Srijita Basu

dblp:185/7998 · DBLP profile ↗
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5ranked-venue papers
4as first author
4since 2021 · last 2026
0000-0002-6835-947XORCID · corroborated

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

Security and privacy · 3 · 3 first-author · 3 since 2021Software engineering, systems software and programming languages · 1 · 1 since 2021
YearPublicationVenuePosition
2026 An Investigation of the AUTOSAR Adaptive Platform from an Industry Perspective
abstract
Context: The reliance on software as a distinguishing factor in the automotive industry is increasing. With a combined reliance on vendor-supplied software and cost-effective implementation, the AUTOSAR consortium was initialized to provide standardized platform specifications that enable re-use. Specifically, the AUTOSAR Adaptive Platform (AP) specification aims to provide a high-performance service-oriented architecture. Objective: The goal of this study is to investigate what pain-points emerge when developing AUTOSAR Adaptive applications and whether they originate from the platform specification, its vendor-implementation, or its local usage. Methods: We conduct a Design Science Research study, developing a minimal AP that serves as an experimental prototype for our investigation. Results: We find that a combination of specification-inherent, implementation-based, and local practices contributes to the emergence of pain-points. Conclusions: We conclude that there are AUTOSAR specification-inherent reasons for pain-points, resulting from architectural choices and re-use goals. The implication for development organizations is the need to mitigate these effects through tooling that better supports configuration file management and reduces developer training time to properly understand the adaptive application runtime life-cycle.
Bengt Haraldsson, Srijita Basu, Miroslaw Staron, Erika Mayer
ICSA2
2023 A Novel Software Defined Security Framework for SDN
Srijita Basu, Neha Firdaush Raun, Avishek Ghosal, Debanjan Chatterjee, Debarghya Maitra, Chandan Mazumdar
CRiSIS1
2022 Securing Cloud Virtual Machine Image Using Ethereum Blockchain
abstract
Virtual Machine Image (VMI) is the building block of cloud infrastructure. It encapsulates the various applications and data deployed at the Cloud Service Provider (CSP) end. With the leading advances of cloud computing, comes the added concern of its security. Securing the Cloud infrastructure as a whole is based on the security of the underlying Virtual Machine Images (VMI). In this paper an attempt has been made to highlight the various risks faced by the CSP and Cloud Service Consumer (CSC) in the context of VMI related operations. Later, in this article a formal model of the cloud infrastructure has been proposed. Finally, the Ethereum blockchain has been incorporated to secure, track and manage all the vital operations of the VMIs. The immutable and decentralized nature of blockchain not only makes the proposed scheme more reliable but guarantees auditability of the system by maintaining the entire VMI history in the blockchain.
Srijita Basu, Sandip Karmakar, Debasish Bera
Int. J. Inf. Secur. Priv.1
2021 Blockchain based Secured Virtual Machine Image Monitor
Srijita Basu, Sandip Karmakar, Debasish Bera
ICISSP1
2017 A Quantitative Methodology for Cloud Security Risk Assessment
Srijita Basu, Chandan Mazumdar
CLOSER1