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[null,"1.","Record Nr.",null,"UNISA996464423803316"]
[null,null,"Titolo",null,"Information and communications security : 23rd international conference, ICICS 2021, Chongqing, China, November 19-21, 2021 : proceedings : Part 2 / / edited by Debin Gao [and three others]"]
[null,null,"Pubbl/distr/stampa",null,"Cham, Switzerland : , : Springer, , [2021]"]
[{"$nulls":4},"©2021"]
[null,null,"ISBN",null,"3-030-88052-4"]
[null,null,"Descrizione fisica",null,"1 online resource (429 pages)"]
[null,null,"Collana",null,"Lecture Notes in Computer Science ; ; v.12919"]
[null,null,"Disciplina",null,"005.8"]
[null,null,"Soggetti",null,"Computer security"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Nota di bibliografia","Includes bibliographical references and index."]
[null,null,"Nota di contenuto",null,"Intro -- Preface -- Organization -- Keynotes -- Engineering Trustworthy Data-Centric Software: Intelligent Software Engineering and Beyond -- Securing Smart Cars - Opportunities and Challenges -- Contents - Part II -- Contents - Part I -- Machine Learning Security -- Exposing DeepFakes via Localizing the Manipulated Artifacts -- 1 Introduction -- 2 Related Work -- 2.1 DeepFake Creation -- 2.2 DeepFake Detection -- 2.3 Attention Mechanism -- 3 Our Approach -- 3.1 Insight -- 3.2 Framework -- 3.3 Dual Attention for Detection and Localization -- 4 Experiment -- 4.1 Experimental Setup -- 4.2 Detection Effectiveness -- 4.3 Ablation Study -- 4.4 Manipulation Localization -- 5 Conclusion -- A  Dataset Details -- B  Visualization -- References -- Improved Differential-ML Distinguisher: Machine Learning Based Generic Extension for Differential Analysis -- 1 Introduction -- 1.1 Our Contributions -- 1.2 Organization -- 2 Preliminaries -- 2.1 Brief Description of Speck -- 2.2 MILP Aided Differential Analysis -- 2.3 ML Differential Distinguisher -- 2.4 Basic Differential-ML Distinguisher -- 3 The Relationship Between Input Difference and ML Differential Distinguisher -- 4 Improved Differential-ML Distinguisher with Greedy Strategy -- 4.1 Greedy Strategy Based on Considering All Possible Combinations (M1) -- 4.2 Greedy Strategy Based on the ML Differential Distinguisher (M2) -- 4.3 Greedy Strategy Based on the Classical Differential Distinguisher (M3) -- 5 Applications -- 6 Conclusions -- A  The Best Differential Trails for Speck -- B  The Partial Results for Sect.5 -- References -- Black-Box Buster: A Robust Zero-Shot Transfer-Based Adversarial Attack Method -- 1 Introduction "]
[{"$nulls":4},"-- 2 Related Work -- 2.1 Adversarial Examples and Adversarial Attacks -- 2.2 Substitute Training -- 3 Problem Statement -- 3.1 Adversarial Ability -- 3.2 Adversarial Goal -- 4 Methods."]
