Ahmed Abusnaina

Orcid: 0000-0001-5032-3412

According to our database1, Ahmed Abusnaina authored at least 33 papers between 2019 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2023
Burning the Adversarial Bridges: Robust Windows Malware Detection Against Binary-level Mutations.
CoRR, 2023

Measuring and Modeling the Free Content Web.
CoRR, 2023

2022
Cleaning the NVD: Comprehensive Quality Assessment, Improvements, and Analyses.
IEEE Trans. Dependable Secur. Comput., 2022

DL-FHMC: Deep Learning-Based Fine-Grained Hierarchical Learning Approach for Robust Malware Classification.
IEEE Trans. Dependable Secur. Comput., 2022

ShellCore: Automating Malicious IoT Software Detection Using Shell Commands Representation.
IEEE Internet Things J., 2022

Systematically Evaluating the Robustness of ML-based IoT Malware Detection Systems.
Proceedings of the 25th International Symposium on Research in Attacks, 2022

2021
Sensor-Based Continuous Authentication of Smartphones' Users Using Behavioral Biometrics: A Contemporary Survey.
IEEE Internet Things J., 2021

ML-based IoT Malware Detection Under Adversarial Settings: A Systematic Evaluation.
CoRR, 2021

ShellCore: Automating Malicious IoT Software Detection by Using Shell Commands Representation.
CoRR, 2021

Hate, Obscenity, and Insults: Measuring the Exposure of Children to Inappropriate Comments in YouTube.
Proceedings of the Companion of The Web Conference 2021, 2021

TLDR: Deep Learning-Based Automated Privacy Policy Annotation with Key Policy Highlights.
Proceedings of the WPES '21: Proceedings of the 20th Workshop on Workshop on Privacy in the Electronic Society, 2021

Adversarial Example Detection Using Latent Neighborhood Graph.
Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

Systemically Evaluating the Robustness of ML-based IoT Malware Detectors.
Proceedings of the 51st Annual IEEE/IFIP International Conference on Dependable Systems and Networks, 2021

Automated Privacy Policy Annotation with Information Highlighting Made Practical Using Deep Representations.
Proceedings of the CCS '21: 2021 ACM SIGSAC Conference on Computer and Communications Security, Virtual Event, Republic of Korea, November 15, 2021

2020
A Deep Learning-based Fine-grained Hierarchical Learning Approach for Robust Malware Classification.
CoRR, 2020

Sensor-based Continuous Authentication of Smartphones' Users Using Behavioral Biometrics: A Survey.
CoRR, 2020

Understanding the Proxy Ecosystem: A Comparative Analysis of Residential and Open Proxies on the Internet.
IEEE Access, 2020

Insights into Attacks' Progression: Prediction of Spatio-Temporal Behavior of DDoS Attacks.
Proceedings of the Information Security Applications - 21st International Conference, 2020

From Blue-Sky to Practical Adversarial Learning.
Proceedings of the Second IEEE International Conference on Trust, 2020

DFD: Adversarial Learning-based Approach to Defend Against Website Fingerprinting.
Proceedings of the 39th IEEE Conference on Computer Communications, 2020

Hiding in Plain Sight: A Measurement and Analysis of Kids' Exposure to Malicious URLs on YouTube.
Proceedings of the 5th IEEE/ACM Symposium on Edge Computing, 2020

Soteria: Detecting Adversarial Examples in Control Flow Graph-based Malware Classifiers.
Proceedings of the 40th IEEE International Conference on Distributed Computing Systems, 2020

An Analysis of Users Engagement on Twitter During the COVID-19 Pandemic: Topical Trends and Sentiments.
Proceedings of the Computational Data and Social Networks - 9th International Conference, 2020

Investigating Online Toxicity in Users Interactions with the Mainstream Media Channels on YouTube.
Proceedings of the CIKM 2020 Workshops co-located with 29th ACM International Conference on Information and Knowledge Management (CIKM 2020), 2020

2019
Analyzing and Detecting Emerging Internet of Things Malware: A Graph-Based Approach.
IEEE Internet Things J., 2019

COPYCAT: Practical Adversarial Attacks on Visualization-Based Malware Detection.
CoRR, 2019

Examining Adversarial Learning against Graph-based IoT Malware Detection Systems.
CoRR, 2019

Breaking graph-based IoT malware detection systems using adversarial examples: poster.
Proceedings of the 12th Conference on Security and Privacy in Wireless and Mobile Networks, 2019

Adversarial Learning Attacks on Graph-based IoT Malware Detection Systems.
Proceedings of the 39th IEEE International Conference on Distributed Computing Systems, 2019

Honor among Thieves: Towards Understanding the Dynamics and Interdependencies in IoT Botnets.
Proceedings of the 2019 IEEE Conference on Dependable and Secure Computing, 2019

Examining the Robustness of Learning-Based DDoS Detection in Software Defined Networks.
Proceedings of the 2019 IEEE Conference on Dependable and Secure Computing, 2019

Subgraph-Based Adversarial Examples Against Graph-Based IoT Malware Detection Systems.
Proceedings of the Computational Data and Social Networks - 8th International Conference, 2019

Examining the Security of DDoS Detection Systems in Software Defined Networks.
Proceedings of the 15th International Conference on emerging Networking EXperiments and Technologies, 2019


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