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Paper Citation Record · LEDGER

Preventing Adversarial AI Attacks Against Autonomous Situational Awareness: A Maritime Case Study

As of 8 August 2026, this Paper Citation Record lists 91 of 91 outbound references and 0 inbound Pith citation observations for arXiv:2505.21609.

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

pith.paper-citation-record.v1
2505.21609 v1

Coverage vector

measured 91 of 91 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:33:03.086873Z

measured 91 of 91 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+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

91 of 91 outbound references displayed

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External citation measurements

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Outbound references

Observation 426d3745-ea74-4554-ad3e-0cf447071907 · outbound

This paper cites Towards utilising autonomous ships: A viable advance in industry 4.0,.

Preventing Adversarial AI Attacks Against Autonomous Situational Awareness: A Maritime Case Study Towards utilising autonomous ships: A viable advance in industry 4.0,

Reference 1

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Observation ab3987c3-c979-44f2-a743-8c92d7b8cb6e · outbound

This paper cites Situation awareness in remote control centres for unmanned ships,.

Preventing Adversarial AI Attacks Against Autonomous Situational Awareness: A Maritime Case Study Situation awareness in remote control centres for unmanned ships,

Reference 2

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Observation 88362936-4d66-4e93-94f6-4c13bfa97571 · outbound

This paper cites Worlds first autonomous ship to launch in 2018,.

Preventing Adversarial AI Attacks Against Autonomous Situational Awareness: A Maritime Case Study Worlds first autonomous ship to launch in 2018,

Reference 3

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This paper cites Costs and benefits of au- tonomous shipping—a literature review,.

Preventing Adversarial AI Attacks Against Autonomous Situational Awareness: A Maritime Case Study Costs and benefits of au- tonomous shipping—a literature review,

Reference 4

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Observation 586e31fc-b562-4c24-bd33-9eee7f02aeca · outbound

This paper cites Autonomous ships: a review, innovative applications and future maritime business models,.

Preventing Adversarial AI Attacks Against Autonomous Situational Awareness: A Maritime Case Study Autonomous ships: a review, innovative applications and future maritime business models,

Reference 5

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Observation a9201c1f-809e-44db-874a-5d81378083cd · outbound

This paper cites Analyzing the eco- nomic benefit of unmanned autonomous ships: An exploratory cost- comparison between an autonomous and a conventional bulk carrier,.

Preventing Adversarial AI Attacks Against Autonomous Situational Awareness: A Maritime Case Study Analyzing the eco- nomic benefit of unmanned autonomous ships: An exploratory cost- comparison between an autonomous and a conventional bulk carrier,

Reference 6

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Observation ab911765-9e2e-42f4-a2df-91cf43d41451 · outbound

This paper cites The ocean-going autonomous ship—challenges and threats,.

Preventing Adversarial AI Attacks Against Autonomous Situational Awareness: A Maritime Case Study The ocean-going autonomous ship—challenges and threats,

Reference 7

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Observation cc3bbb21-2389-43bc-8d87-6fdb3629c398 · outbound

This paper cites Creating value through autonomous shipping: an ecosystem perspective,.

Preventing Adversarial AI Attacks Against Autonomous Situational Awareness: A Maritime Case Study Creating value through autonomous shipping: an ecosystem perspective,

Reference 8

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Observation 7ad5f830-6880-4ea1-8df2-980b9f7f3a38 · outbound

This paper cites Explaining and Harnessing Adversarial Examples.

Preventing Adversarial AI Attacks Against Autonomous Situational Awareness: A Maritime Case Study Explaining and Harnessing Adversarial Examples

Reference 9

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Observation c519f43a-b24e-4a10-9807-21f58a91ea93 · outbound

This paper cites Intriguing properties of neural networks.

Preventing Adversarial AI Attacks Against Autonomous Situational Awareness: A Maritime Case Study Intriguing properties of neural networks

Reference 10

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Observation b18162d1-15a9-4108-818c-241fab0f6e11 · outbound

This paper cites Thinking about the security of AI systems,.

Preventing Adversarial AI Attacks Against Autonomous Situational Awareness: A Maritime Case Study Thinking about the security of AI systems,

Reference 11

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Observation 04260164-6ec5-462a-b152-67536ad420df · outbound

This paper cites Introducing our new machine learning security principles,.

Preventing Adversarial AI Attacks Against Autonomous Situational Awareness: A Maritime Case Study Introducing our new machine learning security principles,

Reference 12

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Observation ef6fa44a-0ca7-42ba-8552-d6f9b5d3ac95 · outbound

This paper cites Why we should have seen that coming: comments on microsoft’s tay.

Preventing Adversarial AI Attacks Against Autonomous Situational Awareness: A Maritime Case Study Why we should have seen that coming: comments on microsoft’s tay

Reference 13

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Observation 7432373d-721b-458b-b243-b79aa73f1999 · outbound

This paper cites Machine learning security in industry: A quantitative survey,.

