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Information and communications security [electronic resource] : 21st International Conference, ICICS 2019, Beijing, China, December 15-17, 2019, Revised Selected Papers / Jianying Zhou, Xiapu Luo, Qingni Shen, Zhen Xu (eds.).

By: (21st : ICICS (Conference) (21st : 2019 : Beijing, China)Contributor(s): Zhou, Jianying | Luo, Xiapu | Shen, Qingni | Xu, ZhenMaterial type: TextTextSeries: Serienbezeichnung | Lecture notes in computer science ; 11999. | LNCS sublibrary. SL 4, Security and cryptology.Publication details: Cham : Springer, 2020. Description: 1 online resource (834 p.)Content type: text Media type: computer Carrier type: online resourceISBN: 9783030415792; 3030415791Other title: ICICS 2019Subject(s): Cryptography -- Congresses | Computer security -- Congresses | Telecommunication -- Security measures -- Congresses | Telecommunication -- Security measures | Cryptography | Computer security | Application software | Computer networks | Computers | Data protection | Data structures (Computer science) | Software engineeringGenre/Form: Conference papers and proceedings. | Electronic books. Additional physical formats: Print version:: Information and Communications Security : 21st International Conference, ICICS 2019, Beijing, China, December 15-17, 2019, Revised Selected PapersDDC classification: 005.8 | 005.73 LOC classification: QA76.9.A25Online resources: Click here to access online
Contents:
Intro -- Preface -- Organization -- Contents -- Malware Analysis and Detection -- Prototype-Based Malware Traffic Classification with Novelty Detection -- 1 Introduction -- 2 Related Work -- 2.1 Malware Traffic Detection and Classification -- 2.2 Prototype Learning -- 3 Proposed Approach -- 3.1 Problem Formalization -- 3.2 Approach Overview -- 3.3 Objective Function Definition -- 3.4 Novel Class Detection -- 4 Experimental Evaluation -- 4.1 Datasets -- 4.2 Implementation Details -- 4.3 Evaluation Metrics -- 4.4 Evaluation Results and Comparisons -- 5 Conclusion -- References
Evading API Call Sequence Based Malware Classifiers -- 1 Introduction -- 1.1 Problem Statement -- 1.2 Contribution of This Work -- 2 Proposed Methodology -- 2.1 Preparing Target Models -- 2.2 Evasion of Target Model -- 3 Experimental Results and Comparison -- 3.1 Feature Level Evasion Results -- 3.2 Executable Level Evasion Results -- 3.3 Comparison to Previous Work -- 3.4 Adversarial Retraining -- 4 Related Work -- 5 Conclusion and Future Work -- References -- UBER: Combating Sandbox Evasion via User Behavior Emulators -- 1 Introduction -- 2 Threat Model -- 3 System Design -- 3.1 Data Collector
3.2 User Profile Generator -- 3.3 Artifact Generation OS -- 3.4 Malware Sandbox Analysis OS -- 3.5 Scheduler -- 4 Implementation -- 5 Evaluation -- 5.1 Artifacts Difference -- 5.2 Measurement -- 5.3 Comparison with Other Mitigation Solutions -- 6 Limitations and Discussions -- 7 Related Work -- 8 Conclusion -- References -- IoT and CPS Security -- AADS: A Noise-Robust Anomaly Detection Framework for Industrial Control Systems -- 1 Introduction -- 2 Related Work -- 3 Problem Statement -- 4 The AADS Framework -- 4.1 Anomaly Detection in Sensors -- 4.2 Anomaly Detection in Actuators
4.3 Detection Logic -- 4.4 Few-Time-Steps Learning -- 4.5 Threshold Selection -- 5 Experimental Evaluation -- 5.1 Experimental Setup -- 5.2 Methodology -- 5.3 Experiment 1: Detection Accuracy -- 5.4 Experiment 2: Additive Noise on the Test Set -- 5.5 Experiment 3: Additive Noise on both Training and Test Sets -- 6 Conclusion -- Appendix A Point Recall Comparison -- References -- Characterizing Internet-Scale ICS Automated Attacks Through Long-Term Honeypot Data -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Honeypot Architecture
3.2 Preprogressing Algorithm and Request Entropy Model -- 3.3 Markov Chain Representation of the Attack Pattern -- 4 Results -- 4.1 General Overview -- 4.2 Packets Classification and Inference -- 5 Attack Patterns on ICS-Related Ports -- 5.1 Common Attacks Around ICS-Related Ports -- 5.2 Proprietary Attacks Based on Well-Known Industrial Protocols -- 5.3 Proprietary Attacks Based on Private Protocols -- 6 Conclusion -- References -- Cloning Vulnerability Detection in Driver Layer of IoT Devices -- 1 Introduction -- 2 Background -- 2.1 Code Clone Detection -- 2.2 Program Slicing -- 3 Method
Summary: This book constitutes the refereed proceedings of the 21th International Conference on Information and Communications Security, ICICS 2019, held in Beijing, China, in December 2019. The 47 revised full papers were carefully selected from 199 submissions. The papers are organized in topics on malware analysis and detection, IoT and CPS security enterprise network security, software security, system security, authentication, applied cryptograph internet security, machine learning security, machine learning privacy, Web security, steganography and steganalysis. -- Provided by publisher.
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Description based upon print version of record.

