no code implementations • 26 Nov 2023 • Soohyeon Choi, RhongHo Jang, DaeHun Nyang, David Mohaisen
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.
no code implementations • 5 Oct 2023 • Ahmed Abusnaina, Yizhen Wang, Sunpreet Arora, Ke Wang, Mihai Christodorescu, David Mohaisen
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.
no code implementations • 26 Apr 2023 • Muhammad Saad, David Mohaisen
Cryptojacking is the permissionless use of a target device to covertly mine cryptocurrencies.
no code implementations • 26 Apr 2023 • Mohammed Abuhamad, Changhun Jung, David Mohaisen, DaeHun Nyang
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.
no code implementations • 27 Oct 2022 • Ulku Meteriz-Yildiran, Necip Fazil Yildiran, Joongheon Kim, David Mohaisen
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.
no code implementations • 3 Oct 2022 • Hattan Althebeiti, David Mohaisen
Security incidents and data breaches are increasing rapidly, and only a fraction of them is being reported.
no code implementations • 29 Sep 2022 • Won Joon Yun, Soohyun Park, Joongheon Kim, David Mohaisen
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.
no code implementations • 3 Jan 2022 • marwan omar, Soohyeon Choi, DaeHun Nyang, David Mohaisen
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.
no code implementations • 22 Sep 2021 • Dongjie Wang, Kunpeng Liu, David Mohaisen, Pengyang Wang, Chang-Tien Lu, Yanjie Fu
Texts of spatial entities, on the other hand, provide semantic understanding of latent feature labels, but is insensible to deep SRL models.
no code implementations • 30 Aug 2021 • Ahmed Abusnaina, Afsah Anwar, Sultan Alshamrani, Abdulrahman Alabduljabbar, RhongHo Jang, DaeHun Nyang, David Mohaisen
Additionally, our analysis of the industry-standard malware detectors shows their instability to the malware mutations.
no code implementations • 3 Mar 2021 • Sultan Alshamrani, Ahmed Abusnaina, Mohammed Abuhamad, DaeHun Nyang, David Mohaisen
Social media has become an essential part of the daily routines of children and adolescents.
no code implementations • ICCV 2021 • Ahmed Abusnaina, Yuhang Wu, Sunpreet Arora, Yizhen Wang, Fei Wang, Hao Yang, David Mohaisen
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.
no code implementations • 21 Sep 2020 • Jaesung Yoo, Jeman Park, An Wang, David Mohaisen, Joongheon Kim
Generative Adversarial Network (GAN) is a useful type of Neural Networks in various types of applications including generative models and feature extraction.
no code implementations • 30 Jun 2020 • Aminollah Khormali, DaeHun Nyang, David Mohaisen
However, deep learning models are vulnerable to Adversarial Examples (AEs), carefully crafted samples to deceive those models.
no code implementations • 23 Jan 2020 • Mohammed Abuhamad, Ahmed Abusnaina, DaeHun Nyang, David Mohaisen
This task is made possible with today's smartphones' embedded sensors that enable continuous and implicit user authentication by capturing behavioral biometrics and traits.
no code implementations • 28 Nov 2019 • David Mohaisen, Songqing Chen
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.