Introduction -- 2 Related Work -- 3 Method -- 3.1 Vision Transformer -- 3.2 GRVT Architecture -- 3.3 Multi-scale Patch Embedding -- 3.4 Mixed Attention Selection -- 4 Experiments -- 4.1 Datasets and Implementation Details -- 4.2 Comparison with the State of the Art -- 4.3 Ablation Study -- 4.4 Visualization -- 5 Conclusion -- References



-- A Transformer-Based Cloth-Irrelevant Patches Feature Extracting Method for Long-Term Cloth-Changing Person Re-identification -- 1 Introduction -- 2 Related Work -- 2.1 Cloth-Changing Person Re-identification -- 2.2 Vision Transformer -- 2.3 Human Parsing -- 3 Methodology.

3.1 Transformer Encoder.