Beyond Heavy Log Curation: Perplexity-Based APT Detection via Unsupervised, Context-Augmented Language Models | Paper Citation Record

Observation 6909902a-903d-4c7a-b6fe-8f98da965906 · outbound

This paper cites On the reproducibility of provenance-based intrusion detection that uses deep learning.

Beyond Heavy Log Curation: Perplexity-Based APT Detection via Unsupervised, Context-Augmented Language Models On the reproducibility of provenance-based intrusion detection that uses deep learning

Reference 1

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Observation 7a97a281-fc5a-4485-9b5f-9d50c98b457c · outbound

This paper cites Clouseau: A hierarchical multi-agent approach for au- tonomous attack investigation.

Beyond Heavy Log Curation: Perplexity-Based APT Detection via Unsupervised, Context-Augmented Language Models Clouseau: A hierarchical multi-agent approach for au- tonomous attack investigation

Reference 2

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Observation cfe6cc52-cc9d-44eb-b692-01afab65fc38 · outbound

This paper cites Berkay Celik, Xiangyu Zhang, and Dongyan Xu.

Beyond Heavy Log Curation: Perplexity-Based APT Detection via Unsupervised, Context-Augmented Language Models Berkay Celik, Xiangyu Zhang, and Dongyan Xu

Reference 3

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Observation b76906e3-34a0-414f-8f3d-f577846a44a2 · outbound

This paper cites Language models are few-shot learners.

Beyond Heavy Log Curation: Perplexity-Based APT Detection via Unsupervised, Context-Augmented Language Models Language models are few-shot learners

Reference 4

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Beyond Heavy Log Curation: Perplexity-Based APT Detection via Unsupervised, Context-Augmented Language Models Unresolved cited work

Reference 5

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Observation 10e96583-ce5f-474d-aa19-e76e22350075 · outbound

This paper cites Kairos: Practical intrusion detection and investigation using whole-system provenance.

Beyond Heavy Log Curation: Perplexity-Based APT Detection via Unsupervised, Context-Augmented Language Models Kairos: Practical intrusion detection and investigation using whole-system provenance

Reference 6

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Observation e1b9f339-d062-4d2e-bc04-f441d31c5c96 · outbound

This paper cites Evaluation of BERT and ALBERT Sentence Embedding Performance on Downstream NLP Tasks.

Beyond Heavy Log Curation: Perplexity-Based APT Detection via Unsupervised, Context-Augmented Language Models Evaluation of BERT and ALBERT Sentence Embedding Performance on Downstream NLP Tasks

Reference 7

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Observation 0efe28bf-865a-4bc3-9405-530337be5d02 · outbound

This paper cites Clue: A high-performance, efficient, and robust apt detection framework via fine- tuning pretrained transformer and contrastive learning.

Beyond Heavy Log Curation: Perplexity-Based APT Detection via Unsupervised, Context-Augmented Language Models Clue: A high-performance, efficient, and robust apt detection framework via fine- tuning pretrained transformer and contrastive learning

Reference 8

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Observation 83f55160-5025-433b-8c12-1d4594a15b5a · outbound

This paper cites gemma-3-1b-it (gemma 3 1b instruction-tuned) model card.

Beyond Heavy Log Curation: Perplexity-Based APT Detection via Unsupervised, Context-Augmented Language Models gemma-3-1b-it (gemma 3 1b instruction-tuned) model card

Reference 9

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Observation 0bcfa55f-3161-4ec4-a475-1eec24d2330b · outbound

This paper cites BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding.

Beyond Heavy Log Curation: Perplexity-Based APT Detection via Unsupervised, Context-Augmented Language Models BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Reference 10

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Observation 460a85b5-ec34-424d-8add-41a24de2905f · outbound

This paper cites AIRTAG: Towards automated attack investigation by unsupervised learning with log texts.

Beyond Heavy Log Curation: Perplexity-Based APT Detection via Unsupervised, Context-Augmented Language Models AIRTAG: Towards automated attack investigation by unsupervised learning with log texts

Reference 11

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Observation ca370b5a-7060-428f-8128-ae4b9923b949 · outbound

This paper cites Deeplog: Anomaly detection and diagnosis from system logs through deep learning.

Beyond Heavy Log Curation: Perplexity-Based APT Detection via Unsupervised, Context-Augmented Language Models Deeplog: Anomaly detection and diagnosis from system logs through deep learning

Reference 12

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Observation 2a2194fa-a398-4bda-b3d3-053267324f5d · outbound

This paper cites The llama 3 herd of models, 2024.

