Zobrazeno 1 - 10 of 37 pro vyhledávání: '"Rhongho Jang"'
1
Akademický článek
Investigating the Effect of Traffic Sampling on Machine Learning-Based Network Intrusion Detection Approaches
Autor: Jumabek Alikhanov, Rhongho Jang, Mohammed Abuhamad, David Mohaisen, Daehun Nyang, Youngtae Noh
Publikováno v: IEEE Access, Vol 10, Pp 5801-5823 (2022)
Machine Learning (ML) based Network Intrusion Systems (NIDSs) operate on flow features which are obtained from flow exporting protocols (i.e., NetFlow). Recent success of ML and Deep Learning (DL) based NIDS solutions assume such flow information (e.
Externí odkaz: https://doaj.org/article/fc1c19fed78949fcb6af33d98885b242
Zobrazit plný text záznamu
2
A One-Page Text Entry Method Optimized for Rectangle Smartwatches
Autor: DaeHun Nyang, Kyunghee Lee, Rhongho Jang, David Mohaisen, Changhun Jung
Publikováno v: IEEE Transactions on Mobile Computing. 21:3443-3454
In this paper, we provide the design and implementation of UOIT, a text entry method optimized for smartwatches. UOIT uses only one page where a user can see and tap directly for entry without any additional actions, such as zoom-in/zoom-out and swip
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::8143e7d70e91b7b3d7d4f5eea9af5649
https://doi.org/10.1109/tmc.2021.3057226
Zobrazit plný text záznamu
3
DL-FHMC: Deep Learning-Based Fine-Grained Hierarchical Learning Approach for Robust Malware Classification
Autor: Rhongho Jang, Afsah Anwar, DaeHun Nyang, David Mohaisen, Ahmed Abusnaina, Hisham Alasmary, Mohammed Abuhamad, Saeed Salem
Publikováno v: IEEE Transactions on Dependable and Secure Computing. 19:3432-3447
Given the limited scalability of dynamic analysis, static analysis, such as the use of Control Flow Graph (CFG)-based features, is widely used by machine learning algorithms for malware analysis and detection. However, recent studies have shown these
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::f3ac5da92b825402ebc8178bfa356856
https://doi.org/10.1109/tdsc.2021.3097296
Zobrazit plný text záznamu
9
Catch Me If You Can: Rogue Access Point Detection Using Intentional Channel Interference
Autor: DaeHun Nyang, Jeonil Kang, Aziz Mohaisen, Rhongho Jang
Publikováno v: IEEE Transactions on Mobile Computing. 19:1056-1071
In this paper, we introduce a powerful hardware-based rogue access point (PrAP), which can relay back and forth traffic between a legitimate AP and a wireless station, and act as a man-in-the-middle attacker. Our PrAP is built of two dedicated wirele
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::4528f3f44dbee746a3e4e79ad2216467
https://doi.org/10.1109/tmc.2019.2903052
Zobrazit plný text záznamu
10
Systemically Evaluating the Robustness of ML-based IoT Malware Detectors
Autor: Ahmed Abusnaina, Sultan S. Alshamrani, David Mohaisen, Rhongho Jang, DaeHun Nyang, Afsah Anwar, Abdulrahman Alabduljabbar
Publikováno v: DSN (Supplements)
The rapid growth of the Internet of Things (IoT) devices is paralleled by them being on the front-line of malicious attacks caused by malicious software. Machine learning (ML) algorithms, alongside the traditional signature-based methods, are typical
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::407041595c774f2ba95d340e09421514
https://doi.org/10.1109/dsn-s52858.2021.00012
Zobrazit plný text záznamu

Vyhledávací nástroje:

Upřesnit hledání

Omezení vyhledávání
Plný text Recenzováno Digitální knihovna AV ČR
Zdroje