Preventing Adversarial AI Attacks Against Autonomous Situational Awareness: A Maritime Case Study Machine learning security in industry: A quantitative survey,

Reference 14

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Observation 4c6cbf5d-5d0f-4839-a9d7-40b27b9ee768 · outbound

This paper cites Securing con- nected & autonomous vehicles: Challenges posed by adversarial machine learning and the way forward,.

Preventing Adversarial AI Attacks Against Autonomous Situational Awareness: A Maritime Case Study Securing con- nected & autonomous vehicles: Challenges posed by adversarial machine learning and the way forward,

Reference 15

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Observation 914aac00-47f0-4259-9902-43ba4df5e35c · outbound

This paper cites Cybersecurity of autonomous vehicles: A systematic literature review of adversarial attacks and defense models,.

Preventing Adversarial AI Attacks Against Autonomous Situational Awareness: A Maritime Case Study Cybersecurity of autonomous vehicles: A systematic literature review of adversarial attacks and defense models,

Reference 16

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Observation 7fbd2151-b9c5-4876-bada-fe6d49832460 · outbound

This paper cites Artificial intelligence failures in autonomous vehicles: Causes, implications, and prevention,.

Preventing Adversarial AI Attacks Against Autonomous Situational Awareness: A Maritime Case Study Artificial intelligence failures in autonomous vehicles: Causes, implications, and prevention,

Reference 17

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Observation 258bccf5-7a15-4097-bedf-fdcd775cb0e8 · outbound

This paper cites Quan- tifying the econometric loss of a cyber-physical attack on a seaport,.

Preventing Adversarial AI Attacks Against Autonomous Situational Awareness: A Maritime Case Study Quan- tifying the econometric loss of a cyber-physical attack on a seaport,

Reference 18

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Observation c72d0360-1724-4874-99b8-57ba29c42d4e · outbound

This paper cites Adversarial AI testcases for maritime autonomous systems,.

Preventing Adversarial AI Attacks Against Autonomous Situational Awareness: A Maritime Case Study Adversarial AI testcases for maritime autonomous systems,

Reference 19

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Observation 71b43677-c815-4d3c-bd4d-09ac4afe0b44 · outbound

This paper cites A red teaming framework for securing AI in maritime autonomous systems,.

Preventing Adversarial AI Attacks Against Autonomous Situational Awareness: A Maritime Case Study A red teaming framework for securing AI in maritime autonomous systems,

Reference 20

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Observation 3fff6920-7273-4b85-947d-01ac3545439f · outbound

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Preventing Adversarial AI Attacks Against Autonomous Situational Awareness: A Maritime Case Study Learning in the presence of malicious errors,

Reference 21

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Preventing Adversarial AI Attacks Against Autonomous Situational Awareness: A Maritime Case Study Adversarial classification,

Reference 22

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Preventing Adversarial AI Attacks Against Autonomous Situational Awareness: A Maritime Case Study Adversarial learning,

Reference 23

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Preventing Adversarial AI Attacks Against Autonomous Situational Awareness: A Maritime Case Study Evasion attacks against machine learning at test time,

Reference 24

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Preventing Adversarial AI Attacks Against Autonomous Situational Awareness: A Maritime Case Study Adversarial Machine Learning at Scale

Reference 25

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Preventing Adversarial AI Attacks Against Autonomous Situational Awareness: A Maritime Case Study The limitations of deep learning in adversarial settings,

Reference 26

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Preventing Adversarial AI Attacks Against Autonomous Situational Awareness: A Maritime Case Study One pixel attack for fooling deep neural networks,

Reference 27

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Preventing Adversarial AI Attacks Against Autonomous Situational Awareness: A Maritime Case Study Towards evaluating the robustness of neural networks,

Reference 28

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Preventing Adversarial AI Attacks Against Autonomous Situational Awareness: A Maritime Case Study Towards Deep Learning Models Resistant to Adversarial Attacks

Reference 29

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Preventing Adversarial AI Attacks Against Autonomous Situational Awareness: A Maritime Case Study Deepfool: a simple and accurate method to fool deep neural networks,

Reference 30

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Preventing Adversarial AI Attacks Against Autonomous Situational Awareness: A Maritime Case Study Can machine learning be secure?

Reference 31

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Preventing Adversarial AI Attacks Against Autonomous Situational Awareness: A Maritime Case Study Support vector machines under adversarial label noise,

Reference 32

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Preventing Adversarial AI Attacks Against Autonomous Situational Awareness: A Maritime Case Study BadNets: Identifying Vulnerabilities in the Machine Learning Model Supply Chain

Reference 33

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Preventing Adversarial AI Attacks Against Autonomous Situational Awareness: A Maritime Case Study Attack strength vs. detectability dilemma in adversarial machine learning,

Reference 34

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Observation dbf45f8d-a243-4573-92bf-c4b45dae9e8f · outbound

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Preventing Adversarial AI Attacks Against Autonomous Situational Awareness: A Maritime Case Study Hacking smart machines with smarter ones: How to extract meaningful data from machine learning classifiers,

Reference 35

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:32:58.249959Z digest=sha256:1a26ec0add05449a6d29665f4690ab781a01b95b39e3f2be97989f2476974150

Observation 0afd20fe-2c79-40bf-94a4-95eeda1b7067 · outbound

This paper cites Membership inference attacks against machine learning models,.