Beyond Heavy Log Curation: Perplexity-Based APT Detection via Unsupervised, Context-Augmented Language Models The llama 3 herd of models, 2024

Reference 13

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Observation 9d1fb625-d7ce-413e-a598-3f901a99b9db · outbound

This paper cites Back- Propagating system dependency impact for attack investigation.

Beyond Heavy Log Curation: Perplexity-Based APT Detection via Unsupervised, Context-Augmented Language Models Back- Propagating system dependency impact for attack investigation

Reference 14

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Observation 6bf8262c-b4cb-41e6-8aaa-3844194ca5a7 · outbound

This paper cites Logbert: Log anomaly detection via bert.

Beyond Heavy Log Curation: Perplexity-Based APT Detection via Unsupervised, Context-Augmented Language Models Logbert: Log anomaly detection via bert

Reference 15

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Observation 238d16ee-d8fa-471f-8706-cbd0ca50ba20 · outbound

This paper cites Log- gpt: Log anomaly detection via gpt.

Beyond Heavy Log Curation: Perplexity-Based APT Detection via Unsupervised, Context-Augmented Language Models Log- gpt: Log anomaly detection via gpt

Reference 16

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Observation 5e63e483-33bd-494d-82fb-bd90ee1b5a1b · outbound

This paper cites Application of large language models in cybersecurity: A systematic literature review.IEEE Access, 12:176751–176778, 2024.

Beyond Heavy Log Curation: Perplexity-Based APT Detection via Unsupervised, Context-Augmented Language Models Application of large language models in cybersecurity: A systematic literature review.IEEE Access, 12:176751–176778, 2024

Reference 17

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Observation 9bfc04b1-04ab-42d5-ad1e-6175a36d92cf · outbound

This paper cites A compre- hensive overview of large language models (llms) for cyber defences: Opportunities and directions, 2024.

Beyond Heavy Log Curation: Perplexity-Based APT Detection via Unsupervised, Context-Augmented Language Models A compre- hensive overview of large language models (llms) for cyber defences: Opportunities and directions, 2024

Reference 18

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Observation 4a0a400d-54ed-4b58-9bf1-b8f36be7cd38 · outbound

This paper cites an unresolved cited work.

Beyond Heavy Log Curation: Perplexity-Based APT Detection via Unsupervised, Context-Augmented Language Models Unresolved cited work

Reference 19

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Observation b42c9bfe-2ca4-45d0-965f-f4ea7958f135 · outbound

This paper cites Ml-mamba: Efficient multi-modal large language model utilizing mamba-2, 2024.

Beyond Heavy Log Curation: Perplexity-Based APT Detection via Unsupervised, Context-Augmented Language Models Ml-mamba: Efficient multi-modal large language model utilizing mamba-2, 2024

Reference 20

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Observation 1ef7bbae-c4ca-43f2-bf62-861ab4f49fae · outbound

This paper cites MAGIC: Detect- ing advanced persistent threats via masked graph representation learning.

Beyond Heavy Log Curation: Perplexity-Based APT Detection via Unsupervised, Context-Augmented Language Models MAGIC: Detect- ing advanced persistent threats via masked graph representation learning

Reference 21

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Observation a55f4484-0829-4476-9a10-c9d9c2e4532e · outbound

This paper cites Is bert really robust? a strong baseline for natural language attack on text classification and entail- ment.

Beyond Heavy Log Curation: Perplexity-Based APT Detection via Unsupervised, Context-Augmented Language Models Is bert really robust? a strong baseline for natural language attack on text classification and entail- ment

Reference 22

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Observation 469d5ce4-a77e-437d-aff9-0f1db4beed21 · outbound

This paper cites Deep learning for anomaly de- tection in log data: A survey.Machine Learning with Applications, 12:100470, June 2023.

Beyond Heavy Log Curation: Perplexity-Based APT Detection via Unsupervised, Context-Augmented Language Models Deep learning for anomaly de- tection in log data: A survey.Machine Learning with Applications, 12:100470, June 2023

Reference 23

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Observation 37f762f8-cd83-4d79-94e9-3f3ffdab1011 · outbound

This paper cites Lanobert: System log anomaly detection based on bert masked language model.Appl.

Beyond Heavy Log Curation: Perplexity-Based APT Detection via Unsupervised, Context-Augmented Language Models Lanobert: System log anomaly detection based on bert masked language model.Appl

Reference 24

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Observation 7a3643c0-a5b4-48b1-b6eb-a762a842ca17 · outbound

This paper cites BART: De- noising sequence-to-sequence pre-training for natural language generation, translation, and comprehension.

