Cyber Security : : 18th China Annual Conference, CNCERT 2021, Beijing, China, July 20-21, 2021, Revised Selected Papers.

• Superior document: Communications in Computer and Information Science Series ; v.1506
• Author: Lu, Wei.
• TeilnehmendeR: Zhang, Yuqing.; Wen, Weiping.; Yan, Hanbing.; Li, Chao.
• Place / Publishing House: Singapore : : Springer Singapore Pte. Limited,, 2022.; ©2022.
• Year of Publication: 2022
• Edition: 1st ed.
• Language: English
• Series: Communications in Computer and Information Science Series
• Physical Description: 1 online resource (234 pages)

Table of Contents

Intro -- Preface -- Organization -- Contents -- Data Security -- A Robust and Adaptive Watermarking Technique for Relational Database -- 1 Introduction -- 2 Related Work -- 3 Scheme -- 3.1 Pre-processing Stage -- 3.2 Data Type Adaptation -- 3.3 Data Volume Evaluation -- 3.4 Data Column Sensitivity Judgment -- 3.5 Automatic Parameter Setting -- 3.6 Watermark Embedding Stage -- 3.7 Watermark Extraction Stage -- 3.8 Result Visualization Mechanism -- 4 Experimental Analysis -- 4.1 Invisibility Analysis Experiments -- 4.2 Precision Control Analysis Experiment -- 4.3 Watermark Robustness Ability Comparison Experiment -- 5 Summary -- References -- A Privacy-Preserving Medical Data Traceability System Based on Attribute-Based Encryption on Blockchain -- 1 Introduction -- 2 Related Work -- 2.1 Blockchain Technology -- 2.2 Reversible Data Desensitization -- 2.3 Attribute-Based Encryption Technology -- 3 System Model -- 3.1 Reversible Data Desensitization -- 3.2 Access Control Based on Attributes -- 4 Scheme -- 5 Performance and Safety Analysis -- 6 Summary -- References -- Privacy Protection -- Analysis of Address Linkability in Tornado Cash on Ethereum -- 1 Introduction -- 2 Related Work -- 3 Preliminaries -- 3.1 Basics of Tornado Cash -- 3.2 Coin Mixing Process in Tornado Cash -- 4 Analysis of Tornado Cash -- 4.1 Definitions -- 4.2 Data Acquisition -- 4.3 Transaction Patterns -- 5 Heuristic Cluster Rules -- 5.1 Heuristics -- 5.2 Evaluation -- 6 Conclusion and Future Work -- References -- FPFlow: Detect and Prevent Browser Fingerprinting with Dynamic Taint Analysis -- 1 Introduction -- 2 Related Work -- 3 Motivation -- 4 Technique Approach -- 4.1 Overview -- 4.2 Taint Source and Taint Sink -- 4.3 Taint Table and Taint Name Table -- 4.4 Taint Propagation -- 4.5 Logging -- 5 Evaluation -- 5.1 Experimental Setup -- 5.2 Large Scale Experiment Result.

5.3 Evaluate the Accuracy of Taint Analysis -- 5.4 Fingerprinting Prevention -- 6 Discussion -- 7 Conclusion -- References -- Anomaly Detection -- Deep Learning Based Anomaly Detection for Muti-dimensional Time Series: A Survey -- 1 Introduction -- 2 Challenge -- 2.1 Dimensional Explosion -- 2.2 Concept Drift -- 2.3 Complex Semantics -- 2.4 Data Sparse -- 2.5 Poor Scalability -- 2.6 Summary -- 3 Rule-Based Anomaly Detection Algorithm -- 4 Anomaly Detection Algorithm Based on Machine Learning -- 4.1 Clustering-Based Method -- 4.2 Classification-Based Method -- 4.3 Method-Based Prediction -- 5 Anomaly Detection Algorithm Based on Deep Learning -- 5.1 Method-Based Regression -- 5.2 Method-Based Dimension Reduction -- 6 Summary -- References -- ExitSniffer: Towards Comprehensive Security Analysis of Anomalous Binding Relationship of Exit Routers -- 1 Introduction -- 2 Related Work -- 3 The Design of ExitSniffer and Phenomenon -- 3.1 The Design of ExitSniffer -- 3.2 Dataset -- 4 Experimental Analysis -- 4.1 The Size of the Malicious Exit Nodes -- 4.2 Bandwidth Ratio of MENP Nodes -- 4.3 Behavior Exploration of MENP Nodes -- 4.4 The co-owner Relationship of the Malicious Exit Node -- 5 Conclusion -- References -- Traffic Analysis -- Efficient Classification of Darknet Access Activity with Partial Traffic -- 1 Introduction -- 2 Background -- 2.1 Tor -- 2.2 Hidden Service Components -- 2.3 Threat Model -- 3 Data Collection and Processing -- 3.1 Data Collection -- 3.2 Data Extraction and Processing -- 4 Evaluation and Discussion -- 4.1 Position Distribution Observation -- 4.2 Comparison of Different Classification Methods -- 4.3 Classification with Partial Cell Fragment -- 5 Related Work -- 6 Conclusion -- References -- Research and Application of Security Situation Awareness Platform for Large Enterprises -- 1 Introduction.