Preventing Adversarial AI Attacks Against Autonomous Situational Awareness: A Maritime Case Study Membership inference attacks against machine learning models,

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:33:12.062317Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:32:58.348980Z digest=sha256:10c3a5607c0b3fa5edcf034657b569f2d47f66722b634ea42b17d283a53a99f3

Observation 0e043d26-c6b1-46cb-a299-f0e6ccd69d76 · outbound

This paper cites Resolving individuals contributing trace amounts of dna to highly complex mixtures using high-density snp genotyping microarrays,.

Preventing Adversarial AI Attacks Against Autonomous Situational Awareness: A Maritime Case Study Resolving individuals contributing trace amounts of dna to highly complex mixtures using high-density snp genotyping microarrays,

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:33:11.922811Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:32:58.428627Z digest=sha256:93d7b785740fbfe5cd826c155b71a737dfd596f5aad80689eafaec9025397624

Observation 6b6869d6-ca3f-47d9-a384-be1eaa89c6d0 · outbound

This paper cites Stealing machine learning models via prediction {APIs},.

Preventing Adversarial AI Attacks Against Autonomous Situational Awareness: A Maritime Case Study Stealing machine learning models via prediction {APIs},

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:33:11.779206Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:32:58.517761Z digest=sha256:e369d0767a0144bf018667f4c29558ff3d5b45d40098caa67f1d0bf85c4474a6

Observation b79b05df-58c3-41ab-ad1c-60b79ca3b741 · outbound

This paper cites Survey of Vulnerabilities in Large Language Models Revealed by Adversarial Attacks.

Preventing Adversarial AI Attacks Against Autonomous Situational Awareness: A Maritime Case Study Survey of Vulnerabilities in Large Language Models Revealed by Adversarial Attacks

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-07T13:32:58.625420Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:32:58.625420Z digest=sha256:24cd16bc1f885f4888db99c9ac7edaf81affa35e8019a34d0232b04e8efa2961

Observation 20617d87-11a7-4cce-9afb-435a0af178ae · outbound

This paper cites A survey on large language model (LLM) security and privacy: The good, the bad, and the ugly,.

Preventing Adversarial AI Attacks Against Autonomous Situational Awareness: A Maritime Case Study A survey on large language model (LLM) security and privacy: The good, the bad, and the ugly,

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:33:11.560314Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:32:58.750062Z digest=sha256:d132309e6759700cd9dd255b4aec695e5bb8dd722502606d1b1fecd8209ba579

Observation fb8baf81-7b10-49d1-a44e-0c0ca93a368c · outbound

This paper cites Breaking down the defenses: A comparative survey of attacks on large language models,.

Preventing Adversarial AI Attacks Against Autonomous Situational Awareness: A Maritime Case Study Breaking down the defenses: A comparative survey of attacks on large language models,

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-07T13:32:58.906897Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:32:58.906897Z digest=sha256:914d09629526c6a65593b7c1c206db7f8b73d1f61735f7fe6d9e321a5da50587

Observation 69131750-f0d4-4ea0-b73d-7011c3c26393 · outbound

This paper cites Understanding robustness of transformers for image classification,.

Preventing Adversarial AI Attacks Against Autonomous Situational Awareness: A Maritime Case Study Understanding robustness of transformers for image classification,

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:33:11.377737Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:32:59.052114Z digest=sha256:21f9b1ba12e8336653eff6eb959cdfe5d3550799683c4c7d723dfd6f521d14dc

Observation bffacfca-cccd-46fe-b2b6-cfd3d8afc4aa · outbound

This paper cites Reveal of Vision Transformers Robustness against Adversarial Attacks.

Preventing Adversarial AI Attacks Against Autonomous Situational Awareness: A Maritime Case Study Reveal of Vision Transformers Robustness against Adversarial Attacks

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-07T13:32:59.161249Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:32:59.161249Z digest=sha256:e38707414c711689cb5180dbcee2d1043d9c1202a7d5f132d06a2c121e6f8123

Observation 59772677-491a-4b2e-8d53-72b1106ba510 · outbound

This paper cites Patch-Fool: Are Vision Transformers Always Robust Against Adversarial Perturbations?.

Preventing Adversarial AI Attacks Against Autonomous Situational Awareness: A Maritime Case Study Patch-Fool: Are Vision Transformers Always Robust Against Adversarial Perturbations?

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-07T13:32:59.262639Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:32:59.262639Z digest=sha256:c620caa0d12d4a39f356e073826fb4b978d4f32e33705f23bb97e28c46ceca3e

Observation c9b065ab-e17e-472c-972b-b9b7208b925d · outbound

This paper cites Towards transferable adversarial attacks on vision transformers,.

