Zobrazeno 1 - 10
of 32
pro vyhledávání: '"Mohammad Mahdi Khalili"'
Publikováno v:
IEEE Access, Vol 9, Pp 70732-70745 (2021)
Personal information and other types of private data are valuable for both data owners and institutions interested in providing targeted and customized services that require analyzing such data. In this context, privacy is sometimes seen as a commodi
Externí odkaz:
https://doaj.org/article/5def62c166b146e2b6fecfdbf507d5e6
Publikováno v:
Games, Vol 13, Iss 4, p 52 (2022)
Nowadays, rating systems play a crucial role in the attraction of customers to different services. However, as it is difficult to detect a fake rating, fraudulent users can potentially unfairly impact the rating’s aggregated score. This fraudulent
Externí odkaz:
https://doaj.org/article/16a1f20034674e4bbeee5435f889247b
Publikováno v:
ACM Transactions on Privacy and Security. 26:1-29
Many data analytics applications rely on temporal data, generated (and possibly acquired) sequentially for online analysis. How to release this type of data in a privacy-preserving manner is of great interest and more challenging than releasing one-t
Autor:
Tania Lavaggi, Mina Samizadeh, Navid Niknafs Kermani, Mohammad Mahdi Khalili, Suresh G. Advani
Publikováno v:
Polymer Composites. 43:5319-5331
Publikováno v:
2022 IEEE International Conference on Data Mining Workshops (ICDMW).
Publikováno v:
IEEE Transactions on Control of Network Systems. 8:964-975
We consider an interdependent security game with networked agents where each agent chooses an effort/investment level for securing itself. The agents are interdependent in a way where the state of security of one agent depends not only on its own eff
Publikováno v:
Proceedings of the 23rd ACM Conference on Economics and Computation.
Autor:
Mohammad Mahdi Khalili, Iman Vakilinia
Publikováno v:
INFOCOM Workshops
Personal information is valuable for organizations and companies providing targeted and customized services. On the other hand, data owners are not willing to share their private information (e.g., spending habits and monthly purchases) due to privac
Publikováno v:
Ergonomics in Design: The Quarterly of Human Factors Applications. 28:7-11
Machine learning models developed from real-world data can inherit potential, preexisting bias in the dataset. When these models are used to inform decisions involving human beings, fairness concerns inevitably arise. Imposing certain fairness constr
Publikováno v:
Games; Volume 13; Issue 4; Pages: 52
Nowadays, rating systems play a crucial role in the attraction of customers to different services. However, as it is difficult to detect a fake rating, fraudulent users can potentially unfairly impact the rating’s aggregated score. This fraudulent
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b0ee1d15e2f0d406da56056cd1d51cbd
http://arxiv.org/abs/2101.10954
http://arxiv.org/abs/2101.10954