{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,15]],"date-time":"2025-11-15T08:09:26Z","timestamp":1763194166818,"version":"3.45.0"},"reference-count":23,"publisher":"IEEE","license":[{"start":{"date-parts":[[2025,6,30]],"date-time":"2025-06-30T00:00:00Z","timestamp":1751241600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,6,30]],"date-time":"2025-06-30T00:00:00Z","timestamp":1751241600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,6,30]]},"DOI":"10.1109\/ijcnn64981.2025.11227820","type":"proceedings-article","created":{"date-parts":[[2025,11,14]],"date-time":"2025-11-14T18:46:15Z","timestamp":1763145975000},"page":"1-7","source":"Crossref","is-referenced-by-count":0,"title":["Topology-Driven Explainable GNNs for Trojan Detection in Deep Learning"],"prefix":"10.1109","author":[{"given":"Riccardo","family":"Ceccaroni","sequence":"first","affiliation":[{"name":"Università \"La Sapienza\",Department of Statistical Sciences,Roma,Italy"}]},{"given":"Pierpaolo","family":"Brutti","sequence":"additional","affiliation":[{"name":"Università \"La Sapienza\",Department of Statistical Sciences,Roma,Italy"}]}],"member":"263","reference":[{"key":"ref1","first-page":"508","article-title":"Auror: defending against poisoning attacks in collaborative deep learning systems","volume-title":"Proc. of ACSAC","author":"Shen"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/ICCAD.2017.8203770"},{"key":"ref3","first-page":"1541","article-title":"Demon in the Variant: Statistical Analysis of DNNs for Robust Backdoor Contamination Detection","volume-title":"Proc. of USENIX Security","author":"Tang"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.3233\/JCS-2012-0460"},{"key":"ref5","article-title":"Programmable Neural Network Trojan for Pre-Trained Feature Extractor","volume":"2019","author":"Ji","year":"2019"},{"key":"ref6","article-title":"Poison as a Cure: Detecting & Neutralizing Variable-Sized Backdoor Attacks in Deep Neural Networks","volume":"2019","author":"Chan","year":"2019"},{"article-title":"Detecting Backdoor Attacks on Deep Neural Networks by Activation Clustering","volume-title":"Proc. of Workshop of AAAI","author":"Chen","key":"ref7"},{"issue":"4","key":"ref8","first-page":"1043","article-title":"Backdoor Attacks on Deep Neural Networks: A Survey","volume":"30","author":"Xiang","year":"2019","journal-title":"IEEE Transactions on Neural Networks and Learning Systems"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.14722\/ndss.2023.23069"},{"key":"ref10","article-title":"NeuronInspect: Detecting Backdoors in Neural Networks via Output Explanations","volume":"2019","author":"Huang","year":"2019"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/TCAD.2021.3111123"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2022.3201586"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/HST.2018.8383920"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1145\/3359789.3359790"},{"key":"ref15","first-page":"3086","article-title":"Poisoning Attacks on Deep Neural Networks: A Survey","volume-title":"Proc. of ICML","author":"Yang"},{"key":"ref16","first-page":"8011","article-title":"Spectral Signatures in Backdoor Attacks","volume-title":"Proc. of NeurIPS","author":"Tran"},{"key":"ref17","first-page":"17258","article-title":"Topological detection of trojaned neural networks","volume":"34","author":"Zheng","year":"2021","journal-title":"extitAdvances in Neural Information Processing Systems"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-64431-3_64"},{"article-title":"GNNExplainer: Generating Explanations for Graph Neural Networks","year":"2019","author":"Ying","key":"ref19"},{"volume-title":"PyTorch Image Models,\u201d GitHub repository","year":"2019","author":"Wightman","key":"ref20"},{"key":"ref21","article-title":"Detecting AI Trojans Using Meta Neural Analysis","volume-title":"CoRR","volume":"abs\/1910.03137","author":"Xu","year":"2019"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.23919\/date51398.2021.9474174"},{"article-title":"Defending Against Backdoor Attack on Graph Neural Network by Explainability","year":"2022","author":"Jiang","key":"ref23"}],"event":{"name":"2025 International Joint Conference on Neural Networks (IJCNN)","start":{"date-parts":[[2025,6,30]]},"location":"Rome, Italy","end":{"date-parts":[[2025,7,5]]}},"container-title":["2025 International Joint Conference on Neural Networks (IJCNN)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/11227166\/11227148\/11227820.pdf?arnumber=11227820","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,11,15]],"date-time":"2025-11-15T08:05:08Z","timestamp":1763193908000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11227820\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,6,30]]},"references-count":23,"URL":"https:\/\/doi.org\/10.1109\/ijcnn64981.2025.11227820","relation":{},"subject":[],"published":{"date-parts":[[2025,6,30]]}}}