Sima Jafarikhah

dblp:195/2869 · DBLP profile ↗
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2ranked-venue papers
0as first author
2since 2021 · last 2024
0009-0000-8427-847XORCID · corroborated

Domains — the database's venue-derived domains; a paper can count in several

Security and privacy · 2 · 2 since 2021
YearPublicationVenuePosition
2024 Assessing Perceptual Hash Algorithms for Publicly Evaluatable Framework
abstract
Image manipulation threatens data integrity and public trust, making reliable authenticity tools essential. The development of a publicly evaluatable perceptual hash framework enables various applications, including private image search resilient to image alterations. Despite the potential of such a framework, little research has systematically analyzed the performance of various perceptual hash algorithms within it. In this paper, we assess the performance of several leading perceptual hash methods, including aHash, pHash, dHash, wHash, and DCT, across five diverse image datasets and examine how cryptographic techniques impact the effectiveness of the algorithms. Integrating advanced encryption techniques with perceptual hashing in this approach is instrumental in advancing data security. It improves the security, privacy, and computational efficiency of perceptual hashing, solidifying its importance within the overall methodology.
Yaser Saei, Jafar Tahmoresnezhad, Sima Jafarikhah, Hossein Siadati
SIN3
2023 Exploring the Threat of Software Supply Chain Attacks on Containerized Applications
abstract
Containerization has become a widely adopted approach for running contemporary software services, with its ingenious layering of Free Open Source Software (FOSS) libraries and packages. The security of containers heavily relies on the integrity of their underlying dependencies, making vulnerability assessment a critical focus for security professionals. However, the landscape has evolved, and recent software supply chain attacks have illuminated a pressing need to shift the focus beyond individual vulnerabilities and delve into the overall security of their supply chain. In this paper, we embark on a data-driven analysis of container threats by examining the security characteristics of software supply chains in their open source dependencies. Leveraging a comprehensive dataset of containers from Docker Hub, our study employs Software Supply Chain metrics like the OSSF scorecard and Software Bill of Material (SBOM) tooling to compile dependency lists. The analysis delivers valuable insights to the security community, empowering them to adopt more effective measures in thwarting and mitigating software supply chain attacks, thereby enhancing the resilience of modern software services.
Motahare Mounesan, Hossein Siadati, Sima Jafarikhah
SIN3