Alternatives and similar repositories for Datacon2019-Malicious-Code-DataSet-Stage1

Users that are interested in Datacon2019-Malicious-Code-DataSet-Stage1 are comparing it to the libraries listed below

• kericwy1337 / Datacon2019-Malicious-Code-DataSet-Stage2
  ☆14Updated 6 years ago
• Bowen-n / MCBG
  Source code of Malware Classification by Learning Semantic and Structural Features of Control Flow Graphs (TrustCom 2021)
  ☆22Updated 3 years ago
• PowerLZY / MalConv-Pytorch
  基于深度学习的恶意软件检测研究；MalConv;
  ☆108Updated 3 years ago
• PowerLZY / MalGAN
  主题为”基于GAN的恶意软件对抗样本生成“。首先介绍了恶意软件发展现状，引出基于模式匹配、特征空间和问题空间三种方式去检测恶意软件。然后介绍了如何生成对抗样本攻击恶意软件检测器，详细介绍了基于GAN的恶意软件对抗样本的MalGAN框架，并对实验结果进行了对比。最后总结了结构…
  ☆35Updated 4 years ago
• yhangf / DataCon
  DataCon大数据安全分析大赛，2019年方向二（恶意代码检测）冠军源码、2020年方向五（恶意代码分析）季军源码
  ☆109Updated 4 years ago
• ryderling / MalGraph
  Code for "MalGraph: Hierarchical Graph Neural Networks for Robust Windows Malware Detection"
  ☆47Updated 3 years ago
• bitterzzZZ / Bert-malware-classification
  使用Bert做embedding，结合BiLSTM做恶意软件的多分类任务
  ☆42Updated 4 years ago
• ryderling / adversarial-attacks-and-defenses-for-windows-pe-malware-detection
  A curated resource list of adversarial attacks and defenses for Windows PE malware detection.
  ☆73Updated 3 years ago
• Asichurter / MalFusionFSL
  Few-Shot malware classification using fused features of static analysis and dynamic analysis （基于静态+动态分析的混合特征的小样本恶意代码分类框架）
  ☆34Updated 3 years ago
• diningphil / robust-call-graph-malware-detection
  Official Repository of "Robust Malware Classification via Deep Graph Networks on Call Graph Topologies" (ESANN 2021)
  ☆14Updated 2 years ago
• eastmountyxz / AI-Security-Paper
  This resource mainly counts papers related to APT attacks, including APT traceability, APT knowledge graph construction, APT malicious sa…
  ☆218Updated last year
• friendllcc / Malware-Detection-API-Sequence-Intrinsic-Features
  ☆31Updated 3 years ago
• syssec-utd / provninja
  Evading Provenance-Based ML Detectors with Adversarial System Actions
  ☆33Updated last year
• purseclab / ATLAS
  ATLAS: A Sequence-based Learning Approach for Attack Investigation
  ☆169Updated 3 years ago
• evandowning / deepreflect
  Discovering Malicious Functionality through Binary Reconstruction
  ☆58Updated 4 years ago
• MHunt-er / Benchmarking-Malware-Family-Classification
  ☆16Updated 4 years ago
• omid-s / cyber_deception
  ☆14Updated 4 years ago
• seclab-fudan / APIGraph
  Building relation graph of Android APIs to catch the semantics between APIs, and used to enhancing Android malware detectors
  ☆93Updated 3 years ago
• rickyxume / MalwareViT
  Training Vision Transformers from Scratch for Malware Classification
  ☆29Updated 4 years ago
• weisong-ucr / MAB-malware
  MAB-Malware an open-source reinforcement learning framework to generate AEs for PE malware. We model this problem as a classic multi-arme…
  ☆52Updated 7 months ago
• yuxiaorun / MalConv-Adversarial
  Reproduction of the paper//arxiv.org/pdf/1803.04173.pdf
  ☆18Updated 7 years ago
• deqangss / adv-dnn-ens-malware
  adversarial examples, adversarial malware examples, adversarial malware detection, adversarial deep ensemble, Android malware variants
  ☆57Updated 2 years ago
• sbustreamspot / sbustreamspot-data
  Datasets used in the StreamSpot experiments
  ☆63Updated 9 years ago
• crimson-unicorn / modeler
  ☆24Updated 4 years ago
• CSJianYang / SEevenLLM
  ☆38Updated last year
• darpa-i2o / Transparent-Computing
  Material from the DARPA Transparent Computing Program
  ☆216Updated 5 years ago
• nikeluobinxiaoma / Learning-Based-PE-Malware-Family-Classification-Methods
  ☆11Updated 3 years ago
• Asichurter / APISeqFewShot
  FewShot Malware Classification based on API call sequences, also as code repo for "A Novel Few-Shot Malware Classification Approach for U…
  ☆20Updated 4 years ago
• whyisyoung / CADE
  Code for our USENIX Security 2021 paper -- CADE: Detecting and Explaining Concept Drift Samples for Security Applications
  ☆144Updated 2 years ago
• tfjmp / provenance-papers
  ☆102Updated 4 years ago