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Paper Citation Record · LEDGER

Defending Retrieval-Augmented Intrusion Detection Against Knowledge Poisoning and Prompt Injection

As of 18 August 2026, this Paper Citation Record lists 43 of 43 outbound references and 0 inbound Pith citation observations for arXiv:2608.08100.

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

pith.paper-citation-record.v1
2608.08100 v1

Coverage vector

measured 43 of 43 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T00:31:12.301022Z

measured 43 of 43 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

43 of 43 outbound references displayed

  • verified exact0
  • verified fuzzy33
  • unresolved10
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation d9f87155-605a-4a4e-8f91-f11e4a9b37d5 · outbound

This paper cites PoisonedRAG: Knowledge Cor- ruption Attacks to Retrieval-Augmented Generation,.

Defending Retrieval-Augmented Intrusion Detection Against Knowledge Poisoning and Prompt Injection PoisonedRAG: Knowledge Cor- ruption Attacks to Retrieval-Augmented Generation,

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T00:31:13.259350Z

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.

source=pdf_text observed=2026-08-12T00:31:12.097473Z digest=sha256:1d3946e10a64feb14daf31308f604323e1fcbfdafc46816469547e9454dbb218

Observation 5a289b0a-04ae-4529-80e9-ac804b968193 · outbound

This paper cites Temporal Dynamics of Memory Poisoning in Web3-Style LLM Agents,.

Defending Retrieval-Augmented Intrusion Detection Against Knowledge Poisoning and Prompt Injection Temporal Dynamics of Memory Poisoning in Web3-Style LLM Agents,

Reference 2

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verified fuzzy
raw_fallback, observed 2026-08-12T00:31:13.244285Z

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.

source=pdf_text observed=2026-08-12T00:31:12.103121Z digest=sha256:9d08ab1400f637907752906b2b62e7547f76ad66086b0817663ec69ad31e024d

Observation 561603f7-a009-4921-8046-9a3abd40da30 · outbound

This paper cites Not What You’ve Signed Up For: Compromising Real-World LLM-Integrated Applications with Indirect Prompt Injec- tion,.

Defending Retrieval-Augmented Intrusion Detection Against Knowledge Poisoning and Prompt Injection Not What You’ve Signed Up For: Compromising Real-World LLM-Integrated Applications with Indirect Prompt Injec- tion,

Reference 3

Resolution
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raw_fallback, observed 2026-08-12T00:31:13.229170Z

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.

source=pdf_text observed=2026-08-12T00:31:12.108287Z digest=sha256:281d792fd5cc859b0c2f7128b75ffd80ce3e8cd22f1407d725f63f5e06bf01ac

Observation c7273308-16ed-4f82-b79e-48bf680f61df · outbound

This paper cites SafeRAG: Benchmarking Security in Retrieval- Augmented Generation of Large Language Models,.

Defending Retrieval-Augmented Intrusion Detection Against Knowledge Poisoning and Prompt Injection SafeRAG: Benchmarking Security in Retrieval- Augmented Generation of Large Language Models,

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T00:31:13.213985Z

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.

source=pdf_text observed=2026-08-12T00:31:12.113209Z digest=sha256:1c785f77d56ef12873661b113c5544a4445c84161434844947b31e0c0ff4f48e

Observation b73f9c55-69f3-404b-a939-15df1af7edce · outbound

This paper cites Outside the Closed World: On Using Machine Learning for Network Intrusion Detection,.

Defending Retrieval-Augmented Intrusion Detection Against Knowledge Poisoning and Prompt Injection Outside the Closed World: On Using Machine Learning for Network Intrusion Detection,

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T00:31:13.199712Z

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.

source=pdf_text observed=2026-08-12T00:31:12.118571Z digest=sha256:af23d323fb8b5eae02887dbf95d9bd1150cf3d551054f51023dfc84f02a92046

Observation cca24721-3864-411a-8314-ee4f19ee2b22 · outbound

This paper cites The Base-Rate Fallacy and Its Implications for the Difficulty of Intrusion Detection,.

Defending Retrieval-Augmented Intrusion Detection Against Knowledge Poisoning and Prompt Injection The Base-Rate Fallacy and Its Implications for the Difficulty of Intrusion Detection,

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T00:31:13.184556Z

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.

source=pdf_text observed=2026-08-12T00:31:12.123542Z digest=sha256:75b5135a340c228e260cda592939b9c510bd7792fd1d8b5e1ef39c5c1c580720

Observation 52be8446-2ee7-4867-a18e-ddb1825b6f21 · outbound

This paper cites UNSW-NB15: A Comprehensive Data Set for Network Intrusion Detection Systems,.