Beyond Heavy Log Curation: Perplexity-Based APT Detection via Unsupervised, Context-Augmented Language Models BART: De- noising sequence-to-sequence pre-training for natural language generation, translation, and comprehension

Reference 25

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Observation d4bd8780-b3e6-406c-94de-4c121a5a6ea5 · outbound

This paper cites Conlbs: An attack investigation approach using contrastive learning with behavior sequence.Sensors, 23(24), 2023.

Beyond Heavy Log Curation: Perplexity-Based APT Detection via Unsupervised, Context-Augmented Language Models Conlbs: An attack investigation approach using contrastive learning with behavior sequence.Sensors, 23(24), 2023

Reference 26

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Observation 15d7966c-4511-4226-af99-615acf84f01f · outbound

This paper cites Blip-2: Bootstrapping language-image pre-training with frozen image encoders and large language models, 2023.

Beyond Heavy Log Curation: Perplexity-Based APT Detection via Unsupervised, Context-Augmented Language Models Blip-2: Bootstrapping language-image pre-training with frozen image encoders and large language models, 2023

Reference 27

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Observation c9d0e4ac-d597-4a89-af2a-503ca10b1413 · outbound

This paper cites Failure prediction in ibm bluegene/l event logs.

Beyond Heavy Log Curation: Perplexity-Based APT Detection via Unsupervised, Context-Augmented Language Models Failure prediction in ibm bluegene/l event logs

Reference 28

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Observation e8cf54b9-28aa-4c38-be8c-79990595edc6 · outbound

This paper cites Log clustering based problem identification for online service systems.

Beyond Heavy Log Curation: Perplexity-Based APT Detection via Unsupervised, Context-Augmented Language Models Log clustering based problem identification for online service systems

Reference 29

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Observation 31d12313-c21b-4bc1-8405-568b042c271e · outbound

This paper cites Improved baselines with visual instruction tuning.

Beyond Heavy Log Curation: Perplexity-Based APT Detection via Unsupervised, Context-Augmented Language Models Improved baselines with visual instruction tuning

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Observation 69a8c2e4-37a2-4631-8216-419de571d563 · outbound

This paper cites Mining invariants from console logs for system problem detection.

Beyond Heavy Log Curation: Perplexity-Based APT Detection via Unsupervised, Context-Augmented Language Models Mining invariants from console logs for system problem detection

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Observation 58abfba8-ad89-4df3-a628-fb5e2a380ffa · outbound

This paper cites Trec: Apt tactic / technique recognition via few-shot provenance subgraph learning.

Beyond Heavy Log Curation: Perplexity-Based APT Detection via Unsupervised, Context-Augmented Language Models Trec: Apt tactic / technique recognition via few-shot provenance subgraph learning

Reference 32

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Observation 6bd1ac65-8052-46fd-9522-5febaa711baf · outbound

This paper cites Knowhow: Automatically applying high-level cti knowledge for interpretable and accurate provenance analysis, 2025.

Beyond Heavy Log Curation: Perplexity-Based APT Detection via Unsupervised, Context-Augmented Language Models Knowhow: Automatically applying high-level cti knowledge for interpretable and accurate provenance analysis, 2025

Reference 33

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Observation a1f7c99e-707b-4c78-b224-c61ebd10fb2c · outbound

This paper cites Llama 3.2 1b instruct, 2024.

Beyond Heavy Log Curation: Perplexity-Based APT Detection via Unsupervised, Context-Augmented Language Models Llama 3.2 1b instruct, 2024

Reference 34

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This paper cites Training language models to follow instructions with human feedback.Advances in neural information pro- cessing systems, 35:27730–27744, 2022.

Beyond Heavy Log Curation: Perplexity-Based APT Detection via Unsupervised, Context-Augmented Language Models Training language models to follow instructions with human feedback.Advances in neural information pro- cessing systems, 35:27730–27744, 2022

Reference 35

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Beyond Heavy Log Curation: Perplexity-Based APT Detection via Unsupervised, Context-Augmented Language Models Unresolved cited work

Reference 36

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Observation c7262d0a-77bf-409f-a652-02e2130db5a4 · outbound

This paper cites Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks.

Beyond Heavy Log Curation: Perplexity-Based APT Detection via Unsupervised, Context-Augmented Language Models Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks

Reference 37

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This paper cites DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter.

