| Weaponizing Data Science for Social Engineering: Automated E2E Spearphishing on Twitter J Seymour, PJ Tully Black Hat USA 2016, DEF CON 24, 2016 | 118 | 2016 |
| Synaptic and nonsynaptic plasticity approximating probabilistic inference PJ Tully, MH Hennig, A Lansner Frontiers in synaptic neuroscience 6, 8, 2014 | 58 | 2014 |
| Spike-based Bayesian-Hebbian learning of temporal sequences PJ Tully, H Lindén, MH Hennig, A Lansner PLoS computational biology 12 (5), e1004954, 2016 | 47 | 2016 |
| Generative models for spear phishing posts on social media J Seymour, P Tully arXiv preprint arXiv:1802.05196, 2018 | 37 | 2018 |
| Large-scale simulations of plastic neural networks on neuromorphic hardware JC Knight, PJ Tully, BA Kaplan, A Lansner, SB Furber Frontiers in neuroanatomy 10, 37, 2016 | 24 | 2016 |
| Functional relevance of different basal ganglia pathways investigated in a spiking model with reward dependent plasticity P Berthet, M Lindahl, PJ Tully, J Hellgren-Kotaleski, A Lansner Frontiers in Neural Circuits 10, 53, 2016 | 22 | 2016 |
| Methods for automated social phishing J Foster, M Price, CB Cullison, P Tully, JJ Seymour III US Patent App. 15/944,254, 2019 | 11 | 2019 |
| Repurposing Neural Networks to Generate Synthetic Media for Information Operations P Tully, L Foster Black Hat USA 2020, 2020 | 7 | 2020 |
| Transformers for end-to-end infosec tasks: A feasibility study EM Rudd, MS Rahman, P Tully Proceedings of the 1st Workshop on Robust Malware Analysis, 21-31, 2022 | 5 | 2022 |
| Spike-Based Bayesian-Hebbian Learning in Cortical and Subcortical Microcircuits P Tully KTH Royal Institute of Technology, 2017 | 2 | 2017 |
| Probabilistic computation underlying sequence learning in a spiking attractor memory network P Tully, H Lindén, MH Hennig, A Lansner BMC Neuroscience 14, 1-2, 2013 | 2 | 2013 |
| Systems and methods for automated cybersecurity analysis of extracted binary string sets P Tully, M Haigh, J Gibble, M Sikorski US Patent 11,556,640, 2023 | 1 | 2023 |
| A Picture is Worth a Thousand Words, Literally: Deep Neural Networks for Social Stego P Tully, MT Raggo | | |
Anders Lansnerprofessor of comptuter science, Dept of Mathematics, Stockholm university and KTH在 kth.se 的电子邮件经过验证