Preventing Adversarial AI Attacks Against Autonomous Situational Awareness: A Maritime Case Study Towards transferable adversarial attacks on vision transformers,

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:33:11.137921Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:32:59.380552Z digest=sha256:9dbb6a30cac6f1dd11a3a9077f0575539dc411342bd4b75aebde8f26ce56dbd0

Observation 45dd8eb4-e773-4b3d-bac0-59d628aa947f · outbound

This paper cites Towards transferable adversarial attacks on image and video transformers,.

Preventing Adversarial AI Attacks Against Autonomous Situational Awareness: A Maritime Case Study Towards transferable adversarial attacks on image and video transformers,

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-07T13:32:59.477495Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:32:59.477495Z digest=sha256:e869d8ae24a94893c62fd670a9373b759f8c4234c2e2c40276ce8bdd126c2886

Observation bb8c9c13-1d5c-41cc-ac5f-bf012805bd1d · outbound

This paper cites SlowFormer: Universal Adversarial Patch for Attack on Compute and Energy Efficiency of Inference Efficient Vision Transformers.

Preventing Adversarial AI Attacks Against Autonomous Situational Awareness: A Maritime Case Study SlowFormer: Universal Adversarial Patch for Attack on Compute and Energy Efficiency of Inference Efficient Vision Transformers

Reference 47

Resolution
verified exact
local_arxiv, observed 2026-08-07T13:33:03.397326Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:32:59.591146Z digest=sha256:ab990ae765981e684adde0b715b36eb97b236bb0fa28e43bc9d502759dbd8b51

Observation aadf2015-3834-4db6-9b68-a4e4df654de3 · outbound

This paper cites DeSparsify: Adversarial Attack Against Token Sparsification Mechanisms in Vision Transformers.

Preventing Adversarial AI Attacks Against Autonomous Situational Awareness: A Maritime Case Study DeSparsify: Adversarial Attack Against Token Sparsification Mechanisms in Vision Transformers

Reference 48

Resolution
verified exact
local_arxiv, observed 2026-08-07T13:33:03.258486Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:32:59.696282Z digest=sha256:d9b6e6960cb695e15c9222442cbc64693a6b60cc43623cd0fd54aff5c22f18ef

Observation 9846d78a-1a6d-4f02-a300-6101f10ae20c · outbound

This paper cites Literature review of maritime cyber security: The first decade,.

Preventing Adversarial AI Attacks Against Autonomous Situational Awareness: A Maritime Case Study Literature review of maritime cyber security: The first decade,

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:33:10.926005Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:32:59.814753Z digest=sha256:28b358bcc85ec018074cfffba366ff0d72fb91a0ae79f91edaf885f27b41ee23

Observation a141eaa1-45d3-4d84-a48d-6861d56e9aa2 · outbound

This paper cites Artificial intelligence for au- tonomous ship: Potential cyber threats and security,.

Preventing Adversarial AI Attacks Against Autonomous Situational Awareness: A Maritime Case Study Artificial intelligence for au- tonomous ship: Potential cyber threats and security,

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:33:10.667333Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:32:59.907735Z digest=sha256:ef74f4798a768661a52a7c06d08c2d61ae6316099a90e891584830a15760b313

Observation d6569bea-c4cd-43c2-8186-893befad298a · outbound

This paper cites Vulnerability of clean-label poisoning attack for object detection in maritime autonomous surface ships,.

Preventing Adversarial AI Attacks Against Autonomous Situational Awareness: A Maritime Case Study Vulnerability of clean-label poisoning attack for object detection in maritime autonomous surface ships,

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:33:10.379951Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:32:59.972376Z digest=sha256:7b3bf1f889bf06081ef4211dc7b5317d9e7777ec44f2b787feb715d4aa3c8666

Observation 343f31ea-2313-4109-88ea-54a9b0d8bbc3 · outbound

This paper cites Adver- sarial waypoint injection attacks on maritime autonomous surface ships (MASS) collision avoidance systems,.

Preventing Adversarial AI Attacks Against Autonomous Situational Awareness: A Maritime Case Study Adver- sarial waypoint injection attacks on maritime autonomous surface ships (MASS) collision avoidance systems,

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:33:10.137305Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:33:00.053379Z digest=sha256:625e6dd9e3af5f4f4772767ae608feb57cd711919ed4d2a777857d64a6aff291

Observation f869b3d5-eaec-4015-a700-a1ee401d4a4d · outbound

This paper cites Autonomous cyber defense agents for nato: Threat analysis, design, and experimentation,.

Preventing Adversarial AI Attacks Against Autonomous Situational Awareness: A Maritime Case Study Autonomous cyber defense agents for nato: Threat analysis, design, and experimentation,

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:33:09.925001Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:33:00.153550Z digest=sha256:e7afc770d2efdc220bb05ef36d3addea7e9512851ff2852d2425f3f479748726

Observation 811b5e7c-46e9-405e-a7da-94ced700db10 · outbound

This paper cites Advancing radar cybersecurity: Defending against adversarial attacks in SAR ship recognition using explainable AI and ensemble learning,.

