Computer Security

Benchmarks archive 2025-07-28

1 leaderboard table shown for this task, 1 with rows (a “benchmark” on this site is a table with at least one row, as on /sota), ordered by row count. “Best model” is the first row in the archive's own order at snapshot; nothing is re-ranked here and metric direction is not recorded in the archive. PwC's Trend sparklines are not in the archive, so that column is omitted.

Syntology column: samples harvested from the paper's repositories and executed on synthesized fixtures; “ran” is not a correctness claim and does not order the table. A dash means no Syntology record for that paper, not a recorded non-run. Read from the graph 2026-09-24.

Libraries

Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.

Datasets archive 2025-07-28

2 datasets whose archive record lists this task, ordered by the archive's paper count.

Subtasks archive 2025-07-28

1 subtask in the archive's task tree.

Most implemented papers archive 2025-07-28

18 shown of 18 papers with code (66 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• Novel Feature Extraction, Selection and Fusion for Effective Malware Family Classification
  13 Nov 2015 19 repositories listed
  This paradigm is presented and discussed in the present paper, where emphasis has been given to the phases related to the extraction, and selection of a set of novel features for the effective representation of malware…
• Defending Against Neural Fake News
  29 May 2019 4 repositories listed Syntology ran 1 of 10 samples · 9 unverified · 10 pointer-only (licence)
  We find that best current discriminators can classify neural fake news from real, human-written, news with 73% accuracy, assuming access to a moderate level of training data.
• Scaling Language Models: Methods, Analysis & Insights from Training Gopher
  8 Dec 2021 3 repositories listed
  Language modelling provides a step towards intelligent communication systems by harnessing large repositories of written human knowledge to better predict and understand the world.
• Not what you've signed up for: Compromising Real-World LLM-Integrated Applications with Indirect Prompt Injection
  23 Feb 2023 2 repositories listed Syntology ran 0 of 2 samples · 2 unverified
  Large Language Models (LLMs) are increasingly being integrated into various applications.
• Evaluating Explanation Methods for Deep Learning in Security
  5 Jun 2019 2 repositories listed
  Deep learning is increasingly used as a building block of security systems.
• Effectiveness of Tree-based Ensembles for Anomaly Discovery: Insights, Batch and Streaming Active Learning
  23 Jan 2019 2 repositories listed Syntology ran 0 of 21 samples · 21 unverified
  Our results show that active learning allows us to discover significantly more anomalies than state-of-the-art unsupervised baselines, our batch active learning algorithm discovers diverse anomalies, and our algorithms…
• Active Anomaly Detection via Ensembles
  17 Sep 2018 2 repositories listed
  First, we present an important insight into how anomaly detector ensembles are naturally suited for active learning.
• Reservoir of Diverse Adaptive Learners and Stacking Fast Hoeffding Drift Detection Methods for Evolving Data Streams
  7 Sep 2017 2 repositories listed
  In addition, a number of methods have been developed to detect concept drifts in these streams.
• Emergent Misalignment: Narrow finetuning can produce broadly misaligned LLMs
  24 Feb 2025 1 repository listed Syntology ran 0 of 7 samples · 7 unverified
  In our experiment, a model is finetuned to output insecure code without disclosing this to the user.
• CySecBench: Generative AI-based CyberSecurity-focused Prompt Dataset for Benchmarking Large Language Models
  2 Jan 2025 1 repository listed
  Typically, these methods are evaluated using datasets of malicious prompts designed to bypass security policies established by LLM providers.
• SecQA: A Concise Question-Answering Dataset for Evaluating Large Language Models in Computer Security
  26 Dec 2023 1 repository listed Syntology ran 6 of 7 samples · 1 unverified
  In this paper, we introduce SecQA, a novel dataset tailored for evaluating the performance of Large Language Models (LLMs) in the domain of computer security.
• Understand Waiting Time in Transaction Fee Mechanism: An Interdisciplinary Perspective
  4 May 2023 1 repository listed
  Our study identified NFT drops as a unique source of market congestion -- holiday effects -- beyond trend and season effects.
• SoK: Explainable Machine Learning for Computer Security Applications
  22 Aug 2022 1 repository listed
  The security literature sometimes also fails to disentangle the role of the various stakeholders, e.
• CVSS-BERT: Explainable Natural Language Processing to Determine the Severity of a Computer Security Vulnerability from its Description
  16 Nov 2021 1 repository listed
  The severity score computed from the predicted CVSS vector is also very close to the real severity score attributed by a human expert.
• Fragments Expert A Graphical User Interface MATLAB Toolbox for Classification of File Fragments
  23 Dec 2020 1 repository listed
  The classification of file fragments of various file formats is an essential task in various applications such as firewalls, intrusion detection systems, anti-viruses, web content filtering, and digital forensics.
• CodeCMR: Cross-Modal Retrieval For Function-Level Binary Source Code Matching
  1 Dec 2020 1 repository listed
  We adopt Deep Pyramid Convolutional Neural Network (DPCNN) for source code feature extraction and Graph Neural Network (GNN) for binary code feature extraction.
• Robust Neural Malware Detection Models for Emulation Sequence Learning
  28 Jun 2018 1 repository listed
  These models target the core of the malicious operation by learning the presence and pattern of co-occurrence of malicious event actions from within these sequences.
• Neural Network-based Graph Embedding for Cross-Platform Binary Code Similarity Detection
  22 Aug 2017 1 repository listed
  The problem of cross-platform binary code similarity detection aims at detecting whether two binary functions coming from different platforms are similar or not.

Syntology lines on 5 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.