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Fabio Di Troia
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2020 – today
- 2024
- [j19]Olha Jurecková, Martin Jurecek
, Mark Stamp, Fabio Di Troia, Róbert Lórencz:
Classification and online clustering of zero-day malware. J. Comput. Virol. Hacking Tech. 20(4): 579-592 (2024) - [j18]Matous Kozák
Creating valid adversarial examples of malware. J. Comput. Virol. Hacking Tech. 20(4): 607-621 (2024) - [j17]Pavla Louthánová, Matous Kozák
A comparison of adversarial malware generators. J. Comput. Virol. Hacking Tech. 20(4): 623-639 (2024) - [c26]Quang Duy Tran, Jaehyun Lim, Fabio Di Troia:
An Advanced Malware Detection System Based on NLP to Generate Genetic Markers. ICCE 2024: 1-6 - 2023
- [j16]Aparna Sunil Kale, Vinay Pandya, Fabio Di Troia, Mark Stamp
Malware classification with Word2Vec, HMM2Vec, BERT, and ELMo. J. Comput. Virol. Hacking Tech. 19(1): 1-16 (2023) - [j15]Huy Nguyen, Fabio Di Troia, Genya Ishigaki
Generative adversarial networks and image-based malware classification. J. Comput. Virol. Hacking Tech. 19(4): 579-595 (2023) - [c25]Jaehyun Lim, Quang Duy Tran, Fabio Di Troia:
Enhancing Malware Detection Using "Genetic Markers" and Machine Learning. DASC/PiCom/CBDCom/CyberSciTech 2023: 975-977 - [c24]Vinay Pandya, Fabio Di Troia:
Malware Detection through Contextualized Vector Embeddings. SVCC 2023: 1-7 - [i17]Matous Kozák, Martin Jurecek, Mark Stamp, Fabio Di Troia:
Creating Valid Adversarial Examples of Malware. CoRR abs/2306.13587 (2023) - [i16]Aditya Raghavan, Fabio Di Troia, Mark Stamp:
Hidden Markov Models with Random Restarts vs Boosting for Malware Detection. CoRR abs/2307.10256 (2023) - [i15]Yuvaray Athur Raghuvir, Senthil Govindarajan, Sanjeevi Vijayakumar, Pradeep Yadlapalli, Fabio Di Troia:
Advancement on Security Applications of Private Intersection Sum Protocol. CoRR abs/2308.14741 (2023) - [i14]Anish Singh Shekhawat, Fabio Di Troia, Mark Stamp:
Feature Analysis of Encrypted Malicious Traffic. CoRR abs/2312.04596 (2023) - 2022
- [c23]Muhammad Ali, Monem Hamid, Jacob Jasser, Joachim Lerman, Samod Shetty, Fabio Di Troia:
Profile Hidden Markov Model Malware Detection and API Call Obfuscation. ICISSP 2022: 688-695 - [c22]Hoseong Asher Lee, Nikhil Prathapani, Rajesh Paturi, Sarp Parmaksiz, Fabio Di Troia:
NLP-based User Authentication through Mouse Dynamics. ICISSP 2022: 696-702 - [c21]Katrina Tran, Fabio Di Troia, Mark Stamp
Robustness of Image-Based Malware Analysis. SVCC 2022: 3-21 - [c20]Quang Duy Tran, Fabio Di Troia
Word Embeddings for Fake Malware Generation. SVCC 2022: 22-37 - [c19]Sanmesh Bhosale, Fabio Di Troia
Twitter Bots' Detection with Benford's Law and Machine Learning. SVCC 2022: 38-54 - [c18]Thomas H. Austin
A Blockchain-Based Tamper-Resistant Logging Framework. SVCC 2022: 90-104 - [e1]Sang-Yoon Chang
Silicon Valley Cybersecurity Conference - Second Conference, SVCC 2021, San Jose, CA, USA, December 2-3, 2021, Revised Selected Papers. Communications in Computer and Information Science 1536, Springer 2022, ISBN 978-3-030-96056-8 [contents] - [i13]Anusha Damodaran, Fabio Di Troia, Corrado Aaron Visaggio, Thomas H. Austin, Mark Stamp:
