Zobrazeno 1 - 10
of 4 332
pro vyhledávání: '"Khalil, Ibrahim A"'
Autor:
Edirimannage, Shehan, Elvitigala, Charitha, Don, Asitha Kottahachchi Kankanamge, Daluwatta, Wathsara, Wijesekara, Primal, Khalil, Ibrahim
With the wave of high-profile supply chain attacks targeting development and client organizations, supply chain security has recently become a focal point. As a result, there is an elevated discussion on securing the development environment and incre
Externí odkaz:
http://arxiv.org/abs/2411.07479
The right to be forgotten mandates that machine learning models enable the erasure of a data owner's data and information from a trained model. Removing data from the dataset alone is inadequate, as machine learning models can memorize information fr
Externí odkaz:
http://arxiv.org/abs/2410.10128
In the context of machine unlearning, the primary challenge lies in effectively removing traces of private data from trained models while maintaining model performance and security against privacy attacks like membership inference attacks. Traditiona
Externí odkaz:
http://arxiv.org/abs/2406.16986
Autor:
Khalil Ibrahim, Ghada Abd El Wahab1, Elaidy, Shaimaa A.1 shaimaaelaidy@yahoo.com, Aly Ghonemy, Mohamed Hanafy1
Publikováno v:
Zagazig University Medical Journal. Jul2024, Vol. 30 Issue 4, p1346-1353. 8p.
Autor:
Ismail, Mohamed hamdy1, Khalil Ibrahim, Ghada Abd El Wahab1, Elaidy, Shaimaa A.1 shaimaaelaidy@yahoo.com
Publikováno v:
Zagazig University Medical Journal. Oct2024, Vol. 30 Issue 7, p3298-3307. 10p.
Publikováno v:
ACM Symposium on Information, Computer and Communications Security (ASIA CCS 2023)
Since the beginning of this decade, several incidents report that false data injection attacks targeting intelligent connected vehicles cause huge industrial damage and loss of lives. Data Theft, Flooding, Fuzzing, Hijacking, Malware Spoofing and Adv
Externí odkaz:
http://arxiv.org/abs/2308.09237
Publikováno v:
IEEE Internet of Things Journal, vol. 10, no. 5, pp. 3763-3773, 1 March1, 2023
We propose a privacy-preserving ensemble infused enhanced Deep Neural Network (DNN) based learning framework in this paper for Internet-of-Things (IoT), edge, and cloud convergence in the context of healthcare. In the convergence, edge server is used
Externí odkaz:
http://arxiv.org/abs/2305.09224
Publikováno v:
IEEE Transactions on Industrial Informatics, 2022
The advancement of Internet and Communication Technologies (ICTs) has led to the era of Industry 4.0. This shift is followed by healthcare industries creating the term Healthcare 4.0. In Healthcare 4.0, the use of IoT-enabled medical imaging devices
Externí odkaz:
http://arxiv.org/abs/2305.09209
Publikováno v:
IEEE Transactions on Network and Service Management, 2023
The widespread adoption of Internet of Things (IoT) devices in smart cities, intelligent healthcare systems, and various real-world applications have resulted in the generation of vast amounts of data, often analyzed using different Machine Learning
Externí odkaz:
http://arxiv.org/abs/2305.09134
Publikováno v:
Network and System Security: 16th International Conference, NSS 2022, Denarau Island, Fiji, December, 2022
Smart manufacturing systems involve a large number of interconnected devices resulting in massive data generation. Cloud computing technology has recently gained increasing attention in smart manufacturing systems for facilitating cost-effective serv
Externí odkaz:
http://arxiv.org/abs/2304.13379