Search Results for author:
Found 11 papers, 2 papers with code
Untargeted Code Authorship Evasion with Seq2Seq Transformation
Code authorship attribution is the problem of identifying authors of programming language codes through the stylistic features in their codes, a topic that recently witnessed significant interest with outstanding performance.
SHIELD: Thwarting Code Authorship Attribution
For the targeted attacks, we show the possibility of impersonating a programmer using targeted-adversarial perturbations with a success rate ranging from 66\% to 88\% for different authorship attribution techniques under several adversarial scenarios.
Robust Natural Language Processing: Recent Advances, Challenges, and Future Directions
Recent natural language processing (NLP) techniques have accomplished high performance on benchmark datasets, primarily due to the significant improvement in the performance of deep learning.
ML-based IoT Malware Detection Under Adversarial Settings: A Systematic Evaluation
Additionally, our analysis of the industry-standard malware detectors shows their instability to the malware mutations.
Hate, Obscenity, and Insults: Measuring the Exposure of Children to Inappropriate Comments in YouTube
Social media has become an essential part of the daily routines of children and adolescents.
Generating Adversarial Examples with an Optimized Quality
However, deep learning models are vulnerable to Adversarial Examples (AEs), carefully crafted samples to deceive those models.
Sensor-based Continuous Authentication of Smartphones' Users Using Behavioral Biometrics: A Contemporary Survey
This task is made possible with today's smartphones' embedded sensors that enable continuous and implicit user authentication by capturing behavioral biometrics and traits.
W-Net: A CNN-based Architecture for White Blood Cells Image Classification
Computer-aided methods for analyzing white blood cells (WBC) have become widely popular due to the complexity of the manual process.
COPYCAT: Practical Adversarial Attacks on Visualization-Based Malware Detection
Therefore, we proposed an approach to generate adversarial examples, COPYCAT, which is specifically designed for malware detection systems considering two main goals; achieving a high misclassification rate and maintaining the executability and functionality of the original input.
Exploring the Attack Surface of Blockchain: A Systematic Overview
In this paper, we systematically explore the attack surface of the Blockchain technology, with an emphasis on public Blockchains.
Cryptography and Security
A survey on deep packet inspection for intrusion detection systems
Deep packet inspection is widely recognized as a powerful way which is used for intrusion detection systems for inspecting, deterring and deflecting malicious at- tacks over the network.