Intro -- Preface -- Organization -- Contents -- Malware Analysis and Detection -- Prototype-Based Malware Traffic Classification with Novelty Detection -- 1 Introduction -- 2 Related Work -- 2.1 Malware Traffic Detection and Classification -- 2.2 Prototype Learning -- 3 Proposed Approach -- 3.1 Problem Formalization -- 3.2 Approach Overview -- 3.3 Objective Function Definition -- 3.4 Novel Class Detection -- 4 Experimental Evaluation -- 4.1 Datasets -- 4.2 Implementation Details -- 4.3 Evaluation Metrics -- 4.4 Evaluation Results and Comparisons -- 5 Conclusion -- References

Evading API Call Sequence Based Malware Classifiers -- 1 Introduction -- 1.1 Problem Statement -- 1.2 Contribution of This Work -- 2 Proposed Methodology -- 2.1 Preparing Target Models -- 2.2 Evasion of Target Model -- 3 Experimental Results and Comparison -- 3.1 Feature Level Evasion Results -- 3.2 Executable Level Evasion Results -- 3.3 Comparison to Previous Work -- 3.4 Adversarial Retraining -- 4 Related Work -- 5 Conclusion and Future Work -- References -- UBER: Combating Sandbox Evasion via User Behavior Emulators -- 1 Introduction -- 2 Threat Model -- 3 System Design -- 3.1 Data Collector

3.2 User Profile Generator -- 3.3 Artifact Generation OS -- 3.4 Malware Sandbox Analysis OS -- 3.5 Scheduler -- 4 Implementation -- 5 Evaluation -- 5.1 Artifacts Difference -- 5.2 Measurement -- 5.3 Comparison with Other Mitigation Solutions -- 6 Limitations and Discussions -- 7 Related Work -- 8 Conclusion -- References -- IoT and CPS Security -- AADS: A Noise-Robust Anomaly Detection Framework for Industrial Control Systems -- 1 Introduction -- 2 Related Work -- 3 Problem Statement -- 4 The AADS Framework -- 4.1 Anomaly Detection in Sensors -- 4.2 Anomaly Detection in Actuators

4.3 Detection Logic -- 4.4 Few-Time-Steps Learning -- 4.5 Threshold Selection -- 5 Experimental Evaluation -- 5.1 Experimental Setup -- 5.2 Methodology -- 5.3 Experiment 1: Detection Accuracy -- 5.4 Experiment 2: Additive Noise on the Test Set -- 5.5 Experiment 3: Additive Noise on both Training and Test Sets -- 6 Conclusion -- Appendix A Point Recall Comparison -- References -- Characterizing Internet-Scale ICS Automated Attacks Through Long-Term Honeypot Data -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Honeypot Architecture

3.2 Preprogressing Algorithm and Request Entropy Model -- 3.3 Markov Chain Representation of the Attack Pattern -- 4 Results -- 4.1 General Overview -- 4.2 Packets Classification and Inference -- 5 Attack Patterns on ICS-Related Ports -- 5.1 Common Attacks Around ICS-Related Ports -- 5.2 Proprietary Attacks Based on Well-Known Industrial Protocols -- 5.3 Proprietary Attacks Based on Private Protocols -- 6 Conclusion -- References -- Cloning Vulnerability Detection in Driver Layer of IoT Devices -- 1 Introduction -- 2 Background -- 2.1 Code Clone Detection -- 2.2 Program Slicing -- 3 Method

3.1 Overall Structure

This book constitutes the refereed proceedings of the 21th International Conference on Information and Communications Security, ICICS 2019, held in Beijing, China, in December 2019. The 47 revised full papers were carefully selected from 199 submissions. The papers are organized in topics on malware analysis and detection, IoT and CPS security enterprise network security, software security, system security, authentication, applied cryptograph internet security, machine learning security, machine learning privacy, Web security, steganography and steganalysis. -- Provided by publisher.

Includes author index.

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