A Comparison of Static, Dynamic, and Hybrid Analysis for Malware Detection. CoRR abs/2203.09938 (2022) - [i12]Tazmina Sharmin, Fabio Di Troia, Katerina Potika, Mark Stamp:
Convolutional Neural Networks for Image Spam Detection. CoRR abs/2204.01710 (2022) - [i11]Andrew Miller, Fabio Di Troia, Mark Stamp:
Hidden Markov Models with Momentum. CoRR abs/2206.04057 (2022) - [i10]Huy Nguyen, Fabio Di Troia, Genya Ishigaki, Mark Stamp:
Generative Adversarial Networks and Image-Based Malware Classification. CoRR abs/2207.00421 (2022) - [i9]Samanvitha Basole, Fabio Di Troia, Mark Stamp:
Multifamily Malware Models. CoRR abs/2207.00620 (2022) - 2021
- [c17]Aparna Sunil Kale, Fabio Di Troia, Mark Stamp:
Malware Classification with Word Embedding Features. ICISSP 2021: 733-742 - [c16]Dennis Dang, Fabio Di Troia, Mark Stamp:
Malware Classification using Long Short-term Memory Models. ICISSP 2021: 743-752 - [c15]Elliu Huang, Fabio Di Troia, Mark Stamp, Preethi Sundaravaradhan:
A New Dataset for Smartphone Gesture-based Authentication. ICISSP 2021: 771-780 - [c14]Harshit Trehan, Fabio Di Troia
Fake Malware Generation Using HMM and GAN. SVCC 2021: 3-21 - [i8]Aparna Sunil Kale, Fabio Di Troia, Mark Stamp:
Malware Classification with Word Embedding Features. CoRR abs/2103.02711 (2021) - [i7]Dennis Dang, Fabio Di Troia, Mark Stamp:
Malware Classification Using Long Short-Term Memory Models. CoRR abs/2103.02746 (2021) - [i6]Zidong Jiang, Fabio Di Troia, Mark Stamp:
Sentiment Analysis for Troll Detection on Weibo. CoRR abs/2103.09054 (2021) - [i5]Ruchira Gothankar, Fabio Di Troia, Mark Stamp:
Clickbait Detection in YouTube Videos. CoRR abs/2107.12791 (2021) - [i4]Elliu Huang, Fabio Di Troia, Mark Stamp:
Evaluating Deep Learning Models and Adversarial Attacks on Accelerometer-Based Gesture Authentication. CoRR abs/2110.14597 (2021) - 2020
- [b1]Fabio Di Troia:
Machine learning classification for advanced malware detection. Kingston University, Kingston upon Thames, UK, 2020 - [j14]Guruswamy Nellaivadivelu, Fabio Di Troia, Mark Stamp
Black box analysis of android malware detectors. Array 6: 100022 (2020) - [j13]Mayuri Wadkar
Detecting malware evolution using support vector machines. Expert Syst. Appl. 143 (2020) - [j12]Tazmina Sharmin, Fabio Di Troia, Katerina Potika
Convolutional neural networks for image spam detection. Inf. Secur. J. A Glob. Perspect. 29(3): 103-117 (2020) - [j11]Samanvitha Basole, Fabio Di Troia, Mark Stamp
Multifamily malware models. J. Comput. Virol. Hacking Tech. 16(1): 79-92 (2020)
2010 – 2019
- 2019
- [j10]Anish Singh Shekhawat, Fabio Di Troia, Mark Stamp
Feature analysis of encrypted malicious traffic. Expert Syst. Appl. 125: 130-141 (2019) - [j9]Aditya Raghavan, Fabio Di Troia, Mark Stamp
Hidden Markov models with random restarts versus boosting for malware detection. J. Comput. Virol. Hacking Tech. 15(2): 97-107 (2019) - [j8]Supraja Suresh, Fabio Di Troia, Katerina Potika