Defending Retrieval-Augmented Intrusion Detection Against Knowledge Poisoning and Prompt Injection UNSW-NB15: A Comprehensive Data Set for Network Intrusion Detection Systems,

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T00:31:13.170082Z

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.

source=pdf_text observed=2026-08-12T00:31:12.129119Z digest=sha256:2bcb0aa9e13442cf799e4ebc50c8f0c2a5edcb7989649fdedcf2bc46ed415455

Observation 7e653bc4-b1b5-4b29-9a99-af385e6d08d3 · outbound

This paper cites Poisoning and Evasion: Deep Learning-Based NIDS under Adversarial Attacks,.

Defending Retrieval-Augmented Intrusion Detection Against Knowledge Poisoning and Prompt Injection Poisoning and Evasion: Deep Learning-Based NIDS under Adversarial Attacks,

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T00:31:13.155096Z

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.

source=pdf_text observed=2026-08-12T00:31:12.134075Z digest=sha256:b62fb815ad6dc87a34eb53ca00b9dffb07055c917672fe2248555d6132788c37

Observation 5f237742-4fd8-4159-841a-8f6b88100e99 · outbound

This paper cites Retrieval-Augmented Generation for Knowledge- Intensive NLP Tasks,.

Defending Retrieval-Augmented Intrusion Detection Against Knowledge Poisoning and Prompt Injection Retrieval-Augmented Generation for Knowledge- Intensive NLP Tasks,

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T00:31:13.140259Z

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.

source=pdf_text observed=2026-08-12T00:31:12.139224Z digest=sha256:4fc2b63739af91b027dd82ed9afe233b2c7ea00e8899cc2a4cc72a65a1e3265a

Observation bb0e40b1-9d54-4e7d-a8a8-56c5aadf11a0 · outbound

This paper cites RAGAS: Automated Evaluation of Retrieval Augmented Generation,.

Defending Retrieval-Augmented Intrusion Detection Against Knowledge Poisoning and Prompt Injection RAGAS: Automated Evaluation of Retrieval Augmented Generation,

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T00:31:13.126045Z

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.

source=pdf_text observed=2026-08-12T00:31:12.144334Z digest=sha256:86f87539a471501404d2f8a6bdeecd51d1521e75fab2076357f4143852816bfc

Observation ac4b5711-b39b-4dea-b3bc-0e1ba64e23b0 · outbound

This paper cites C-Pack: Packed Resources For General Chinese Embeddings.

Defending Retrieval-Augmented Intrusion Detection Against Knowledge Poisoning and Prompt Injection C-Pack: Packed Resources For General Chinese Embeddings

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-12T00:31:12.149279Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T00:31:12.149279Z digest=sha256:d08b286b5d7fadc23cbd1ce27395082e71fb6ab63fdc459ccffbc06769384da7

Observation 11a0d23d-e37a-4681-8f28-ee0dc4d4b295 · outbound

This paper cites The Probabilistic Relevance Framework: BM25 and Beyond,.

Defending Retrieval-Augmented Intrusion Detection Against Knowledge Poisoning and Prompt Injection The Probabilistic Relevance Framework: BM25 and Beyond,

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T00:31:13.111018Z

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.

source=pdf_text observed=2026-08-12T00:31:12.154615Z digest=sha256:a3ae8914c2cfa2f8f09848a1105f8a3123b12f646ec17e513232f4767c7999ca

Observation 05764f3d-66c4-4952-9341-195e06de55f5 · outbound

This paper cites Reciprocal Rank Fusion Outperforms Condorcet and Individual Rank Learning Methods,.

Defending Retrieval-Augmented Intrusion Detection Against Knowledge Poisoning and Prompt Injection Reciprocal Rank Fusion Outperforms Condorcet and Individual Rank Learning Methods,

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T00:31:13.096700Z

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.

source=pdf_text observed=2026-08-12T00:31:12.159628Z digest=sha256:b76c7ffbb83d92fbdf395437cf1e913dcec8179894d4e89c80f7a5dae8a7844f

Observation 9409e9d3-3259-4e1b-bc51-299fbc4f6cce · outbound

This paper cites Random Forests,.

