Guozhu Meng

Orcid: 0000-0001-6388-2571

According to our database1, Guozhu Meng authored at least 69 papers between 2013 and 2024.

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Bibliography

2024
Revealing the exploitability of heap overflow through PoC analysis.
Cybersecur., December, 2024

A Survey on Physical Adversarial Attacks against Face Recognition Systems.
CoRR, 2024

Deep Learning-based Software Engineering: Progress, Challenges, and Opportunities.
CoRR, 2024

Dormant: Defending against Pose-driven Human Image Animation.
CoRR, 2024

AuthNet: Neural Network with Integrated Authentication Logic.
CoRR, 2024

Evaluating Decision Optimality of Autonomous Driving via Metamorphic Testing.
CoRR, 2024

Making Them Ask and Answer: Jailbreaking Large Language Models in Few Queries via Disguise and Reconstruction.
Proceedings of the 33rd USENIX Security Symposium, 2024

SSL-WM: A Black-Box Watermarking Approach for Encoders Pre-trained by Self-Supervised Learning.
Proceedings of the 31st Annual Network and Distributed System Security Symposium, 2024

Demystifying RCE Vulnerabilities in LLM-Integrated Apps.
Proceedings of the 2024 on ACM SIGSAC Conference on Computer and Communications Security, 2024

DataElixir: Purifying Poisoned Dataset to Mitigate Backdoor Attacks via Diffusion Models.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
Are our clone detectors good enough? An empirical study of code effects by obfuscation.
Cybersecur., December, 2023

SkillSim: voice apps similarity detection.
Cybersecur., December, 2023

GraphSearchNet: Enhancing GNNs via Capturing Global Dependencies for Semantic Code Search.
IEEE Trans. Software Eng., April, 2023

ConFL: Constraint-guided Fuzzing for Machine Learning Framework.
CoRR, 2023

Aliasing Backdoor Attacks on Pre-trained Models.
Proceedings of the 32nd USENIX Security Symposium, 2023

Differential Testing of Cross Deep Learning Framework APIs: Revealing Inconsistencies and Vulnerabilities.
Proceedings of the 32nd USENIX Security Symposium, 2023

Fairness via Group Contribution Matching.
Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

ContraBERT: Enhancing Code Pre-trained Models via Contrastive Learning.
Proceedings of the 45th IEEE/ACM International Conference on Software Engineering, 2023

FMDiv: Functional Module Division on Binary Malware for Accurate Malicious Code Localization.
Proceedings of the 26th International Conference on Computer Supported Cooperative Work in Design, 2023

Good-looking but Lacking Faithfulness: Understanding Local Explanation Methods through Trend-based Testing.
Proceedings of the 2023 ACM SIGSAC Conference on Computer and Communications Security, 2023

2022
Towards Security Threats of Deep Learning Systems: A Survey.
IEEE Trans. Software Eng., 2022

MalRadar: Demystifying Android Malware in the New Era.
Proc. ACM Meas. Anal. Comput. Syst., 2022

The inconsistency of documentation: a study of online C standard library documents.
Cybersecur., 2022

Learning Program Semantics with Code Representations: An Empirical Study.
Proceedings of the IEEE International Conference on Software Analysis, 2022

TraceDroid: A Robust Network Traffic Analysis Framework for Privacy Leakage in Android Apps.
Proceedings of the Science of Cyber Security - 4th International Conference, 2022

TransRepair: Context-aware Program Repair for Compilation Errors.
Proceedings of the 37th IEEE/ACM International Conference on Automated Software Engineering, 2022

Message from the RAIS 2022 Chairs.
Proceedings of the IEEE International Symposium on Software Reliability Engineering Workshops, 2022

Automated Privacy Network Traffic Detection via Self-labeling and Learning.
Proceedings of the IEEE Symposium on Computers and Communications, 2022

LibHunter: An Unsupervised Approach for Third-party Library Detection without Prior Knowledge.
Proceedings of the IEEE Symposium on Computers and Communications, 2022

Detecting API Missing-Check Bugs Through Complete Cross Checking of Erroneous Returns.
Proceedings of the Information Security and Cryptology - 18th International Conference, 2022

Understanding Real-world Threats to Deep Learning Models in Android Apps.
Proceedings of the 2022 ACM SIGSAC Conference on Computer and Communications Security, 2022

2021
A Performance-Sensitive Malware Detection System Using Deep Learning on Mobile Devices.
IEEE Trans. Inf. Forensics Secur., 2021

DeepObliviate: A Powerful Charm for Erasing Data Residual Memory in Deep Neural Networks.
CoRR, 2021

SEPAL: Towards a Large-scale Analysis of SEAndroid Policy Customization.
Proceedings of the WWW '21: The Web Conference 2021, 2021

Have You been Properly Notified? Automatic Compliance Analysis of Privacy Policy Text with GDPR Article 13.
Proceedings of the WWW '21: The Web Conference 2021, 2021

