Evidence map›Paper›PMID 41270065›Full record

ArticlePloS one2025

Research on network security vulnerability risk contagion in software supply chain based on system dynamics.

Hui Cai, Qiang Xiong, Shuai Lian

Abstract read
In one paragraph

Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Hui CaiSino-British College, University of Shanghai for Science and Technology, Shanghai, China.ORCID https://orcid.org/0000-0003-1789-0620
Qiang XiongSchool of Management, Jiangsu University, Zhenjiang, Jiangsu, China.
Shuai LianSchool of Management, Jiangsu University, Zhenjiang, Jiangsu, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Software supply chains have emerged as a critical battleground in cyberspace security, with their compromise posing direct threats to critical infrastructure and information systems. The inherent multi-level structures and complex interdependencies among supply chain entities have introduced novel challenges in network and information security. This study investigates the contagion mechanisms of information security risks in software supply chains, aiming to identify key factors influencing risk propagation and evaluate effective defense strategies under multi-layer network conditions. We employ system dynamics (SD) modeling to construct a risk contagion framework for software supply chains, incorporating multi-layer network structures. Dynamic simulations are conducted to analyze risk transmission patterns under different attack and defense scenarios. The simulation results show that the risk transmission rate of software supply chain information security is influenced by the attack path. As compared to random attacks, selective attacks result in a faster risk transmission. In terms of defense strategy, increasing information security investment and improving the level of software quality are more effective for defense against random attacks. In terms of governance measures, increasing technological progress is more effective as compared to reducing the vulnerability rate. The results show that the marginal benefits of the technological progress rate show a decreasing trend. The study quantitatively validates the cascading effects of security risks in multi-layer supply chain networks and provides actionable insights and establishes a system dynamics foundation for predictive risk assessment in complex software supply chain ecosystems.

Indexed as

Computer SecuritySoftwareComputer SimulationHumansModels, Theoretical

Identifiers

PMID41270065
PMCPMC12637968

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.