Defending Retrieval-Augmented Intrusion Detection Against Knowledge Poisoning and Prompt Injection Random Forests,

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T00:31:13.082297Z

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.

source=pdf_text observed=2026-08-12T00:31:12.164222Z digest=sha256:d3718d86f5dceaee7d511dded4c2d8b0eb95f53cff2bf2dc9575080148e5e6a1

Observation b5f1b1d6-e1bd-412a-bf2f-7bdc53f14bdf · outbound

This paper cites XGBoost: A Scalable Tree Boosting System,.

Defending Retrieval-Augmented Intrusion Detection Against Knowledge Poisoning and Prompt Injection XGBoost: A Scalable Tree Boosting System,

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T00:31:13.067570Z

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.

source=pdf_text observed=2026-08-12T00:31:12.168852Z digest=sha256:fc8c8e2eab2912dcf02b52569d93be7ada85826fc9303a7d6179780dc50dc110

Observation 076c0105-16a0-4fea-9be4-fbb019bb89e4 · outbound

This paper cites A Survey of Network-Based Intrusion Detection Data Sets,.

Defending Retrieval-Augmented Intrusion Detection Against Knowledge Poisoning and Prompt Injection A Survey of Network-Based Intrusion Detection Data Sets,

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T00:31:13.053240Z

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.

source=pdf_text observed=2026-08-12T00:31:12.173054Z digest=sha256:0f85a43af9e08777804faba3418bccd1dd1458c0a0ebbcc6f13984dab3a12d6e

Observation 8a7aa011-9f27-4fb9-9ad8-bbf344820433 · outbound

This paper cites Cy- berRAG: An Agentic RAG Cyber Attack Classification and Reporting Tool,.

Defending Retrieval-Augmented Intrusion Detection Against Knowledge Poisoning and Prompt Injection Cy- berRAG: An Agentic RAG Cyber Attack Classification and Reporting Tool,

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T00:31:13.038318Z

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.

source=pdf_text observed=2026-08-12T00:31:12.177147Z digest=sha256:7d03e3d11dbf88f56f007c0a6a7345bf8d00abff4b62559e78aef23b77d66a30

Observation c8769d73-ef09-4c12-b4fd-3ccce4480f7e · outbound

This paper cites MA-IDS: Multi-Agent RAG Framework for IoT Network Intrusion Detection with an Experience Library.

Defending Retrieval-Augmented Intrusion Detection Against Knowledge Poisoning and Prompt Injection MA-IDS: Multi-Agent RAG Framework for IoT Network Intrusion Detection with an Experience Library

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-12T00:31:12.181329Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T00:31:12.181329Z digest=sha256:44c06f5ade59dc27b59fe720267ac025e5262d476529f0469ed89bb4b905caf6

Observation e197c7b7-70ff-429b-acd6-f795017b843a · outbound

This paper cites FALCON: Transforming Cyber Threat Intelligence into Deployable IDS Rules with Self-Reflection.

Defending Retrieval-Augmented Intrusion Detection Against Knowledge Poisoning and Prompt Injection FALCON: Transforming Cyber Threat Intelligence into Deployable IDS Rules with Self-Reflection

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-12T00:31:12.186108Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T00:31:12.186108Z digest=sha256:0d34a69f518cfbcaec5d46cfbe22fa39bdd85e79ef66c6c9d6f7124367243c4d

Observation 962c72b9-fb6e-4970-907c-99d332ae06d6 · outbound

This paper cites FlowTransformer: A Transformer Framework for Flow-Based Network Intrusion Detection Systems,.

Defending Retrieval-Augmented Intrusion Detection Against Knowledge Poisoning and Prompt Injection FlowTransformer: A Transformer Framework for Flow-Based Network Intrusion Detection Systems,

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T00:31:13.023103Z

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.

source=pdf_text observed=2026-08-12T00:31:12.190636Z digest=sha256:1c1ff66680b48016f01aab353af5ac0d459416ea5777cf53af9c714da6b5faa6

Observation c94b06fd-b20a-4bf6-b0c4-3ae309e1ed46 · outbound

This paper cites Billion-Scale Similarity Search with GPUs,.