Beyond Heavy Log Curation: Perplexity-Based APT Detection via Unsupervised, Context-Augmented Language Models DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter

Reference 38

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Observation c4243df2-cfbd-4dcc-99ba-029a89932dbe · outbound

This paper cites GLU Variants Improve Transformer.

Beyond Heavy Log Curation: Perplexity-Based APT Detection via Unsupervised, Context-Augmented Language Models GLU Variants Improve Transformer

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This paper cites Anomaly detection for web log data analysis: A review.Journal of Alge- braic Statistics, 13(1), 2022.

Beyond Heavy Log Curation: Perplexity-Based APT Detection via Unsupervised, Context-Augmented Language Models Anomaly detection for web log data analysis: A review.Journal of Alge- braic Statistics, 13(1), 2022

Reference 40

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This paper cites From alerts to intelligence: A novel llm-aided framework for host-based intrusion detection, 2025.

Beyond Heavy Log Curation: Perplexity-Based APT Detection via Unsupervised, Context-Augmented Language Models From alerts to intelligence: A novel llm-aided framework for host-based intrusion detection, 2025

Reference 41

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Observation 25893412-3aca-465c-be1b-8ebd29950b1e · outbound

This paper cites Gemma 3 technical report, 2025.

Beyond Heavy Log Curation: Perplexity-Based APT Detection via Unsupervised, Context-Augmented Language Models Gemma 3 technical report, 2025

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Observation a2e6e4a3-021f-4935-a51e-cee9c1365942 · outbound

This paper cites Attention is all you need.

Beyond Heavy Log Curation: Perplexity-Based APT Detection via Unsupervised, Context-Augmented Language Models Attention is all you need

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Observation f8e5e4b7-bc8a-444e-a727-334fd7dc073c · outbound

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Beyond Heavy Log Curation: Perplexity-Based APT Detection via Unsupervised, Context-Augmented Language Models Cogvlm: Visual expert for pretrained language models

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Observation 61a2c4ee-3949-4172-801d-a3c38a8599b3 · outbound

This paper cites Logppo: A log-based anomaly detector aided with prox- imal policy optimization algorithms.Smart Cities, 9(1), 2026.

Beyond Heavy Log Curation: Perplexity-Based APT Detection via Unsupervised, Context-Augmented Language Models Logppo: A log-based anomaly detector aided with prox- imal policy optimization algorithms.Smart Cities, 9(1), 2026

Reference 45

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This paper cites Chi, Quoc V.

Beyond Heavy Log Curation: Perplexity-Based APT Detection via Unsupervised, Context-Augmented Language Models Chi, Quoc V

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Observation 06a45f57-4a6b-409a-9019-68bd980edcd6 · outbound

This paper cites Large language models for cyber security: A systematic literature review.ACM Trans.

Beyond Heavy Log Curation: Perplexity-Based APT Detection via Unsupervised, Context-Augmented Language Models Large language models for cyber security: A systematic literature review.ACM Trans

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Beyond Heavy Log Curation: Perplexity-Based APT Detection via Unsupervised, Context-Augmented Language Models Unresolved cited work

Reference 48

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Observation 5e83f255-0451-4182-88af-a2bc5e02c323 · outbound

This paper cites Deep learning-based intrusion detection systems: A survey, 2025.

Beyond Heavy Log Curation: Perplexity-Based APT Detection via Unsupervised, Context-Augmented Language Models Deep learning-based intrusion detection systems: A survey, 2025

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This paper cites A survey on log anomaly detection using deep learning.

Beyond Heavy Log Curation: Perplexity-Based APT Detection via Unsupervised, Context-Augmented Language Models A survey on log anomaly detection using deep learning

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This paper cites Qwen3 technical report, 2025.

Beyond Heavy Log Curation: Perplexity-Based APT Detection via Unsupervised, Context-Augmented Language Models Qwen3 technical report, 2025

Reference 51

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Observation 9c761e66-f3a5-435d-8577-d36659ee8b51 · outbound

This paper cites +/-”. To assess the impact of this artifact, we conducted additional experiments where we removed the “+/-.

Beyond Heavy Log Curation: Perplexity-Based APT Detection via Unsupervised, Context-Augmented Language Models +/-”. To assess the impact of this artifact, we conducted additional experiments where we removed the “+/-

Reference 52

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Observation a759f49e-08c4-4aac-a42d-0c1775bafe79 · outbound

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Beyond Heavy Log Curation: Perplexity-Based APT Detection via Unsupervised, Context-Augmented Language Models Unresolved cited work

Reference 2024

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