Papers
This page contains a list of papers that I have found interested or referenced. The papers are categorised by topic and author.
Note, also check out Paper Stack from dreadnode.io.
| Name | Category | Author |
|---|---|---|
| EMBER: An Open Dataset for Training Static PE Malware Machine Learning Models | Machine Learning Malware Detection Dataset | Hyrum S. Anderson Phil Roth |
| Application of Artificial Intelligence in the Study of Fishing Vessel Behavior | Artificial Intelligence Fishing Vessel Behavior | Xin Cheng Fan Zhang Xinjun Chen Jintao Wang |
| Adversarial Attacks against Windows PE Malware Detection: A Survey of the State-of-the-Art | Adversarial Attacks Malware Detection Survey | Xiang Ling Lingfei Wu Jiangyu Zhang Zhenqing Qu Wei Deng Xiang Chen Yaguan Qian Chunming Wu Shouling Ji Tianyue Luo Jingzheng Wu Yanjun Wu |
| Machine learning and deep learning | Machine Learning Deep Learning Fundamentals | Christian Janiesch Patrick Zschech Kai Heinrich |
| CRISP-DM Twenty Years Later: From Data Mining Processes to Data Science Trajectories | Data Mining Data Science Processes | Fernando Martínez-Plumed Lidia Contreras-Ochando Cèsar Ferri José Hernández-Orallo Meelis Kull Nicolas Lachich |
| DMME: Data mining methodology for engineering applications – a holistic extension to the CRISP-DM model | Data Mining Engineering Applications CRISP-DM | Steffen Huber Hajo Wiemer Dorothea Schneider Steffen Ihlenfeldt |
| A heuristic approach for detection of obfuscated malware | Heuristic Approach Obfuscated Malware Detection | S. Treadwell M. Zhou |
| A survey on heuristic malware detection techniques | Heuristic Malware Detection Survey | Z. Bazrafshan H. Hashemi S.M. Hazrati Fard A. Hamzeh |
| Identifying useful features for malware detection in the Ember dataset | Malware Detection Ember Dataset | Y. Oyama T. Miyashita H. Kokubo |
| A comprehensive review on malware detection approaches | Malware Detection Review | Ö. Aslan R. Samet |
| Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks | NLP Knowledge-Intensive Tasks Retrieval-Augmented Generation | Lewis, P. Perez, E. Piktus, A. Petroni, F. Karpukhin, V. Goyal, N. Küttler, H. Lewis, M. Yih, W. Rocktäschel, T. Riedel, S. Kiela, D. |
| Improving language understanding by generative pre-training | Language Understanding Generative Pre-training | Radford, A. Narasimhan, K. Salimans, T. Sutskever, I. |
| An application of multi-agent simulation to traffic behavior for evacuation in earthquake disaster | Multi-agent Simulation Traffic Behavior Evacuation Planning Disaster Management | Seiichi Kagaya Ken'etsu Uchida Toru Hagiwara |
| ReAct: Synergizing Reasoning and Acting in Language Models | Language Models Reasoning NLP AI Agents | Shunyu Yao Jeffrey Zhao Dian Yu Nan Du Izhak Shafran Karthik Narasimhan Yuan Cao |
| Open-source DeepResearch – Freeing our search agents | Open Source Search Agents NLP AI Agents | Aymeric Roucher Albert Villanova del Moral Merve Noyan Thomas Wolf Clémentine Fourrier |
| On the Biology of a Large Language Model | Language Models Model Interpretability Circuit Analysis | Jack Lindsey Wes Gurnee Emmanuel Ameisen Brian Chen Adam Pearce Nicholas L. Turner Craig Citro Chris Olah Joshua Batson |
| EMBER2024 - A Benchmark Dataset for Holistic Evaluation of Malware Classifiers | Machine Learning Malware Detection Dataset Benchmark | R.J. Joyce G. Miller P. Roth R. Zak E. Zaresky-Williams H. Anderson E. Raff J. Holt |
| Learning to Evade Static PE Machine Learning Malware Models via Reinforcement Learning | Adversarial Attacks Malware Detection Reinforcement Learning | H.S. Anderson A. Kharkar B. Filar D. Evans P. Roth |
| Adversarial Examples for CNN-Based Malware Detectors | Adversarial Examples Malware Detection CNN | B. Chen S. Su H. Wang S. He Y. Tang |
| A review of black-box adversarial attacks and defenses in machine learning-based malware detection | Survey Adversarial Attacks Malware Detection | J. Chen |
| HopSkipJumpAttack: A Query-Efficient Decision-Based Attack | Adversarial Attacks Black-Box Decision-Based | J. Chen M.I. Jordan M.J. Wainwright |
| Functionality-preserving Black-box Optimization of Adversarial Windows Malware | Adversarial Attacks Black-Box Malware Detection | L. Demetrio B. Biggio G. Lagorio F. Roli A. Armando |
| Towards a Practical Defense Against Adversarial Attacks on Deep Learning-Based Malware Detectors via Randomized Smoothing | Adversarial Defense Randomized Smoothing Malware Detection | D. Gibert G. Zizzo Q. Le |
| Black-Box Attacks against RNN based Malware Detection Algorithms | Adversarial Attacks RNN Malware Detection | W. Hu Y. Tan |
| Evaluating Realistic Adversarial Attacks against Machine Learning Models for Windows PE Malware Detection | Adversarial Attacks Malware Detection Evaluation | M. Imran A. Appice D. Malerba |