Defending Retrieval-Augmented Intrusion Detection Against Knowledge Poisoning and Prompt Injection Billion-Scale Similarity Search with GPUs,

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T00:31:13.007490Z

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.

source=pdf_text observed=2026-08-12T00:31:12.195134Z digest=sha256:19a7d34ab04ba10a6e5f901d8053bd28c24648d6eb882a3bdb5d24797adda5f4

Observation c1d94f46-8613-4045-9723-3885c6784161 · outbound

This paper cites SMOTE: Synthetic Minority Over-sampling Technique,.

Defending Retrieval-Augmented Intrusion Detection Against Knowledge Poisoning and Prompt Injection SMOTE: Synthetic Minority Over-sampling Technique,

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T00:31:12.991141Z

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.

source=pdf_text observed=2026-08-12T00:31:12.200140Z digest=sha256:7121172585c56f503789adb6642bfb4dfb3c64b0b0614fc0bfc81e06db18b625

Observation e4dbfa03-50bc-46cc-8727-ca6b6d7243b0 · outbound

This paper cites Benchmarking and Defending Against Indirect Prompt Injection Attacks on Large Language Models.

Defending Retrieval-Augmented Intrusion Detection Against Knowledge Poisoning and Prompt Injection Benchmarking and Defending Against Indirect Prompt Injection Attacks on Large Language Models

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-12T00:31:12.204782Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T00:31:12.204782Z digest=sha256:8e45b549284ee778f07ccec29640f691c7459af0c72f14f766cdc5681405da34

Observation 6073300e-9ef7-48e0-95cd-99ddb8e0f477 · outbound

This paper cites Basic Con- cepts and Taxonomy of Dependable and Secure Computing,.

Defending Retrieval-Augmented Intrusion Detection Against Knowledge Poisoning and Prompt Injection Basic Con- cepts and Taxonomy of Dependable and Secure Computing,

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T00:31:12.976006Z

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.

source=pdf_text observed=2026-08-12T00:31:12.210069Z digest=sha256:9757ed2d3fa27053fd1a6d1d48ae38da08445d7becac9bda4a61c3cf32631d4a

Observation 2adfcbbb-2611-4ee3-84ad-9e711c8bf373 · outbound

This paper cites Security Evaluation of Pattern Classifiers under Attack,.

Defending Retrieval-Augmented Intrusion Detection Against Knowledge Poisoning and Prompt Injection Security Evaluation of Pattern Classifiers under Attack,

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T00:31:12.960727Z

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.

source=pdf_text observed=2026-08-12T00:31:12.214428Z digest=sha256:41e1d3d97462a3ae48469cc3aaa34e96347d371e2d6b59238a13d1af27ff9761

Observation 02f17696-ed1e-4511-82f2-0f1b4280aa15 · outbound

This paper cites Wild Patterns: Ten Years After the Rise of Adversarial Machine Learning,.

Defending Retrieval-Augmented Intrusion Detection Against Knowledge Poisoning and Prompt Injection Wild Patterns: Ten Years After the Rise of Adversarial Machine Learning,

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T00:31:12.944754Z

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.

source=pdf_text observed=2026-08-12T00:31:12.219011Z digest=sha256:f3975815dcf823e91d8d61b40512fb235660b1c4aba1e9651324be1774b3b209

Observation d10bb2a6-df30-445c-a118-37436469834f · outbound

This paper cites Dense Passage Retrieval for Open-Domain Ques- tion Answering,.

Defending Retrieval-Augmented Intrusion Detection Against Knowledge Poisoning and Prompt Injection Dense Passage Retrieval for Open-Domain Ques- tion Answering,

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T00:31:12.928443Z

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.

source=pdf_text observed=2026-08-12T00:31:12.223649Z digest=sha256:d9c678544a1b5942f6b57291e790bc0fae2010841a2f351eb209961162f88e0c

Observation 3805553e-b315-4433-9892-a5aabd11d051 · outbound

This paper cites Retrieval-Augmented Generation for Large Language Models: A Survey.

Defending Retrieval-Augmented Intrusion Detection Against Knowledge Poisoning and Prompt Injection Retrieval-Augmented Generation for Large Language Models: A Survey

Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-12T00:31:12.228187Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T00:31:12.228187Z digest=sha256:6f95c522b9cd7c5374063bec4cb1cdb257124303f95dd0864b07625b79982615

Observation 3193cebe-57b4-44f0-9a87-16bb569380dd · outbound

This paper cites Adversarial Machine Learning: A Taxonomy and Terminology of Attacks and Mitigations,.

