{"id":19979307,"url":"https://github.com/edisonleeeee/guard","last_synced_at":"2025-05-04T04:32:56.190Z","repository":{"id":109814398,"uuid":"483819569","full_name":"EdisonLeeeee/GUARD","owner":"EdisonLeeeee","description":"[CIKM 2023] GUARD: Graph Universal Adversarial Defense","archived":false,"fork":false,"pushed_at":"2024-02-27T06:36:42.000Z","size":7444,"stargazers_count":7,"open_issues_count":1,"forks_count":2,"subscribers_count":3,"default_branch":"master","last_synced_at":"2024-02-27T07:59:37.215Z","etag":null,"topics":["adversarial-defense","dgl","graph-adversarial-learning","graph-neural-networks"],"latest_commit_sha":null,"homepage":"","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/EdisonLeeeee.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null}},"created_at":"2022-04-20T21:32:26.000Z","updated_at":"2024-02-27T06:23:08.000Z","dependencies_parsed_at":"2023-05-01T13:32:41.734Z","dependency_job_id":null,"html_url":"https://github.com/EdisonLeeeee/GUARD","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/EdisonLeeeee%2FGUARD","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/EdisonLeeeee%2FGUARD/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/EdisonLeeeee%2FGUARD/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/EdisonLeeeee%2FGUARD/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/EdisonLeeeee","download_url":"https://codeload.github.com/EdisonLeeeee/GUARD/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":224385195,"owners_count":17302442,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["adversarial-defense","dgl","graph-adversarial-learning","graph-neural-networks"],"created_at":"2024-11-13T03:37:28.366Z","updated_at":"2024-11-13T03:37:29.052Z","avatar_url":"https://github.com/EdisonLeeeee.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# GUARD: Graph Universal Adversarial Defense\nPyTorch implementation of the CIKM 2023 paper: \"GUARD: Graph Universal Adversarial Defense\" [[arXiv]](https://arxiv.org/abs/2204.09803).\n\n\n\u003cp align=\"center\"\u003e \u003cimg src=\"./figs/demo.png\" /\u003e \u003cp align=\"center\"\u003e\u003cem\u003eFig. 1. An illustrative example of graph universal defense. The universal patch p can be applied to an arbitrary node (here v1) to protect it from adversarial targeted attacks by removing adversarial edges (if exist).\u003c/em\u003e\u003c/p\u003e\n\n# Requirements\n+ torch==1.9\n+ dgl==0.7.0\n\n# Datasets\n+ Cora (available in `data/`)\n+ Pubmed (available in `data/`)\n+ ogbn-arxiv from OGB\n+ Reddit from http://snap.stanford.edu/graphsage/\n\n\nInstall graphattack:\n```bash\ncd GraphAttack\npip install -e .\n```\n\n# Quick Start\nSee `demo.ipynb`\n\n# Reproduce results in the paper\nrun\n```python\n\npython evaluate_guard.py\n```\n\n# Cite\nif you find this repo helpful, please cite our work:\n```bixtex\n@inproceedings{li2022guard,\n  author       = {Jintang Li and\n                  Jie Liao and\n                  Ruofan Wu and\n                  Liang Chen and\n                  Zibin Zheng and\n                  Jiawang Dan and\n                  Changhua Meng and\n                  Weiqiang Wang},\n  title        = {{GUARD:} Graph Universal Adversarial Defense},\n  booktitle    = {{CIKM}},\n  pages        = {1198--1207},\n  publisher    = {{ACM}},\n  year         = {2023}\n}\n```\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fedisonleeeee%2Fguard","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fedisonleeeee%2Fguard","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fedisonleeeee%2Fguard/lists"}