DRMI: A Dataset Reduction Technology based on Mutual Information for Black-box Attacks.
Proceedings of the 30th USENIX Security Symposium, 2021

Vall-nut: Principled Anti-Grey box - Fuzzing.
Proceedings of the 32nd IEEE International Symposium on Software Reliability Engineering, 2021

Why is Your Trojan NOT Responding? A Quantitative Analysis of Failures in Backdoor Attacks of Neural Networks.
Proceedings of the Algorithms and Architectures for Parallel Processing, 2021

2020
Large-Scale Empirical Studies on Effort-Aware Security Vulnerability Prediction Methods.
IEEE Trans. Reliab., 2020

A3Ident: A Two-phased Approach to Identify the Leading Authors of Android Apps.
CoRR, 2020

A<sup>3</sup>Ident: A Two-phased Approach to Identify the Leading Authors of Android Apps.
Proceedings of the IEEE International Conference on Software Maintenance and Evolution, 2020

A large-scale empirical study on vulnerability distribution within projects and the lessons learned.
Proceedings of the ICSE '20: 42nd International Conference on Software Engineering, Seoul, South Korea, 27 June, 2020

An empirical assessment of security risks of global Android banking apps.
Proceedings of the ICSE '20: 42nd International Conference on Software Engineering, Seoul, South Korea, 27 June, 2020

2019
Securing Android App Markets via Modeling and Predicting Malware Spread Between Markets.
IEEE Trans. Inf. Forensics Secur., 2019

Towards Privacy and Security of Deep Learning Systems: A Survey.
CoRR, 2019

Securing android applications via edge assistant third-party library detection.
Comput. Secur., 2019

Characterizing Android App Signing Issues.
Proceedings of the 34th IEEE/ACM International Conference on Automated Software Engineering, 2019

Learning Performance Optimization from Code Changes for Android Apps.
Proceedings of the 2019 IEEE International Conference on Software Testing, 2019

MobiDroid: A Performance-Sensitive Malware Detection System on Mobile Platform.
Proceedings of the 24th International Conference on Engineering of Complex Computer Systems, 2019

RoLMA: A Practical Adversarial Attack Against Deep Learning-Based LPR Systems.
Proceedings of the Information Security and Cryptology - 15th International Conference, 2019

2018
DroidEcho: an in-depth dissection of malicious behaviors in Android applications.
Cybersecur., 2018

AUSERA: Large-Scale Automated Security Risk Assessment of Global Mobile Banking Apps.
CoRR, 2018

Are mobile banking apps secure? what can be improved?
Proceedings of the 2018 ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering, 2018

Efficiently manifesting asynchronous programming errors in Android apps.
Proceedings of the 33rd ACM/IEEE International Conference on Automated Software Engineering, 2018

Large-scale analysis of framework-specific exceptions in Android apps.
Proceedings of the 40th International Conference on Software Engineering, 2018

From UI design image to GUI skeleton: a neural machine translator to bootstrap mobile GUI implementation.
Proceedings of the 40th International Conference on Software Engineering, 2018

SoProtector: Securing Native C/C++ Libraries for Mobile Applications.
Proceedings of the Algorithms and Architectures for Parallel Processing, 2018

2017
A semantic-based analysis of Android malware for detection, generation, and trend analysis
PhD thesis, 2017

Battery-Aware Mobile Data Service.
IEEE Trans. Mob. Comput., 2017

Auditing Anti-Malware Tools by Evolving Android Malware and Dynamic Loading Technique.
IEEE Trans. Inf. Forensics Secur., 2017

AndroVault: Constructing Knowledge Graph from Millions of Android Apps for Automated Analysis.
CoRR, 2017

Guided, stochastic model-based GUI testing of Android apps.
Proceedings of the 2017 11th Joint Meeting on Foundations of Software Engineering, 2017

Mining implicit design templates for actionable code reuse.
Proceedings of the 32nd IEEE/ACM International Conference on Automated Software Engineering, 2017

Battery state-of-health estimation for mobile devices.
Proceedings of the 8th International Conference on Cyber-Physical Systems, 2017

2016
Semantic modelling of Android malware for effective malware comprehension, detection, and classification.
Proceedings of the 25th International Symposium on Software Testing and Analysis, 2016

Contextual Weisfeiler-Lehman graph kernel for malware detection.
Proceedings of the 2016 International Joint Conference on Neural Networks, 2016

Mystique: Evolving Android Malware for Auditing Anti-Malware Tools.
Proceedings of the 11th ACM on Asia Conference on Computer and Communications Security, 2016

2015
Collaborative Security: A Survey and Taxonomy.
ACM Comput. Surv., 2015

2013
AUTHSCAN: Automatic Extraction of Web Authentication Protocols from Implementations.
Proceedings of the 20th Annual Network and Distributed System Security Symposium, 2013


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