Exploiting Hidden Information Leakages in Backward Privacy for Dynamic Searchable Symmetric Encryption

Autor: Hyundo Yoon, Muncheon Yu, Changhee Hahn, Dongyoung Koo, Junbeom Hur

Publikováno v: Applied Sciences, Vol 14, Iss 6, p 2287 (2024)

Dynamic searchable symmetric encryption (DSSE) enables searches over encrypted data as well as data dynamics such as flexible data addition and deletion operations. A major security concern in DSSE is how to preserve forward and backward privacy, whi

Externí odkaz: https://doaj.org/article/734557aceed8449a8ec3bc0b74643465

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The study of Accountants Perceptions of Different Security Systems Adopted in the Public Accounting Sector in Lebanon

Autor: Ali Kassem, Bogdan Stefan Ionescu

Publikováno v: Proceedings of the International Conference on Business Excellence, Vol 13, Iss 1, Pp 335-346 (2019)

Public Accounting is one of the very rising sectors in the industry. The aim is to produce bulk of financial information that can be further used for making informed decisions by the stakeholders. The wrong information or might jeopardize the involve

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::91065edda924eb07fd8376004b710f82
https://doi.org/10.2478/picbe-2019-0030

Hacking smart machines with smarter ones: How to extract meaningful data from machine learning classifiers

Autor: Angelo Spognardi, Domenico Vitali, Giuseppe Ateniese, Luigi V. Mancini, Giovanni Felici, Antonio Villani

Publikováno v: International journal of security and networks
info:cnr-pdr/source/autori:Ateniese G.; Mancini L.V.; Spognardi A.; Villani A.; Vitali D.; Felici G./titolo:Hacking smart machines with smarter ones: How to extract meaningful data from machine learning classifiers/doi:10.1504%2FIJSN.2015.071829/rivista:International journal of security and networks (Print)/anno:2015/pagina_da:137/pagina_a:150/intervallo_pagine:137–150/volume:10

Machine Learning (ML) algorithms are used to train computers to perform a variety of complex tasks and improve with experience. Computers learn how to recognize patterns, make unintended decisions, or react to a dynamic environment. Certain trained m

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7fb670401c1162470da8cd783e6aa296
http://hdl.handle.net/11573/878035

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