Zobrazeno 1 - 10
of 16
pro vyhledávání: '"Muhammad Umar Janjua"'
Publikováno v:
IEEE Open Journal of the Computer Society, Vol 5, Pp 278-289 (2024)
Blockchain technology enables users to control and record their cryptocurrency transactions through the use of digital wallets. As the use of blockchain technology and cryptocurrency wallets continues to grow in popularity, the potential for attacks
Externí odkaz:
https://doaj.org/article/ab1ab48c549a463d98127b5cf2876455
Publikováno v:
IEEE Access, Vol 10, Pp 8163-8183 (2022)
Crowdsourcing is an effective technique that allows humans to solve complex problems that are hard to accomplish by automated tools. Some significant challenges in crowdsourcing systems include avoiding security attacks, effective trust management, a
Externí odkaz:
https://doaj.org/article/cc4485c6ea674b589afb0dd7e097d5d3
Autor:
Anwar Said, Muhammad Umar Janjua, Saeed-Ul Hassan, Zeeshan Muzammal, Tania Saleem, Tipajin Thaipisutikul, Suppawong Tuarob, Raheel Nawaz
Publikováno v:
PeerJ Computer Science, Vol 7, p e815 (2021)
Ethereum, the second-largest cryptocurrency after Bitcoin, has attracted wide attention in the last few years and accumulated significant transaction records. However, the underlying Ethereum network structure is still relatively unexplored. Also, ve
Externí odkaz:
https://doaj.org/article/6ed7d3986ec8462ca19c3b1ecce321a7
Publikováno v:
Computer Communications. 192:384-401
Publikováno v:
Computers & Security. 131:103290
Autor:
Maryam Zulfiqar, Jack W. Stokes, Talha Ahmad, Muhammad Umar Janjua, Muhammad Hassan, Tania Saleem
Publikováno v:
International Journal of Information Security. 21:653-668
SSL certificates hold immense importance when it comes to the security of the WebPKI. The trust in these certificates is driven by the strength of their cryptographic attributes and the presence of revocation features. In this paper, we perform a his
Autor:
Ala Al-Fuqaha, Dusit Niyato, Junaid Qadir, Muhammad Umar Janjua, Muhammad Usama, Inaam Ilahi, Dinh Thai Huang
Deep reinforcement learning (DRL) has numerous applications in the real world, thanks to its ability to achieve high performance in a range of environments with little manual oversight. Despite its great advantages, DRL is susceptible to adversarial
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::cf94664500a0251b82ece3cb5cf085e8
https://hdl.handle.net/10453/159796
https://hdl.handle.net/10453/159796
Publikováno v:
Computers & Security. 121:102827
One of the key challenges in federated learning (FL) is the detection of malicious parameter updates. In a typical FL setup, the presence of malicious client(s) can potentially demolish the overall training of the shared global model by influencing t
Autor:
Tania Saleem, Muhammad Umar Janjua, Muhammad Hassan, Talha Ahmad, Filza Tariq, Khadija Hafeez, Muhammad Ahsan Salal, Muhammad Danish Bilal
Publikováno v:
Computer Networks. 213:109069
Publikováno v:
LCN
The performance of densely-deployed low-power wide-area networks (LPWANs) can significantly deteriorate due to packets collisions, and one of the main reasons for that is the rule-based PHY layer transmission parameters assignment algorithms. LoRaWAN