On the public citation graph

Adversarial Data Mining

0 signed · 24 inferred · view as graph

Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.

Is this your work? Sign in with ORCID and put your name on the claims that are yours.

Claim with ORCID

Reference health. See whether every reference in this work resolves to a known work and none has been retracted — and get a dated CiteStamped badge you can embed.

See reference health

What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/s10618-010-0197-3openalex-snapshot

Classifier evaluation and attribute selection against active adversaries

inferredcites →https://doi.org/10.1007/s10844-010-0148-xopenalex-snapshot

“Andromaly”: a behavioral malware detection framework for android devices

inferredcites →https://doi.org/10.1017/cbo9780511546921openalex-snapshot

Prediction, Learning, and Games

inferredcites →https://doi.org/10.1109/acsac.2007.21openalex-snapshot

Limits of Static Analysis for Malware Detection

inferredcites →https://doi.org/10.1109/icdm.2012.58openalex-snapshot

Sparse Bayesian Adversarial Learning Using Relevance Vector Machine Ensembles

inferredcites →https://doi.org/10.1109/sp.2010.25openalex-snapshot

Outside the Closed World: On Using Machine Learning for Network Intrusion Detection

inferredcites →https://doi.org/10.1145/1014052.1014066openalex-snapshot

Adversarial classification

inferredcites →https://doi.org/10.1145/2339530.2339697openalex-snapshot

Adversarial support vector machine learning

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.2139/ssrn.4629044openalex-extracted

Big Data Technologies for Cyber Security in the Digital Era

inferred← citeshttps://doi.org/10.1007/978-3-031-43792-2_5openalex-snapshot

Attacks Against Machine Learning Systems: Analysis and GAN-based Approach to Protection

inferred← citeshttps://doi.org/10.1007/978-3-319-77492-3_13openalex-snapshot

Biologically Inspired Artificial Intelligence Techniques

inferred← citeshttps://doi.org/10.1007/978-981-99-9704-6_32openalex-snapshot

Artificial Cognitive Intelligence and Information Technology in Cybersecurity

inferred← citeshttps://doi.org/10.1007/s10462-024-10938-5openalex-snapshot

Big data applications: overview, challenges and future

inferred← citeshttps://doi.org/10.1016/j.cose.2021.102287openalex-snapshot

Challenges and pitfalls in malware research

inferred← citeshttps://doi.org/10.1109/bigdata62323.2024.10825681openalex-snapshot

Leveraging Large Language Models for Dynamic Scenario Building targeting Enhanced Cyber-threat Detection and Security Training

inferred← citeshttps://doi.org/10.1109/ecai.2017.8166441openalex-snapshot

Neural network models in big data analytics and cyber security

inferred← citeshttps://doi.org/10.1109/fit.2018.00030openalex-snapshot

A Supervised Machine Learning Based Approach for Automatically Extracting High-Level Threat Intelligence from Unstructured Sources

inferred← citeshttps://doi.org/10.1109/tdsc.2022.3210029openalex-snapshot

Mitigating Adversarial Gray-Box Attacks Against Phishing Detectors

inferred← citeshttps://doi.org/10.1134/s1054661824700408openalex-snapshot

Approach to Detecting Attacks against Machine Learning Systems with a Generative Adversarial Network

inferred← citeshttps://doi.org/10.1145/3600094openalex-snapshot

Taxonomy and Recent Advance of Game Theoretical Approaches in Adversarial Machine Learning: A Survey

inferred← citeshttps://doi.org/10.2139/ssrn.6434687openalex-snapshot

SCAFFOLD: A Practical Framework for Cybersecurity Strategy in Adversarial Information Security Interactions

inferred← citeshttps://doi.org/10.23919/cisti54924.2022.9820579openalex-snapshot

Information Gain applied to reduce model-building time in decision-tree-based intrusion detection system

inferred← citeshttps://doi.org/10.2495/tdi-v4-n1-29-41openalex-snapshot

How Port Security has to evolve to address the Cyber-Physical Security Threat: lessons from the SAURON project

inferred← citeshttps://doi.org/10.3389/fdata.2019.00001openalex-snapshot

Research Challenges at the Intersection of Big Data, Security and Privacy

Editorial review for independent work. ICSAC — the Institute for Complexity Science and Advanced Computing — runs a structured editorial panel for researchers publishing outside journals, and publishes on CiteStamp rails. Submission is free and goes through ORCID: icsacinstitute.org/submit.