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Nonetheless, significant concerns have been raised regarding the security and privacy levels that cloud systems can provide, as enterprises have accelerated their cloud migration journeys in an effort to provide a remote working environment for their employees, primarily in light of the COVID-19 outbreak. The goal of this study is to come up with a way to improve steganography in ad hoc cloud systems by using deep learning. This research implementation is separated into two sections. In Phase 1, the \u201cAd-hoc Cloud System\u201d idea and deployment plan were set up with the help of V-BOINC. In Phase 2, a modified form of steganography and deep learning were used to study the security of data transmission in ad-hoc cloud networks. In the majority of prior studies, attempts to employ deep learning models to augment or replace data-hiding systems did not achieve a high success rate. The implemented model inserts data images through colored images in the developed ad hoc cloud system. A systematic steganography model conceals from statistics lower message detection rates. Additionally, it may be necessary to incorporate small images beneath huge cover images. The implemented ad-hoc system outperformed Amazon AC2 in terms of performance, while the execution of the proposed deep steganography approach gave a high rate of evaluation for concealing both data and images when evaluated against several attacks in an ad-hoc cloud system environment.<\/jats:p>","DOI":"10.1186\/s13677-022-00339-w","type":"journal-article","created":{"date-parts":[[2022,12,21]],"date-time":"2022-12-21T12:02:57Z","timestamp":1671624177000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":12,"title":["A deep learning based steganography integration framework for ad-hoc cloud computing data security augmentation using the V-BOINC system"],"prefix":"10.1186","volume":"11","author":[{"given":"Ahmed A.","family":"Mawgoud","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mohamed Hamed N.","family":"Taha","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Amr","family":"Abu-Talleb","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Amira","family":"Kotb","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2022,12,21]]},"reference":[{"key":"339_CR1","doi-asserted-by":"publisher","first-page":"102183","DOI":"10.1016\/j.ijinfomgt.2020.102183","volume":"55","author":"N Iivari","year":"2020","unstructured":"Iivari N, Sharma S, Vent\u00e4-Olkkonen L (2020) Digital transformation of everyday life\u2013how COVID-19 pandemic transformed the basic education of the young generation and why information management research should care? 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