Defending Retrieval-Augmented Intrusion Detection Against Knowledge Poisoning and Prompt Injection Adversarial Machine Learning: A Taxonomy and Terminology of Attacks and Mitigations,

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T00:31:12.913023Z

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.

source=pdf_text observed=2026-08-12T00:31:12.234019Z digest=sha256:2fdd3ffe2b219bdb6fb3512e31b37bd87077be3a832175d6c39c12d7cc9ee66e

Observation 0d8821d1-c191-44fa-955e-f9a06a7602c9 · outbound

This paper cites Kitsune: An Ensemble of Autoencoders for Online Network Intrusion Detection,.

Defending Retrieval-Augmented Intrusion Detection Against Knowledge Poisoning and Prompt Injection Kitsune: An Ensemble of Autoencoders for Online Network Intrusion Detection,

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T00:31:12.896184Z

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.

source=pdf_text observed=2026-08-12T00:31:12.238968Z digest=sha256:ca8162e54d49ad4a22e11177c923d88782d8dd475033e3d60c252d4789916435

Observation d766553c-6d5d-42cd-a901-7cb5578c4a13 · outbound

This paper cites On the Effectiveness of Machine and Deep Learning for Cyber Secu- rity,.

Defending Retrieval-Augmented Intrusion Detection Against Knowledge Poisoning and Prompt Injection On the Effectiveness of Machine and Deep Learning for Cyber Secu- rity,

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T00:31:12.880861Z

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.

source=pdf_text observed=2026-08-12T00:31:12.244159Z digest=sha256:f164a5e7dc63503ae023d54df0e0bc0b034a605d85cbb0021cb1c47062baf66e

Observation 59bd10ca-a856-4463-80d2-2ff910165dad · outbound

This paper cites Toward Generating a New Intrusion Detection Dataset and Intrusion Traffic Characteriza- tion,.

Defending Retrieval-Augmented Intrusion Detection Against Knowledge Poisoning and Prompt Injection Toward Generating a New Intrusion Detection Dataset and Intrusion Traffic Characteriza- tion,

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T00:31:12.864964Z

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.

source=pdf_text observed=2026-08-12T00:31:12.248982Z digest=sha256:681af13fbbd9b7280aaa5964c9e1dc64f21a6ec1e69cd48f168f9ef2f7bfdb45

Observation 993d9eee-5f9a-4be0-ad7a-e240d406ba78 · outbound

This paper cites The Evaluation of Network Anomaly Detec- tion Systems: Statistical Analysis of the UNSW-NB15 Data Set,.

Defending Retrieval-Augmented Intrusion Detection Against Knowledge Poisoning and Prompt Injection The Evaluation of Network Anomaly Detec- tion Systems: Statistical Analysis of the UNSW-NB15 Data Set,

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T00:31:12.848844Z

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.

source=pdf_text observed=2026-08-12T00:31:12.253686Z digest=sha256:5d80885a7a71ca1bb4646d6dd8d8f70de8636ad396553229a55fc2269f36afb8

Observation 95ac9cca-b663-4072-89a1-72c76f51a39f · outbound

This paper cites Phantom: General Trigger Attacks on Retrieval Augmented Language Generation,.

Defending Retrieval-Augmented Intrusion Detection Against Knowledge Poisoning and Prompt Injection Phantom: General Trigger Attacks on Retrieval Augmented Language Generation,

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-12T00:31:12.258416Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T00:31:12.258416Z digest=sha256:ac1eee6246b754f21e1c323bc48d9ad62be116c3565c02b5c583710c98ace630

Observation 272564cc-6dee-4971-b26c-ba64eeebd544 · outbound

This paper cites Practical Poisoning Attacks against Retrieval- Augmented Generation,.

Defending Retrieval-Augmented Intrusion Detection Against Knowledge Poisoning and Prompt Injection Practical Poisoning Attacks against Retrieval- Augmented Generation,

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-12T00:31:12.263349Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T00:31:12.263349Z digest=sha256:7d684ca49c982107fd9badeec403d3ec565dc1aa3e7f730dd7ee70bcf4134e20

Observation 493cb7af-da58-49ae-b1ef-462bc84e77d7 · outbound

This paper cites Defending Against Knowledge Poisoning Attacks During Retrieval-Augmented Generation,.