| Adversarial training for raw-binary malware classifiers | Adversarial Training Malware Detection Binary Classification | L. Keane M. Kantchelian I. Stoian T. Cassidy A. Javed M. Lash E. Raff C. Nicholas H. Anderson R. Zak |
| Adversarial Malware Binaries: Evading Deep Learning for Malware Detection in Executables | Adversarial Attacks Malware Detection Deep Learning | B. Kolosnjaji A. Demontis B. Biggio D. Maiorca G. Giacinto F. Roli C. Eckert |
| Deceiving Portable Executable Malware Classifiers into Targeted Misclassification with Practical Adversarial Examples | Adversarial Examples Malware Detection Targeted Attack | Y. Kucuk G. Yan |
| GAMBD: Generating adversarial malware against MalConv | Adversarial Attacks MalConv Malware Detection | K. Li M. Li Z. Liang Z. Qin |
| Adversarial attacks against Windows PE malware detection: A survey of the state-of-the-art | Survey Adversarial Attacks Malware Detection | X. Ling X. Chen Y. Qian C. Wu S. Ji |
| The Limitations of Deep Learning in Adversarial Settings | Adversarial Machine Learning Deep Learning Security | N. Papernot P. McDaniel S. Jha M. Fredrikson Z.B. Celik A. Swami |
| Practical Black-Box Attacks against Machine Learning | Black-Box Attacks Adversarial Attacks Machine Learning | N. Papernot P. McDaniel I. Goodfellow S. Jha Z.B. Celik A. Swami |
| Malware Detection by Eating a Whole EXE | Malware Detection Deep Learning PE Files | E. Raff J. Barker J. Sylvester R. Brandon B. Catanzaro C. Nicholas |
| Generic Black-Box End-to-End Attack Against State of the Art API Call Based Malware Classifiers | Black-Box Attacks API Calls Malware Detection | I. Rosenberg A. Shabtai L. Rokach Y. Elovici |
| Query-Efficient Black-Box Attack Against Sequence-Based Malware Classifiers | Black-Box Attacks Query Efficiency Malware Detection | I. Rosenberg A. Shabtai L. Rokach Y. Elovici |
| Exploring Adversarial Examples in Malware Detection | Adversarial Examples Malware Detection Evaluation | O. Suciu S.E. Coull J. Johns |
| Adversary Resistant Deep Neural Networks with an Application to Malware Detection | Adversarial Defense Deep Neural Networks Malware Detection | Q. Wang W. Guo K. Zhang A. Gunter G. Danezis Z. Chen |
| A Survey of Adversarial Attack and Defense Methods for Malware Classification in Cyber Security | Survey Adversarial Attacks Malware Detection | S. Yan Z. Gu J. Liu T. Li Z. Li Z. Wu |
| Attribute-Aware Generative Design With Generative Adversarial Networks | Generative Adversarial Networks Attribute-Aware Design Machine Learning | C. Yuan M. Moghaddam |
| Concurrency and Computation: Practice and Experience | Journal Distributed Computing Parallel Computing Cloud Computing | Wiley |
| Future Internet | Journal Internet Technologies Information Society Open Access | MDPI |
| Efficient Malware Analysis Using Metric Embeddings | Malware Analysis Metric Learning Embeddings | Ethan M. Rudd et al. |
| EMBERSim: A Large-Scale Databank for Boosting Similarity Search in Malware Analysis | Malware Analysis Similarity Search Dataset | Dragos G. Corlatescu Alexandru Dinu Mihaela Gaman Paul Sumedrea |
| BEACON: Behavioral Malware Classification with Large Language Model Embeddings | Malware Classification LLM Embeddings Behavioral Analysis | arXiv preprint |
| GEMAL: Embedding Vector Generation Based on Function Call Graph | Malware Classification Embeddings Function Call Graph | Springer |
| Malware Detection through Contextualized Vector Embeddings | Malware Detection Vector Embeddings NLP | IEEE |
| Similarity-Based Malware Classification Using Graph Neural Networks | Malware Classification Graph Neural Networks Similarity | MDPI |
| Automatic Malware Description via Attribute Tagging and Similarity Embedding (SMART) | Malware Classification Similarity Embedding Attribute Tagging | arXiv preprint |
| Advancements in File Similarity Techniques: Traditional and Modern Approaches for Malware Detection | Malware Detection File Similarity Survey | Udbhav Prasad |
| Using LLM Embeddings with Similarity Search for Botnet TLS Certificate Detection | LLM Embeddings Similarity Search TLS Certificates | Rapid7 Research |
| Plan-and-Solve Prompting: Improving Zero-Shot Chain-of-Thought Reasoning by Large Language Models | LLM Agents Prompting | Lei Wang et al. |
| Reflexion: Language Agents with Verbal Reinforcement Learning | LLM Agents Self-Reflection | Noah Shinn et al. |
| ReAct: Synergizing Reasoning and Acting in Language Models | LLM Agents Reasoning | Shunyu Yao et al. |
| Toolformer: Language Models Can Teach Themselves to Use Tools | LLM Agents Tool Use | Timo Schick et al. |
| Do the Right Thing: Studies in Limited Rationality | Bounded Rationality Decision Making | Stuart Russell Eric Wefald |
| HuggingGPT: Solving AI Tasks with ChatGPT and its Friends in Hugging Face | LLM Agents Task Planning | Yongliang Shen et al. |