Publications

2026

1. EMSE

   Evaluating and improving the robustness of security attack detectors generated by LLMs

   Samuele Pasini ,  Jinhan Kim ,  Tommaso Aiello , and 3 more authors

   Empirical Software Engineering, 2026

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   @article{pasini2026evaluating,
     title = {Evaluating and improving the robustness of security attack detectors generated by LLMs},
     author = {Pasini, Samuele and Kim, Jinhan and Aiello, Tommaso and Cabrera Lozoya, Roc{\'\i}o and Sabetta, Antonino and Tonella, Paolo},
     journal = {Empirical Software Engineering},
     volume = {31},
     number = {2},
     pages = {35},
     year = {2026},
     publisher = {Springer},
     url = {https://link.springer.com/article/10.1007/s10664-025-10743-w},
     doi = {https://doi.org/10.1007/s10664-025-10743-w},
   }

   Pasini, Samuele, et al. "Evaluating and improving the robustness of security attack detectors generated by LLMs." Empirical Software Engineering 31.2 (2026): 35.

   Pasini, S., Kim, J., Aiello, T., Cabrera Lozoya, R., Sabetta, A., & Tonella, P. (2026). Evaluating and improving the robustness of security attack detectors generated by LLMs. Empirical Software Engineering, 31(2), 35.

2. JSS

   Cross-Site Scripting Adversarial Attacks Based on Deep Reinforcement Learning: Evaluation and Extension Study

   Samuele Pasini ,  Gianluca Maragliano ,  Jinhan Kim , and 1 more author

   Journal of Systems and Software, 2026

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   @article{PASINI2026112856,
     title = {Cross-Site Scripting Adversarial Attacks Based on Deep Reinforcement Learning: Evaluation and Extension Study},
     author = {Pasini, Samuele and Maragliano, Gianluca and Kim, Jinhan and Tonella, Paolo},
     journal = {Journal of Systems and Software},
     pages = {112856},
     year = {2026},
     issn = {0164-1212},
     url = {https://www.sciencedirect.com/science/article/pii/S0164121226000907},
     doi = {https://doi.org/10.1016/j.jss.2026.112856},
   }

   Pasini, Samuele, et al. "Cross-Site Scripting Adversarial Attacks Based on Deep Reinforcement Learning: Evaluation and Extension Study." Journal of Systems and Software (2026): 112856.

   Pasini, S., Maragliano, G., Kim, J., & Tonella, P. (2026). Cross-Site Scripting Adversarial Attacks Based on Deep Reinforcement Learning: Evaluation and Extension Study. Journal of Systems and Software, 112856.

2022

1. MDPI

   Weakly supervised object detection for remote sensing images: A survey

   Corrado Fasana ,  Samuele Pasini ,  Federico Milani , and 1 more author

   MDPI Remote Sensing, 2022

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   @article{fasana2022weakly,
     title = {Weakly supervised object detection for remote sensing images: A survey},
     author = {Fasana, Corrado and Pasini, Samuele and Milani, Federico and Fraternali, Piero},
     journal = {MDPI Remote Sensing},
     volume = {14},
     number = {21},
     pages = {5362},
     year = {2022},
     publisher = {MDPI},
     url = {https://www.mdpi.com/2072-4292/14/21/5362},
     doi = {https://doi.org/10.3390/rs14215362},
   }

   Fasana, Corrado, et al. "Weakly supervised object detection for remote sensing images: A survey." Remote Sensing 14.21 (2022): 5362.

   Fasana, C., Pasini, S., Milani, F., & Fraternali, P. (2022). Weakly supervised object detection for remote sensing images: A survey. Remote Sensing, 14(21), 5362.