Preventing Adversarial AI Attacks Against Autonomous Situational Awareness: A Maritime Case Study Advancing radar cybersecurity: Defending against adversarial attacks in SAR ship recognition using explainable AI and ensemble learning,

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:33:09.714095Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:33:00.206174Z digest=sha256:a9fc386038d2e500755c517282f49994ca82b4d6e0ee493338a437f723cfc792

Observation 77f5ef7f-5a71-4a6b-85c6-1f9864803140 · outbound

This paper cites A practical deceptive jamming method based on vulnerable location awareness adversarial attack for radar HRRP target recognition,.

Preventing Adversarial AI Attacks Against Autonomous Situational Awareness: A Maritime Case Study A practical deceptive jamming method based on vulnerable location awareness adversarial attack for radar HRRP target recognition,

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:33:09.543079Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:33:00.305663Z digest=sha256:d1de63e168b5476f66467cb0ed1f4eac394681bcf07a313a35a005208d42b648

Observation 8eba57a3-d296-4e1e-a7b9-ee9ad841793e · outbound

This paper cites Adversarial camouflage for naval vessels,.

Preventing Adversarial AI Attacks Against Autonomous Situational Awareness: A Maritime Case Study Adversarial camouflage for naval vessels,

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:33:09.391798Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:33:00.419660Z digest=sha256:a00e3da474e34286be46a1abd0f45df6cc64cb6a89c192d34b0adc76de9974c0

Observation 6075c688-f6d3-436d-b19d-1d78a160886f · outbound

This paper cites Robustness of adversarial camouflage (ac) for naval vessels,.

Preventing Adversarial AI Attacks Against Autonomous Situational Awareness: A Maritime Case Study Robustness of adversarial camouflage (ac) for naval vessels,

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:33:09.223592Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:33:00.537774Z digest=sha256:3a2c5acfd8b1a0ed7bff6112bac66e9e3651ea34fb8499c195293c3bacdd3201

Observation 6bf864a9-d6dd-42b7-a897-30a7620d173d · outbound

This paper cites Shipcamou: adversarial camouflage against optical remote sensing image ship detector,.

Preventing Adversarial AI Attacks Against Autonomous Situational Awareness: A Maritime Case Study Shipcamou: adversarial camouflage against optical remote sensing image ship detector,

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:33:09.061982Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:33:00.672316Z digest=sha256:ab3619ac55e2127d67d1f7e5d0b1270ec01b8d24158495ec4e78f414801ef82b

Observation e1fc0f4a-e0df-4a9d-8674-79e963745ccb · outbound

This paper cites Cyber risk assessment of cyber-enabled autonomous cargo vessel,.

Preventing Adversarial AI Attacks Against Autonomous Situational Awareness: A Maritime Case Study Cyber risk assessment of cyber-enabled autonomous cargo vessel,

Reference 59

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:33:08.914473Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:33:00.740752Z digest=sha256:efaf8b70b393f1f4307e3e42837a026a1bc3ab9f13c4c0a9bc3d775fe46fad01

Observation e4adc911-1b26-4f63-9647-a587b22ed691 · outbound

This paper cites Verifai: Framework for functional verification of AI based systems in the mar- itime domain,.

Preventing Adversarial AI Attacks Against Autonomous Situational Awareness: A Maritime Case Study Verifai: Framework for functional verification of AI based systems in the mar- itime domain,

Reference 60

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:33:08.741199Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:33:00.826496Z digest=sha256:e8fc017fc7f9b1ccbdecdf788d16ac080e6f657ba096915578f261aca9fa1c9a

Observation 1df9cca9-b688-420c-abb1-d0cf4703ca5f · outbound

This paper cites Formulating cybersecurity requirements for au- tonomous ships using the square methodology,.

Preventing Adversarial AI Attacks Against Autonomous Situational Awareness: A Maritime Case Study Formulating cybersecurity requirements for au- tonomous ships using the square methodology,

Reference 61

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:33:08.668417Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:33:00.940201Z digest=sha256:44fb7d649b0e8f0348d6ce1161cd0ffaa175b245f546b3a304ee14422ceb244e

Observation ddb39e1a-ff84-4612-841d-cdcf02b7278b · outbound

This paper cites Artificial intelligence and data fusion at the edge,.

Preventing Adversarial AI Attacks Against Autonomous Situational Awareness: A Maritime Case Study Artificial intelligence and data fusion at the edge,

Reference 62

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:33:08.388168Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:33:01.010867Z digest=sha256:405abe438fda6c7ec621b65bdec5686de804d65f190a419c1b7a9d1fc12aeec2

Observation 2fac9681-65f0-41c1-90c2-f05f728296fe · outbound

This paper cites An introduction to multisensor data fusion,.

Preventing Adversarial AI Attacks Against Autonomous Situational Awareness: A Maritime Case Study An introduction to multisensor data fusion,

Reference 63

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:33:08.234867Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:33:01.091961Z digest=sha256:a632694b2944e50c87f4c3fee209f798c0c5259cadf4387fb5546112f1eea084

Observation 95d2705b-ca62-43a0-a1b3-e45fe5f084cb · outbound

This paper cites Bayesian data fusion of multiview synthetic aperture sonar imagery for seabed classification,.