[{"$nulls":4},"4.1 Substitute Training -- 4.2 Adversarial Transferable Attack -- 5 Experiment -- 5.1 Experimental Setup -- 5.2 Experiments on MNIST -- 5.3 Experiments on CIFAR10 -- 5.4 Sensitivity Analysis -- 5.5 Visualization Results -- 6 Conclusion -- References -- A Lightweight Metric Defence Strategy for Graph Neural Networks Against Poisoning Attacks -- 1 Introduction -- 2 Related Works -- 3 Preliminaries -- 3.1 Problem Definition -- 3.2 Why Using Metric Methods in Defense -- 4 Our Methodology -- 4.1 Structure Property: Common Neighbors -- 4.2 Feature Property: Metric Methods -- 4.3 Clean Perturbed Edges -- 4.4 Application on GNN -- 5 Experiments -- 5.1 Experimental Settings -- 5.2 Defense Performance Analysis -- 5.3 Scalability Analysis -- 5.4 Metric Discussion -- 5.5 Threshold Discussion -- 6 Conclusion -- A  Appendix -- A.1  Visualization -- A.2  Parameter Settings -- References -- Rethinking Adversarial Examples Exploiting Frequency-Based Analysis -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Adversarial Attack Methods -- 3.2 Frequency-Based Analysis Methods -- 4 Results and Analyses -- 4.1 Experimental Setup -- 4.2 Analysis on MNIST -- 4.3 Analysis on CIFAR-10 -- 4.4 Analysis on ImageNet -- 4.5 Discussion -- 5 Conclusion and Further Work -- References -- Multimedia Security -- Compressive Sensing Image Steganography via Directional Lifting Wavelet Transform -- 1 Introduction -- 2 Background -- 2.1 Steganography in the Transform Domain -- 2.2 Compressive Sensing for Steganography -- 3 Proposed Image Steganography Scheme -- 3.1 Steganography Based on DLWT-SVD -- 3.2 Encryption Based on Chaotic System -- 3.3 Reconstruction Based on Deep-Based CS -- 4 Experimental Results -- 4.1 Visual Quality Analysis -- 4.2 Encryption Performance Analysis -- 5 Conclusion -- References."]
[{"$nulls":4},"Remote Recovery of Sound from Speckle Pattern Video Based on Convolutional LSTM -- 1 Introduction -- 2 Related Work -- 2.1 Optical Methods -- 2.2 Deep Learning Technology -- 3 Background -- 3.1 Speckle Pattern -- 3.2 ConvLSTM -- 3.3 CNN Model for Comparative Experiments -- 4 Experiment Setup -- 4.1 Data Collection -- 4.2 Training Details -- 4.3 Evaluation Metrics -- 5 Results -- 5.1 Overall Evaluation -- 5.2 Influence of Sampling Rates -- 5.3 Generalization Performance -- 6 Conclusion -- References -- Secure Image Coding Based on Compressive Sensing with Optimized Rate-Distortion -- 1 Introduction -- 2 Background -- 2.1 Compressive Sensing Theory -- 2.2 Logistic-Tent Map -- 3 The Proposed Image Coding Scheme -- 3.1 The Overview of the Proposed Image Coding Scheme -- 3.2 The Image Coding with the Elaborate Encoder -- 3.3 The Decryption and Decoding of Received Image -- 4 Experimental Results -- 4.1 Feasibility -- 4.2 The R-D Performance of the Proposed Scheme -- 4.3 The Performance of the Selected Measurement Matrix -- 4.4 Security Analysis -- 5 Conclusion -- References -- Black-Box Audio Adversarial Example Generation Using Variational Autoencoder -- 1 Introduction -- 2 Variational Autoencoder -- 3 Problem Definition -- 4 Related Work -- 5 Proposed Method -- 5.1 Generating Word-Level Adversarial Examples -- 5.2 Generating Sentence-Level Adversarial Examples -- 6 Results -- 6.1 Distortion vs Interpolation Strength -- 6.2 Word-Level Adversarial Examples -- 6.3 Sentence-Level Adversarial Examples -- 6.4 Circumventing Temporal Dependency Detection -- 6.5 Robustness Against Transformation -- 7 Limitations and Future Work -- 8 Conclusion -- References -- Security Analysis -- Security Analysis of Even-Mansour Structure Hash Functions -- 1 Introduction -- 2 "]
[{"$nulls":4},"Preliminaries -- 2.1 Description of the Even-Mansour Structure Hash Functions -- 2.2 Notations."]
