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.