Preventing Adversarial AI Attacks Against Autonomous Situational Awareness: A Maritime Case Study Bayesian data fusion of multiview synthetic aperture sonar imagery for seabed classification,

Reference 64

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:33:08.084027Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:33:01.173080Z digest=sha256:4d8b32476e21511f005ac97419e5906c20598aa28cd8ae4a5f8815132b6b7e71

Observation 7aa9c4bf-f734-4f0e-b1e2-9428be9fd8fd · outbound

This paper cites Bayesian information fusion and multitarget tracking for maritime situational awareness,.

Preventing Adversarial AI Attacks Against Autonomous Situational Awareness: A Maritime Case Study Bayesian information fusion and multitarget tracking for maritime situational awareness,

Reference 65

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:33:07.893030Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:33:01.253547Z digest=sha256:6e50a36cbaabf0d16b554cfc978adc07f71bd5097ecac7e7a6185514ba213adc

Observation e9289ecd-f886-4ade-818b-f00c2f175f6d · outbound

This paper cites Asynchronous trajectory matching-based multimodal maritime data fusion for vessel traffic surveillance in inland waterways,.

Preventing Adversarial AI Attacks Against Autonomous Situational Awareness: A Maritime Case Study Asynchronous trajectory matching-based multimodal maritime data fusion for vessel traffic surveillance in inland waterways,

Reference 66

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:33:07.686848Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:33:01.327438Z digest=sha256:cb1645b0a0bad1b7716a2202041ab56d70d923b3582da7beb2082cbd8fc12aea

Observation 17b2a748-55de-4ed1-bd15-c4ee97f6c164 · outbound

This paper cites Space-based global maritime surveillance. part ii: Artificial intelligence and data fusion techniques,.

Preventing Adversarial AI Attacks Against Autonomous Situational Awareness: A Maritime Case Study Space-based global maritime surveillance. part ii: Artificial intelligence and data fusion techniques,

Reference 67

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:33:07.452010Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:33:01.373637Z digest=sha256:07fff07f80633d74d652dc5726da63391e7f02d57085f699419892477ad3c51e

Observation fd5c63ad-23b3-450c-bd75-8faf4319ac73 · outbound

This paper cites A network model for detecting marine floating weak targets based on multimodal data fusion of radar echoes,.

Preventing Adversarial AI Attacks Against Autonomous Situational Awareness: A Maritime Case Study A network model for detecting marine floating weak targets based on multimodal data fusion of radar echoes,

Reference 68

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:33:07.182548Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:33:01.429140Z digest=sha256:6ae2859d3f1ed94a908e43cb790d9586343436858f5532a16d50161b60c0b44e

Observation 7f0f23bf-fdff-4557-b568-d2e6015001d6 · outbound

This paper cites A fuzzy-logic architecture for autonomous multisensor data fusion,.

Preventing Adversarial AI Attacks Against Autonomous Situational Awareness: A Maritime Case Study A fuzzy-logic architecture for autonomous multisensor data fusion,

Reference 69

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:33:07.038379Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:33:01.482864Z digest=sha256:633cfcb95a31e0d431eb0b2a80e88092eaac1348de2c758b93a0189c141527ad

Observation dd52c970-cb58-4302-aac4-25e06c77dc12 · outbound

This paper cites Practical moving target detection in maritime environments using fuzzy multi-sensor data fusion,.

Preventing Adversarial AI Attacks Against Autonomous Situational Awareness: A Maritime Case Study Practical moving target detection in maritime environments using fuzzy multi-sensor data fusion,

Reference 70

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:33:06.809718Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:33:01.542023Z digest=sha256:6612af772d6be619823a7217dcb2d359da030a31be4c5bb1deef2144f449ebbf

Observation 4e58d443-71d0-40a9-be36-29c65432a86c · outbound

This paper cites Multisensor tracking of marine targets: Decentralized fusion of kalman and neural filters,.

Preventing Adversarial AI Attacks Against Autonomous Situational Awareness: A Maritime Case Study Multisensor tracking of marine targets: Decentralized fusion of kalman and neural filters,

Reference 71

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:33:06.690003Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:33:01.609806Z digest=sha256:26963f0ead6baa9213f2488303e6cb3d8bc816099f86d6a66b277ee6eba8ab41

Observation 96e5c63f-b65a-416f-98cd-a2404b7aebc6 · outbound

This paper cites Image and ais data fusion technique for maritime computer vision applications,.

Preventing Adversarial AI Attacks Against Autonomous Situational Awareness: A Maritime Case Study Image and ais data fusion technique for maritime computer vision applications,

Reference 72

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:33:06.469581Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:33:01.675701Z digest=sha256:964fed8e1875e1b856d19b1a39f9c066da17ad2e22af9c8799cafd30b47b47ed

Observation 9ba9e486-0f5e-42e4-b3b9-a0c8c37ee228 · outbound

This paper cites A CNNGRU-MHA method for ship trajectory prediction based on marine fusion data,.

