Search Results for author:
Found 16 papers, 0 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.
Burning the Adversarial Bridges: Robust Windows Malware Detection Against Binary-level Mutations
Highlighting volatile information channels within the software, we introduce three software pre-processing steps to eliminate the attack surface, namely, padding removal, software stripping, and inter-section information resetting.
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.
Analyzing In-browser Cryptojacking
Cryptojacking is the permissionless use of a target device to covertly mine cryptocurrencies.
Learning Location from Shared Elevation Profiles in Fitness Apps: A Privacy Perspective
To preserve the privacy of users while allowing sharing, several of those platforms may allow users to disclose partial information, such as the elevation profile for an activity, which supposedly would not leak the location of the users.
Enriching Vulnerability Reports Through Automated and Augmented Description Summarization
Security incidents and data breaches are increasing rapidly, and only a fraction of them is being reported.
Self-Configurable Stabilized Real-Time Detection Learning for Autonomous Driving Applications
In addition, we demonstrate the self-configurable stabilized detection with YOLOv3-tiny and FlowNet2-S, which are the real-time object detection network and an optical flow estimation network, respectively.
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.
Automated Feature-Topic Pairing: Aligning Semantic and Embedding Spaces in Spatial Representation Learning
Texts of spatial entities, on the other hand, provide semantic understanding of latent feature labels, but is insensible to deep SRL models.
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.
Adversarial Example Detection Using Latent Neighborhood Graph
We present the first graph-based adversarial detection method that constructs a Latent Neighborhood Graph (LNG) around an input example to determine if the input example is adversarial.
On the Performance of Generative Adversarial Network (GAN) Variants: A Clinical Data Study
Generative Adversarial Network (GAN) is a useful type of Neural Networks in various types of applications including generative models and feature extraction.
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.
Computer Systems Have 99 Problems, Let's Not Make Machine Learning Another One
Machine learning techniques are finding many applications in computer systems, including many tasks that require decision making: network optimization, quality of service assurance, and security.