Defending Retrieval-Augmented Intrusion Detection Against Knowledge Poisoning and Prompt Injection Defending Against Knowledge Poisoning Attacks During Retrieval-Augmented Generation,

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-12T00:31:12.268147Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T00:31:12.268147Z digest=sha256:5a2d542f88b31cfe82dcdbd8422a261bd1823ecc2aad3d8aa7853028f88e3c6a

Observation 89ab000e-6796-42c2-8a62-71f4e4cc5586 · outbound

This paper cites A Detailed Analysis of the KDD CUP 99 Data Set,.

Defending Retrieval-Augmented Intrusion Detection Against Knowledge Poisoning and Prompt Injection A Detailed Analysis of the KDD CUP 99 Data Set,

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T00:31:12.830894Z

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.

source=pdf_text observed=2026-08-12T00:31:12.273212Z digest=sha256:643d18788b4fa5f01b88abcc117f9b892ab3223f63d306313a9bdee335aa7230

Observation c8b67d59-6e17-4a83-9ea4-5546578c94ac · outbound

This paper cites Long Short-Term Memory,.

Defending Retrieval-Augmented Intrusion Detection Against Knowledge Poisoning and Prompt Injection Long Short-Term Memory,

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-12T00:31:12.277789Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T00:31:12.277789Z digest=sha256:1368bd94885a149b2060274f9ee944f403dda20a80a52a7bdc2c1d6dbb843510

Observation c9504cd2-7b1a-413b-885a-e31c21afab06 · outbound

This paper cites Intrusion Detection System: A Comprehensive Review,.

Defending Retrieval-Augmented Intrusion Detection Against Knowledge Poisoning and Prompt Injection Intrusion Detection System: A Comprehensive Review,

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T00:31:12.801239Z

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.

source=pdf_text observed=2026-08-12T00:31:12.282356Z digest=sha256:f27c4cdb53148918bace14cc03f1b244117b87200d2b9af925df5d01c146f545

Observation 285bc6a6-34ed-4d32-9aea-79c230a2b942 · outbound

This paper cites A Survey of Data Mining and Machine Learning Methods for Cyber Security Intrusion Detection,.

Defending Retrieval-Augmented Intrusion Detection Against Knowledge Poisoning and Prompt Injection A Survey of Data Mining and Machine Learning Methods for Cyber Security Intrusion Detection,

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T00:31:12.785595Z

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.

source=pdf_text observed=2026-08-12T00:31:12.286992Z digest=sha256:930e47bfb00b0c4cad84ab402a52a8bcbe7b86aa725bb9e49f130f577adaa918

Observation e411a902-c511-4677-9922-70a89cbf5c26 · outbound

This paper cites A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open Questions,.

Defending Retrieval-Augmented Intrusion Detection Against Knowledge Poisoning and Prompt Injection A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open Questions,

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T00:31:12.770005Z

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.

source=pdf_text observed=2026-08-12T00:31:12.291663Z digest=sha256:b98f46fe45efc461b288074ec339d5f0702d4e6132f063a3174890463d2b5b50

Observation a4bade74-f5a5-487a-9c84-5cad1712eaa6 · outbound

This paper cites Traceback of Poisoning Attacks to Retrieval- Augmented Generation,.

Defending Retrieval-Augmented Intrusion Detection Against Knowledge Poisoning and Prompt Injection Traceback of Poisoning Attacks to Retrieval- Augmented Generation,

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T00:31:12.754204Z

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.

source=pdf_text observed=2026-08-12T00:31:12.296399Z digest=sha256:9e48cf651e459b2a0195763a62ff3e42a4f72bbf3f7eca672394170cd1927498

Observation fef6f70f-e3ab-4355-b74e-1b7df5ac0591 · outbound

This paper cites CPA-RAG:Covert Poisoning Attacks on Retrieval-Augmented Generation in Large Language Models.

Defending Retrieval-Augmented Intrusion Detection Against Knowledge Poisoning and Prompt Injection CPA-RAG:Covert Poisoning Attacks on Retrieval-Augmented Generation in Large Language Models

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-12T00:31:12.301022Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T00:31:12.301022Z digest=sha256:1f6795e428dc1995b7b1b4b0c4171f49a6be9e6648c4ec45a18664d6ff6d67ee

Pith citing papers

No inbound Pith citation observations are available.