Preventing Adversarial AI Attacks Against Autonomous Situational Awareness: A Maritime Case Study A CNNGRU-MHA method for ship trajectory prediction based on marine fusion data,

Reference 73

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:33:06.203440Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:33:01.698295Z digest=sha256:c29042d700d820807eec1fe18051f9c74b9fe78f60378f8dd67aa5b0e10b6f5c

Observation 16014b7f-8372-4e3e-8deb-1319794aefa1 · outbound

This paper cites Ship wake detection using data fusion in multi-sensor remote sensing applications,.

Preventing Adversarial AI Attacks Against Autonomous Situational Awareness: A Maritime Case Study Ship wake detection using data fusion in multi-sensor remote sensing applications,

Reference 74

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:33:05.904564Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:33:01.767459Z digest=sha256:aa2e0943c22317822c624e6e8c899d178797c2205890985e9aa6f5fc7107d4f3

Observation e134f372-db7a-4251-83b9-cd69e7a96675 · outbound

This paper cites Deep-learning approach based on multi-data fusion for damage recognition of marine platforms under complex loads,.

Preventing Adversarial AI Attacks Against Autonomous Situational Awareness: A Maritime Case Study Deep-learning approach based on multi-data fusion for damage recognition of marine platforms under complex loads,

Reference 75

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:33:05.685305Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:33:01.830120Z digest=sha256:d43802f67c48614210ed9e142620cf9e472ebe5a33b5c60d1992d1390c6f6732

Observation c31bd52a-14a6-409f-9fba-876d1c03fdfb · outbound

This paper cites Batman: A brain-like approach for tracking maritime activity and nuance,.

Preventing Adversarial AI Attacks Against Autonomous Situational Awareness: A Maritime Case Study Batman: A brain-like approach for tracking maritime activity and nuance,

Reference 76

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:33:05.444417Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:33:01.938059Z digest=sha256:f3e344726ed4d8ef4def1c9d8c7cf31eba4bec46c7c59fd938c67492c269f1ed

Observation abdabc06-6e02-4dd8-9297-fe0dda02c7c8 · outbound

This paper cites Remote and autonomous ships,.

Preventing Adversarial AI Attacks Against Autonomous Situational Awareness: A Maritime Case Study Remote and autonomous ships,

Reference 77

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:33:05.251831Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:33:02.031589Z digest=sha256:22c071a005cd292c8de7c6e2b5483311eb065b22907fb0b4fcc4eef32bffbea4

Observation 67aa8dcb-43f7-4d1c-8e84-d50fdd379951 · outbound

This paper cites Bon voyage for the autonomous ship mayflower,.

Preventing Adversarial AI Attacks Against Autonomous Situational Awareness: A Maritime Case Study Bon voyage for the autonomous ship mayflower,

Reference 78

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:33:05.106396Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:33:02.120372Z digest=sha256:a61a0a3f426d2e228776a27f7a868d56e613bb063dad619d514e7e2b391d0b51

Observation 162302fe-605e-4681-b7b0-7965d38aed50 · outbound

This paper cites Design and assessment of a low-cost autonomous control system to mitigate effects of communication dropouts in uncrewed surface vessels,.

Preventing Adversarial AI Attacks Against Autonomous Situational Awareness: A Maritime Case Study Design and assessment of a low-cost autonomous control system to mitigate effects of communication dropouts in uncrewed surface vessels,

Reference 79

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:33:04.985436Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:33:02.200157Z digest=sha256:a74ceb2c410cf6eb4070ea937d508349d436c3564a0f47a002773319acfb691c

Observation 1e4960b4-fbf8-4e32-a3cf-588068138760 · outbound

This paper cites Sensors and AI techniques for situational awareness in au- tonomous ships: A review,.

Preventing Adversarial AI Attacks Against Autonomous Situational Awareness: A Maritime Case Study Sensors and AI techniques for situational awareness in au- tonomous ships: A review,

Reference 80

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:33:04.886764Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:33:02.272516Z digest=sha256:ee840d54bee46f662cced27d94c4959902889dbfa10215f1834446c2e8f1c5e4

Observation 806452aa-cac7-468c-aa51-bb5d55a824d4 · outbound

This paper cites A study of the effect of JPG compression on adversarial images.

Preventing Adversarial AI Attacks Against Autonomous Situational Awareness: A Maritime Case Study A study of the effect of JPG compression on adversarial images

Reference 81

Resolution
unresolved
no resolver link, observed 2026-08-07T13:33:02.354014Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:33:02.354014Z digest=sha256:69bd091397e3cde56edc94603baddd24eca68847daa9f496cca384be0f73588b

Observation 4a3ca3d9-9a85-4c01-9f4b-0d9fba0a9107 · outbound

This paper cites YOLO by Ultralytics,.

