Paper Citation Record · LEDGER

The Dark Side of Digital Twins: Adversarial Attacks on AI-Driven Water Forecasting

As of 18 August 2026, this Paper Citation Record lists 15 of 15 outbound references and 0 inbound Pith citation observations for arXiv:2504.20295.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2504.20295 v1

Coverage vector

measured 15 of 15 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-16T05:37:15.953653Z

measured 15 of 15 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

15 of 15 outbound references displayed

verified exact2
verified fuzzy10
unresolved3
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 36db84c0-da79-4fc8-976b-2c86d3d172b2 · outbound

This paper cites Digital twins for wastewater treatment: A technical review,.

The Dark Side of Digital Twins: Adversarial Attacks on AI-Driven Water Forecasting Digital twins for wastewater treatment: A technical review,

Reference 1

Resolution: verified exact; doi, observed 2026-08-16T05:37:15.993211Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation cc2091d9-5f29-4b4b-a492-fff1237d11ce · outbound

This paper cites Impact of digital transformation on carbon emissions reductions in the water industry,.

The Dark Side of Digital Twins: Adversarial Attacks on AI-Driven Water Forecasting Impact of digital transformation on carbon emissions reductions in the water industry,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:37:16.117651Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 5c8525a0-ace4-40ee-a7a5-8fb65be32df5 · outbound

This paper cites Digital Transformation in the Water Distribution System based on the Digital Twins Concept.

The Dark Side of Digital Twins: Adversarial Attacks on AI-Driven Water Forecasting Digital Transformation in the Water Distribution System based on the Digital Twins Concept

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-16T05:37:15.914130Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d6cd8403-2966-401d-99b0-8c682ea1b78f · outbound

This paper cites an unresolved cited work.

The Dark Side of Digital Twins: Adversarial Attacks on AI-Driven Water Forecasting Unresolved cited work

Reference 4

Resolution: unresolved; raw_fallback, observed 2026-08-16T05:37:16.108156Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 320acf08-e5f7-4b0f-b11d-b0a388b3f9bc · outbound

This paper cites A review of digital twins and their application in cybersecurity based on artificial intelligence,.

The Dark Side of Digital Twins: Adversarial Attacks on AI-Driven Water Forecasting A review of digital twins and their application in cybersecurity based on artificial intelligence,

Reference 5

Resolution: verified exact; doi, observed 2026-08-16T05:37:15.982709Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation a77627be-3b72-4220-ba3c-a01185c9cc8b · outbound

This paper cites Universal fourier attack for time series,.

The Dark Side of Digital Twins: Adversarial Attacks on AI-Driven Water Forecasting Universal fourier attack for time series,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:37:16.097992Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 01712d0a-51c0-4b36-884b-fca5469fb8c2 · outbound

This paper cites AdaptEdge: Targeted universal adversarial attacks on time series data in smart grids,.

The Dark Side of Digital Twins: Adversarial Attacks on AI-Driven Water Forecasting AdaptEdge: Targeted universal adversarial attacks on time series data in smart grids,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:37:16.088181Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 9125750c-d021-4311-abbe-f06b0a44acee · outbound

This paper cites Trojan attack and defense for deep learning-based navigation systems of unmanned aerial vehicles,.

The Dark Side of Digital Twins: Adversarial Attacks on AI-Driven Water Forecasting Trojan attack and defense for deep learning-based navigation systems of unmanned aerial vehicles,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:37:16.078511Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 1089ae9b-7c96-4126-9010-3e5e10b0f6d7 · outbound

This paper cites Towards deep learning models resistant to adversarial attacks,.

The Dark Side of Digital Twins: Adversarial Attacks on AI-Driven Water Forecasting Towards deep learning models resistant to adversarial attacks,

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-16T05:37:15.934959Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 747514f0-3202-423d-9801-b31a58673a51 · outbound

This paper cites De- veloping an LSTM model to forecast the monthly water consumption according to the effects of the climatic factors in Yazd, Iran,.

The Dark Side of Digital Twins: Adversarial Attacks on AI-Driven Water Forecasting De- veloping an LSTM model to forecast the monthly water consumption according to the effects of the climatic factors in Yazd, Iran,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:37:16.062775Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 45493a96-b76a-472b-8559-4cead4a4221e · outbound

This paper cites River water temperature forecasting using a deep learning method,.

The Dark Side of Digital Twins: Adversarial Attacks on AI-Driven Water Forecasting River water temperature forecasting using a deep learning method,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:37:16.052463Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation a60c20b2-eab5-4849-a47e-319a47680e04 · outbound

This paper cites A digital twin of a water distribution system by using graph convolutional networks for pump speed-based state estimation,.

The Dark Side of Digital Twins: Adversarial Attacks on AI-Driven Water Forecasting A digital twin of a water distribution system by using graph convolutional networks for pump speed-based state estimation,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:37:16.042350Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation bbc2006a-bfdc-4e5f-bfa7-85e17196324e · outbound

This paper cites Graph neural networks for sensor placement: A proof of concept towards a digital twin of water distribution systems,.

The Dark Side of Digital Twins: Adversarial Attacks on AI-Driven Water Forecasting Graph neural networks for sensor placement: A proof of concept towards a digital twin of water distribution systems,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:37:16.032457Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 88c071ff-0b14-47ef-9921-587924abc766 · outbound

This paper cites Ambling. Official Website,.

The Dark Side of Digital Twins: Adversarial Attacks on AI-Driven Water Forecasting Ambling. Official Website,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:37:16.022453Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 9e430d49-164c-4335-a00a-7ae58f8a3b4d · outbound

This paper cites Rezvanian, A.

The Dark Side of Digital Twins: Adversarial Attacks on AI-Driven Water Forecasting Rezvanian, A

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:37:16.012688Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Pith citing papers

No inbound Pith citation observations are available.