2 General Status and Problems of Information Security in Large Enterprises -- 2.1 General Situation of Information Security in Large Enterprises -- 2.2 Analysis of Information Security Situation of Large Enterprises -- 2.3 Analysis of Information Security Problems in Large Enterprises -- 3 Status and Role of Security Situation Awareness Platform -- 3.1 Relationship Between Security Situation Awareness Platform and Security Management System -- 3.2 Main Functions of Security Situation Awareness Platform -- 4 Technology Implementation Scheme and Evolution Route of Security Situation Awareness Platform -- 4.1 Platform Structure -- 4.2 Main Capabilities of Network Security Situation Awareness Technology -- 4.3 Platform Evolution Route -- 5 Problems Needing Attention -- 5.1 Organization Mechanism Guarantee, Forming a Virtuous Circle -- 5.2 Devops Guarantee -- 5.3 Institutional Constraints to Reduce Employee Risk -- 5.4 Persevere and Introduce Ecology (Good Partner) -- 6 Conclusion -- References -- Social Network Security -- Research on the Relationship Between Chinese Nicknames and Accounts in Social Networks -- 1 Introduction -- 2 Related Work -- 2.1 Research Status -- 2.2 Existing Problem -- 2.3 Research Opportunities -- 3 Data Collection and Implementation -- 3.1 Information Acquisition and Integration Analysis -- 3.2 Acquisition Module Design and Implementation -- 4 Data Collection and Implementation -- 4.1 Universal Feature -- 4.2 Feature Selection -- 5 Algorithm Design -- 5.1 Jaro Distance -- 5.2 Jaro-Winkler Distance -- 5.3 Text Algorithm -- 6 Experiment and Analysis -- 6.1 Data Description -- 6.2 Index Evaluation -- 6.3 Comparison of Methods -- 7 Conclusion -- References -- TFC: Defending Against SMS Fraud via a Two-Stage Algorithm -- 1 Introduction -- 2 Related Work -- 3 Measurement Analysis -- 4 Algorithm Design -- 4.1 Model Overview.

4.2 Stage 1 - Normal SMS Filter -- 4.3 Stage 2 - Fraud SMS Classification -- 5 Experiments -- 5.1 Dataset and Experiments Setting -- 5.2 Comparison of Different Algorithms -- 5.3 Ablation Experiment -- 6 Conclusion -- References -- Vulnerability Detection -- Research Towards Key Issues of API Security -- 1 Introduction -- 2 API Asset Discovery Based on Traffic -- 3 API Vulnerability Detection Method -- 3.1 API Security Audit Based on Data Flow Tracing -- 3.2 Finite State Machine Model of Interaction by API -- 3.3 Demonstration -- 3.4 Relationship Between FSM Testing and Data Flow Taint Analysis -- 4 API Security Audit System Based on Traffic -- 4.1 Research Ideas -- 4.2 System Framework Design -- 4.3 Key Techniques -- 5 Opportunities and Challenges -- 6 Conclusion -- References -- Smart Contract Vulnerability Detection Based on Symbolic Execution Technology -- 1 Introduction -- 2 Related Work -- 3 Background -- 3.1 Reentrancy Vulnerability -- 3.2 Integer Overflow Vulnerability -- 3.3 Unchecked Call Return Value Vulnerability -- 4 Vulnerability Detection Methods -- 4.1 Control Flow Generation -- 4.2 Symbolic Execution -- 4.3 Vulnerability Detection -- 4.4 Constraint Solving -- 5 Evalution -- 6 Conclusion -- References -- Text Classification -- A Multi-task Text Classification Model Based on Label Embedding Learning -- 1 Introduction -- 2 Related Work and Background -- 2.1 Text Classification -- 2.2 Attention Mechanism -- 3 Methodology of Text Classification Model -- 3.1 Framework Overview -- 3.2 Problem Statement -- 3.3 Attention Learning on Word Embedding -- 3.4 Attention Learning on Modified TF-IDF Matrix -- 4 Experiment Evaluation -- 4.1 Dataset and Parameter Settings -- 4.2 Experiment Result -- 4.3 Text Classification Visualization Analysis -- 5 Conclusion -- References -- A Review of Machine Learning Algorithms for Text Classification.

1 Introduction -- 2 Principles of Machine Learning Algorithms -- 2.1 Naive Bayes -- 2.2 Supporting Vector Machine (SVM) -- 2.3 Decision Tree -- 2.4 KNN (K-Nearest Neighbor) -- 2.5 Random Forest -- 2.6 Neural Network -- 3 Comparative Study of the Machine Learning Algorithms -- 4 Conclusion -- References -- Author Index.