[{"$nulls":4},"3 Our Preimage Attack on Even-Mansour Structure Hash Functions -- 3.1 Construction of the Partial Invariables of Input-Output in the Functions -- 3.2 Our Preimage Attack on Even-Mansour Structure Hash Functions -- 4 Multi-block Collision Attack on Even-Mansour Structure Hash Function -- 4.1 Our Multi-block Collision Attack on the Even-Mansour Structure Hash Function -- 4.2 Analysis of the Computational Complexity -- 5 Conclusion -- References -- Rare Variants Analysis in Genetic Association Studies with Privacy Protection via Hybrid System -- 1 Introduction -- 1.1 Our Contributions -- 2 Related Work -- 3 Model Design Overview -- 3.1 System Architecture -- 3.2 Threat Model -- 4 Background -- 4.1 Homomorphic Encryption -- 4.2 Minimal Perfect Hash Function -- 4.3 Overview of Intel SGX -- 4.4 Weighted Sum Statistic Computation -- 5 Method -- 5.1 Encoding of Genomic Data and Hash Generation -- 5.2 Proposed Framework -- 6 Experimental Results and Analysis -- 6.1 Experiment Setup -- 6.2 Implementation Results -- 6.3 Comparison with Existing Methods -- 7 Conclusion -- References -- Rotational-Linear Attack: A New Framework of Cryptanalysis on ARX Ciphers with Applications to Chaskey -- 1 Introduction -- 2 Preliminaries -- 2.1 Notations -- 2.2 Partitioning Technique for Modular Additions -- 2.3 Description of Chaskey -- 3 Rotational Cryptanalysis -- 4 Rotational-Linear Attacks on ARX Ciphers -- 4.1 Correlation of Linear Approximations -- 4.2 The Connective Part -- 4.3 Decrease the Data Complexity -- 4.4 Key Recovery -- 4.5 A Simple Toy Example -- 5 Application to Chaskey -- 5.1 Attack Against 7-Round Chaskey -- 5.2 Distinguisher and Experimental Result -- 6 Conclusion -- A  Application to ChaCha Permutation -- B  The Proposition used When Recovering Partial Key -- References."]
[{"$nulls":4},"A Novel Approach for Supervisor Synthesis to Enforce Opacity of Discrete Event Systems -- 1 Introduction -- 2 Preliminaries -- 2.1 Labeled Transition System (LTS) -- 2.2 The Opacity Property -- 2.3 Symbolic Observation Graph (SOG) -- 2.4 Supervisory Control Background -- 3 Security Approach with Supervisory Control -- 3.1 Supervisor Synthesis -- 3.2 Properties of the Language Induced by Supervision -- 3.3 SOG-Based Approach for Opacity Supervision -- 4 Implementation and Application to an IoT Maze Case Study -- 5 Related Work -- 6 Conclusion and Future Work -- A  Appendix -- A.1  Proof of Theorem 2 -- A.2  Plan of the Maze -- References -- Post-quantum Cryptography -- Lattice-Based Secret Handshakes with Reusable Credentials -- 1 Introduction -- 2 Preliminaries -- 2.1 Background on Lattices -- 2.2 Zero-Knowledge Arguments of Knowledge -- 3 Model and Security Properties of Secret Handshake -- 4 Our Lattice-Based Secret Handshake Scheme -- 5 Security and Performance Analysis of the Scheme -- 5.1 Security -- 5.2 Performance -- 6 Conclusion -- References -- When NTT Meets Karatsuba: Preprocess-then-NTT Technique Revisited -- 1 Introduction -- 2 Preliminaries -- 2.1 Karatsuba Algorithm -- 2.2 Number Theoretic Transform -- 2.3 NTT for Zq[x]/(xn+1) Without 2n-th Root -- 3 Preprocess-then-NTT with Karatsuba (KNTT) -- 3.1 Improving PtNTT with Karatsuba Algorithm -- 3.2 -Round Preprocess-then-NTT with Karatsuba (KNTT) -- 3.3 Experiment Results -- 3.4 Theoretical Comparison and Further Discussion -- 4 Conclusion -- References -- Predicting the Concrete Security of LWE Against the Dual Attack Using Binary Search -- 1 Introduction -- 1.1 Our Contributions -- 1.2 Roadmap -- 2 Preliminaries -- 3 Predicting the Minimal Cost of the Dual Attack -- 3.1 The Optimal Scaling Factor -- 3.2 The Optimal "]
[{"$nulls":4},"Dimension and Block Size."]
[{"$nulls":4},"4 Theoretical Comparison Between the Costs of MR Dual Attack and Albrecht Dual Attack."]