CloudMonitor: Data Flow Filtering as a Service

Fahad, Alqahtani; Sheldon, Frederick T.

doi:10.1109/csci49370.2019.00271

Cited by 2 publications

(1 citation statement)

References 16 publications

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“…Several researchers have proposed solutions to assure security data hosted in the cloud from cloud providers (i.e., internal threats), such as Dawoud et al (2016), Wang et al (2014), Ko et al (2011), Balamurugan and Saravanan (2019), and Ünal (2019). As well, a few have also addressed protecting multimedia content in VoD/multimedia systems when hosted in an untrusted cloud environment, such as Li and Yang (2016), Stewart and Long (2016), He et al (2017) and Alqahtani and Sheldon (2019). Thus, the problem we are attempting to solve with this research is protecting multimedia contents from cloud providers and outsiders in cloud-based VoD systems.…”

Section: Introductionmentioning

confidence: 99%

Enhanced video-on-demand security in cloud computing against insider and outsider threats

Alshayeji¹,

Abed²

2022

IJSN

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Many video-on-demand (VoD) providers leverage the benefits of cloud computing despite the stemming various security threats. For instance, if the hosted multimedia contents are not encrypted, then the VoD providers must fully trust that the cloud provider will not illegitimately access, distribute, or modify the multimedia contents. Nonetheless, the latest ENISA report showed that approximately 25% of security threats over the last six years have been based on internal misuse. In this paper, we introduce a simple yet effective scheme to protect contents from internal and external threats. Encrypt once -confidentiality, privacy, and integrity (EO-CPI) focuses on protecting data confidentiality, integrity, and users' privacy from untrusted cloud-based VoD systems. We compared EO-CPI with advance encryption standard -Galois counter mode (AES-GCM). Results demonstrated a significant reduction of 79% of the server-side computational overhead when using EO-CPI with a re-encryption degree of one time per five users while preserving the user-side performance.

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