Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Towards Deep Learning Enabled Cybersecurity Risk Assessment for Microservice Architectures
As of 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2403.15169.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-11T19:53:24.602075Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-07T10:22:36.045183Z
Reference resolution
0 of 0 outbound references displayed
- verified exact0
- verified fuzzy0
- unresolved0
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
No outbound reference observations are available for this paper version.
Pith citing papers
Observation 0b309c01-5acf-4dd2-8d38-4577af026103 · inbound
Machine Learning Driven Smishing Detection Framework for Mobile Security cites this paper.
Machine Learning Driven Smishing Detection Framework for Mobile Security Towards Deep Learning Enabled Cybersecurity Risk Assessment for Microservice Architectures
Reference 8
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T19:53:24.602075Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 10cc9532-11d5-4786-a2c4-eaec7c2ab77f · inbound
The Future of AI: Exploring the Potential of Large Concept Models cites this paper.
The Future of AI: Exploring the Potential of Large Concept Models Towards Deep Learning Enabled Cybersecurity Risk Assessment for Microservice Architectures
Reference 65
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T21:29:25.030525Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 74a7ca79-bad7-4433-b8aa-328988bb60b4 · inbound
Resilient Auto-Scaling of Microservice Architectures with Efficient Resource Management cites this paper.
Resilient Auto-Scaling of Microservice Architectures with Efficient Resource Management Towards Deep Learning Enabled Cybersecurity Risk Assessment for Microservice Architectures
Reference 3
- Resolution
- verified exact
- local_arxiv, observed 2026-08-07T10:22:36.125235Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.