Preventing Adversarial AI Attacks Against Autonomous Situational Awareness: A Maritime Case Study YOLO by Ultralytics,

Reference 82

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:33:04.757226Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:33:02.440709Z digest=sha256:f200bff5d6f07050f0f7f48c815f66cb0736e0650c872ea3010aeeb1826e0b70

Observation 7861661c-0edc-4586-a92d-f501ab4b600c · outbound

This paper cites End-to-end object detection with transformers,.

Preventing Adversarial AI Attacks Against Autonomous Situational Awareness: A Maritime Case Study End-to-end object detection with transformers,

Reference 83

Resolution
unresolved
no resolver link, observed 2026-08-07T13:33:02.498133Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:33:02.498133Z digest=sha256:41419b00c118adf1c28ceaefc469292c5462022d62d008ea57f9d6672d7a592c

Observation 9ed2198a-715b-481f-a168-e672c38a2b94 · outbound

This paper cites Future of maritime autonomy: cybersecurity, trust and mariner’s situational awareness,.

Preventing Adversarial AI Attacks Against Autonomous Situational Awareness: A Maritime Case Study Future of maritime autonomy: cybersecurity, trust and mariner’s situational awareness,

Reference 84

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:33:04.650217Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:33:02.587560Z digest=sha256:04a9bb97ca6e33f7dbf47e7c823d73aa01325ad016e9a3e499cc21735e2dcf8c

Observation 6143c645-6e2c-4815-864b-df8185a63456 · outbound

This paper cites An evolutionary many-objective optimization algorithm using reference-point-based nondominated sorting approach, part I: solving problems with box constraints,.

Preventing Adversarial AI Attacks Against Autonomous Situational Awareness: A Maritime Case Study An evolutionary many-objective optimization algorithm using reference-point-based nondominated sorting approach, part I: solving problems with box constraints,

Reference 85

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:33:04.536608Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:33:02.664986Z digest=sha256:679c0a9a3503bce0db555ee4da908bf4f672da3cc36f6c6e9ce3b9ade1c35f82

Observation bc2367f0-bad4-4154-8619-735ff71a746b · outbound

This paper cites Evolutionary art attack for black-box adversarial example generation,.

Preventing Adversarial AI Attacks Against Autonomous Situational Awareness: A Maritime Case Study Evolutionary art attack for black-box adversarial example generation,

Reference 86

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:33:04.336982Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:33:02.744445Z digest=sha256:50b5b1737649f9dcd74e90ba0188eb9344ca9f21f3a912aff7f4430e493b70aa

Observation 045e4797-a95a-4c2e-816d-a8552fa21689 · outbound

This paper cites Jpeg-resistant adversarial images,.

Preventing Adversarial AI Attacks Against Autonomous Situational Awareness: A Maritime Case Study Jpeg-resistant adversarial images,

Reference 87

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:33:04.195194Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:33:02.858728Z digest=sha256:3b19648c40634b50b27318ddad02d0f2492651b338391703a92aa120d7365a8c

Observation de0290fc-65a0-4d44-b787-06b6272b7bfd · outbound

This paper cites AIS spoofing: A tutorial for researchers,.

Preventing Adversarial AI Attacks Against Autonomous Situational Awareness: A Maritime Case Study AIS spoofing: A tutorial for researchers,

Reference 88

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:33:04.045505Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:33:02.922863Z digest=sha256:0c7cc759ddc1b2589d8385c7b8299c8f7362ce1fa472e54ddc458ca10b2c617b

Observation 44ff6ec5-5c75-4aa5-bc72-c02184222131 · outbound

This paper cites Cyber-risk assessment for autonomous ships,.

Preventing Adversarial AI Attacks Against Autonomous Situational Awareness: A Maritime Case Study Cyber-risk assessment for autonomous ships,

Reference 89

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:33:03.940936Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:33:03.003941Z digest=sha256:b8cc8675205d544b85f2af37c54f55df970e89d8e12031b490ecf219fec7e0ad

Observation 7167d89a-bc28-4d7e-b4b8-a5b94a0eea15 · outbound

This paper cites Slowformer: Adversarial attack on compute and energy consumption of efficient vision transformers,.

Preventing Adversarial AI Attacks Against Autonomous Situational Awareness: A Maritime Case Study Slowformer: Adversarial attack on compute and energy consumption of efficient vision transformers,

Reference 90

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:33:03.813481Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:33:03.086873Z digest=sha256:2d1c507a507f68442e07b72be20ad09e1401931237b49a058d6b1bada261232e

Observation fe20c679-8484-4d28-94ac-a3a44d9c2688 · outbound

This paper cites Available: https://www.ncsc.gov.uk/blog-post/ thinking-about-security-ai-systems.

Preventing Adversarial AI Attacks Against Autonomous Situational Awareness: A Maritime Case Study Available: https://www.ncsc.gov.uk/blog-post/ thinking-about-security-ai-systems

Reference 2023

Resolution
unresolved
no resolver link, observed 2026-08-07T13:32:55.765248Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:32:55.765248Z digest=sha256:4ab0223344b660ebe6e8db746b0fffc6d7e9db21fde591dd2eb8f2dcfebccf24

Pith citing papers

No inbound Pith citation observations are available.