By Mr Bao Doan

Preprints

Doan BG; Yang S; Montague P; De Vel O; Abraham T; Camtepe S; Kanhere SS; Abbasnejad E; Ranasinghe DC, 2026, Feature-Space Bayesian Adversarial Learning Improved Malware Detector Robustness, http://dx.doi.org/10.48550/arxiv.2301.12680

Bodhankar A; Joshi A; Doan BG; Marchant T; Leslie O; Salim F, 2026, Didact: A Cross-Domain Capability Discovery System for Defence, http://dx.doi.org/10.48550/arxiv.2606.06942

Doan BG; Joshi A; Elinas P; Bodhankar A; Leslie O; Marchant T; Salim F, 2026, A Benchmark Construction and Evaluation Framework for Specialist Domains: Case Study on Defense-related Documents, http://dx.doi.org/10.48550/arxiv.2604.17943

Doan BG; Shamsi A; Guo X-Y; Mohammadi A; Alinejad-Rokny H; Sejdinovic D; Teney D; Ranasinghe DC; Abbasnejad E, 2025, Bayesian Low-Rank LeArning (Bella): A Practical Approach to Bayesian Neural Networks, http://dx.doi.org/10.48550/arxiv.2407.20891

Doan BG; Nguyen DQ; Lindquist C; Montague P; Abraham T; De Vel O; Camtepe S; Kanhere SS; Abbasnejad E; Ranasinghe DC, 2024, On the Credibility of Backdoor Attacks Against Object Detectors in the Physical World, http://dx.doi.org/10.48550/arxiv.2408.12122

Doan BG; Nguyen DQ; Montague P; Abraham T; De Vel O; Camtepe S; Kanhere SS; Abbasnejad E; Ranasinghe DC, 2024, Bayesian Learned Models Can Detect Adversarial Malware For Free, http://dx.doi.org/10.48550/arxiv.2403.18309

Doan BG; Abbasnejad E; Shi JQ; Ranasinghe DC, 2023, Bayesian Learning with Information Gain Provably Bounds Risk for a Robust Adversarial Defense, http://dx.doi.org/10.48550/arxiv.2212.02003

Doan BG; Xue M; Ma S; Abbasnejad E; Ranasinghe DC, 2022, TnT Attacks! Universal Naturalistic Adversarial Patches Against Deep Neural Network Systems, http://dx.doi.org/10.48550/arxiv.2111.09999

Yang S; Doan BG; Montague P; De Vel O; Abraham T; Camtepe S; Ranasinghe DC; Kanhere SS, 2022, Transferable Graph Backdoor Attack, http://dx.doi.org/10.48550/arxiv.2207.00425

Doan BH; Reeves JJ; Sherris M, 2021, Portfolio Management for Insurers and Pension Funds and COVID-19: Targeting Volatility for Equity, Balanced and Target-Date Funds with Leverage Constraints, http://dx.doi.org/10.2139/ssrn.3773495

Doan BG; Abbasnejad E; Ranasinghe DC, 2020, Februus: Input Purification Defense Against Trojan Attacks on Deep Neural Network Systems, http://dx.doi.org/10.48550/arxiv.1908.03369

Gao Y; Doan BG; Zhang Z; Ma S; Zhang J; Fu A; Nepal S; Kim H, 2020, Backdoor Attacks and Countermeasures on Deep Learning: A Comprehensive Review, http://dx.doi.org/10.48550/arxiv.2007.10760

Gao Y; Kim Y; Doan BG; Zhang Z; Zhang G; Nepal S; Ranasinghe DC; Kim H, 2019, Design and Evaluation of a Multi-Domain Trojan Detection Method on Deep Neural Networks, http://dx.doi.org/10.48550/arxiv.1911.10312

Doan BH; Lee JB; Liu Q; Reeves JJ, 2019, Beta Measurement and Forecasting with High Frequency Returns, http://dx.doi.org/10.2139/ssrn.3444103

Doan BH; Foster FD; Yang L, 2018, A Portfolio-Based Measure of Economic Uncertainty, http://dx.doi.org/10.2139/ssrn.3307999

Doan BH; Reeves JJ, 2017, Targeting Market Neutrality and Volatility, http://dx.doi.org/10.2139/ssrn.3021477

Doan BH; Jayasuriya D; Lee JB; Reeves JJ, Event Studies in Finance with Dynamic Betas, http://dx.doi.org/10.2139/ssrn.6240838

Doan BH; Jayasuriya D; Lee JB; Lo WC; Reeves JJ, Neutralizing Market Risk with Backward and Forward Looking Betas, http://dx.doi.org/10.2139/ssrn.5736646

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