Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Reda A. Zayed"'
Autor:
Reda A. Zayed, Lamiaa Fattouh Ibrahim, Hesham A. Hefny, Hesham A. Salman, Abdulaziz AlMohimeed
Publikováno v:
IEEE Access, Vol 11, Pp 111315-111323 (2023)
Shill attacks are a serious threat to the stability of filtering and recommendation systems. These attacks involve the injection of fake profiles into the system, which can compromise the reliability of system output. Several shilling attack detectio
Externí odkaz:
https://doaj.org/article/2c2da97174a3452c8b5f134185937e85
Autor:
Reda A. Zayed, Lamiaa Fattouh Ibrahim, Hesham A. Hefny, Hesham A. Salman, Abdulaziz AlMohimeed
Publikováno v:
IEEE Access, Vol 11, Pp 79358-79369 (2023)
The stability and reliability of filtration and recommender systems are crucial for continuous operation. The presence of fake profiles, known as “shilling attacks,” can undermine the reliability of these systems. Therefore, it is important to de
Externí odkaz:
https://doaj.org/article/885d384e24f54ac18d46e81db2b77c55
Publikováno v:
2023 1st International Conference on Advanced Innovations in Smart Cities (ICAISC).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3956173bb72f7bf74f3a7100cd3a41ba
https://doi.org/10.1109/icaisc56366.2023.10085506
https://doi.org/10.1109/icaisc56366.2023.10085506
Publikováno v:
Advances in Intelligent Systems and Computing ISBN: 9783030440374
AINA Workshops
AINA Workshops
The reliability of the recommender system is highly essential for the continuity of any system. Fake and malicious users may be spoiling system predictions reliability by inserting and injecting fake profiles called “shilling attacks” into the ta
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4c0f2d4178ce1de1c03965f0b7a8fdbc
https://doi.org/10.1007/978-3-030-44038-1_39
https://doi.org/10.1007/978-3-030-44038-1_39
Publikováno v:
2015 First International Conference on Arabic Computational Linguistics (ACLing).
Multi-label classification (MLC) is concerned withlearning from examples where each example is associatedwith a set of labels in opposite to traditional single-labelclassification where an example typically is assigned a single label. MLC problems ap
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::632e62db9c405e69ee0bfd72f4e2e8c7
https://doi.org/10.1109/acling.2015.28
https://doi.org/10.1109/acling.2015.28