Alsharif (Sharif) Abuadbba
Alsharif (Sharif) Abuadbba
Team Leader - CSIRO's Data61, Australia
Verified email at - Homepage
Cited by
Cited by
End-to-end evaluation of federated learning and split learning for Internet of Things
Y Gao, M Kim, A Abuadbba, Y Kim, C Thapa, K Kim, SA Camtepe, H Kim, ...
2020 International Symposium on Reliable Distributed Systems (SRDS), 2020
Can We Use Split Learning on 1D CNN Models for Privacy Preserving Training?
A Abuadbba, K Kim, M Kim, C Thapa, SA Camtepe, Y Gao, H Kim, ...
Proceedings of the 15th ACM AsiaCCS, 305-318, 2020
Hybrid cryptographic access control for cloud-based EHR systems
U Premarathne, A Abuadbba, A Alabdulatif, I Khalil, Z Tari, A Zomaya, ...
IEEE Cloud Computing 3 (4), 58-64, 2016
Evaluation and Optimization of Distributed Machine Learning Techniques for Internet of Things
Y Gao, M Kim, C Thapa, A Abuadbba, Z Zhang, S Camtepe, H Kim, ...
IEEE Transactions on Computers, 2021
Data conversion systems and methods
SA Fernandez, B Conway, D Conway, DJ Gotrik, A Ibaida, ALS Dhiah, ...
US Patent 10,587,399, 2020
Walsh–Hadamard-based 3-D steganography for protecting sensitive information in point-of-care
A Abuadbba, I Khalil
IEEE Transactions on Biomedical Engineering 64 (9), 2186-2195, 2016
Gaussian approximation-based lossless compression of smart meter readings
A Abuadbba, I Khalil, X Yu
IEEE Transactions on Smart Grid 9 (5), 5047-5056, 2017
Energy-efficient hybrid routing protocol for IoT communication systems in 5G and beyond
M Baniata, HT Reda, N Chilamkurti, A Abuadbba
Sensors 21 (2), 537, 2021
Privacy-preserving compression model for efficient IoMT ECG sharing
A Ibaida, A Abuadbba, N Chilamkurti
Computer Communications 166, 1-8, 2021
Wavelet based steganographic technique to protect household confidential information and seal the transmitted smart grid readings
A Abuadbba, I Khalil
Information Systems 53, 224-236, 2015
Quantization backdoors to deep learning commercial frameworks
H Ma, H Qiu, Y Gao, Z Zhang, A Abuadbba, M Xue, A Fu, J Zhang, ...
IEEE Transactions on Dependable and Secure Computing, 2023
Binarizing split learning for data privacy enhancement and computation reduction
ND Pham, A Abuadbba, Y Gao, TK Phan, N Chilamkurti
IEEE Transactions on Information Forensics and Security, 2023
Dangerous cloaking: Natural trigger based backdoor attacks on object detectors in the physical world
H Ma, Y Li, Y Gao, A Abuadbba, Z Zhang, A Fu, H Kim, SF Al-Sarawi, ...
arXiv preprint arXiv:2201.08619, 2022
Towards IoT Security Automation and Orchestration
Y Zheng, A Pal, A Abuadbba, SR Pokhrel, S Nepal, H Janicke
2020 Second IEEE International Conference on Trust, Privacy and Security in …, 2020
Robust privacy preservation and authenticity of the collected data in cognitive radio network—Walsh–Hadamard based steganographic approach
A Abuadbba, I Khalil, M Atiquzzaman
Pervasive and Mobile Computing 22, 58-70, 2015
Reliability and robustness analysis of machine learning based phishing url detectors
B Sabir, MA Babar, R Gaire, A Abuadbba
IEEE Transactions on Dependable and Secure Computing, 2022
Cost-effective authenticated data redaction with privacy protection in IoT
F Zhu, X Yi, A Abuadbba, I Khalil, S Nepal, X Huang
IEEE Internet of Things Journal 8 (14), 11678-11689, 2021
Can differential privacy practically protect collaborative deep learning inference for IoT?
J Ryu, Y Zheng, Y Gao, A Abuadbba, J Kim, D Won, S Nepal, H Kim, ...
Wireless Networks, 1-21, 2022
DeepCapture: Image Spam Detection Using Deep Learning and Data Augmentation
B Kim, A Abuadbba, H Kim
Australasian Conference on Information Security and Privacy, 461-475, 2020
Resilient to shared spectrum noise scheme for protecting cognitive radio smart grid readings− BCH based steganographic approach
A Abuadbba, I Khalil, A Ibaida, M Atiquzzaman
Ad Hoc Networks 41, 30-46, 2016
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