An analysis of Android adware. J. Comput. Virol. Hacking Tech. 15(3): 147-160 (2019) - [c13]Neeraj Chavan, Fabio Di Troia, Mark Stamp
A Comparative Analysis of Android Malware. ICISSP 2019: 664-673 - [c12]Niket Bhodia, Pratikkumar Prajapati, Fabio Di Troia, Mark Stamp
Transfer Learning for Image-based Malware Classification. ICISSP 2019: 719-726 - [i3]Swapna Vemparala, Fabio Di Troia, Corrado Aaron Visaggio, Thomas H. Austin, Mark Stamp:
Malware Detection Using Dynamic Birthmarks. CoRR abs/1901.07312 (2019) - [i2]Niket Bhodia, Pratikkumar Prajapati, Fabio Di Troia, Mark Stamp:
Transfer Learning for Image-Based Malware Classification. CoRR abs/1903.11551 (2019) - [i1]Neeraj Chavan, Fabio Di Troia, Mark Stamp:
A Comparative Analysis of Android Malware. CoRR abs/1904.00735 (2019) - 2018
- [j7]Suchita Deshmukh, Fabio Di Troia, Mark Stamp
Vigenère scores for malware detection. J. Comput. Virol. Hacking Tech. 14(2): 157-165 (2018) - [c11]Mark Stamp, Fabio Di Troia, Miles Stamp, Jasper Huang:
Hidden Markov Models for Vigenère Cryptanalysis. HistoCrypt 2018: 149:011 - [c10]Aneri Chavda, Katerina Potika, Fabio Di Troia, Mark Stamp
Support Vector Machines for Image Spam Analysis. ICETE (1) 2018: 597-607 - [c9]Naman Bagga, Fabio Di Troia, Mark Stamp
On the Effectiveness of Generic Malware Models. ICETE (1) 2018: 608-616 - [c8]Wei-Chung Huang, Fabio Di Troia, Mark Stamp
Robust Hashing for Image-based Malware Classification. ICETE (1) 2018: 617-625 - [c7]Jasper Huang, Fabio Di Troia, Mark Stamp
Acoustic Gait Analysis using Support Vector Machines. ICISSP 2018: 545-552 - [c6]Sravani Yajamanam, Vikash Raja Samuel Selvin, Fabio Di Troia, Mark Stamp
Deep Learning versus Gist Descriptors for Image-based Malware Classification. ICISSP 2018: 553-561 - [c5]Prathiba Nagarajan, Fabio Di Troia, Thomas H. Austin
Autocorrelation Analysis of Financial Botnet Traffic. ICISSP 2018: 599-606 - [p3]Deebiga Rajeswaran, Fabio Di Troia, Thomas H. Austin, Mark Stamp:
Function Call Graphs Versus Machine Learning for Malware Detection. Guide to Vulnerability Analysis for Computer Networks and Systems 2018: 259-279 - [p2]Dhiviya Dhanasekar, Fabio Di Troia, Katerina Potika, Mark Stamp:
Detecting Encrypted and Polymorphic Malware Using Hidden Markov Models. Guide to Vulnerability Analysis for Computer Networks and Systems 2018: 281-299 - [p1]Swathi Nambiar Kadala Manikoth, Fabio Di Troia, Mark Stamp:
Masquerade Detection on Mobile Devices. Guide to Vulnerability Analysis for Computer Networks and Systems 2018: 301-315 - 2017
- [j6]Rohit Vobbilisetty, Fabio Di Troia, Richard M. Low, Corrado Aaron Visaggio, Mark Stamp
Classic cryptanalysis using hidden Markov models. Cryptologia 41(1): 1-28 (2017) - [j5]Ismeet Kaur Makkar, Fabio Di Troia, Corrado Aaron Visaggio, Thomas H. Austin
SocioBot: a Twitter-based botnet. Int. J. Secur. Networks 12(1): 1-12 (2017) - [j4]Anusha Damodaran, Fabio Di Troia, Corrado Aaron Visaggio, Thomas H. Austin
A comparison of static, dynamic, and hybrid analysis for malware detection. J. Comput. Virol. Hacking Tech. 13(1): 1-12 (2017) - [j3]Swathi Pai, Fabio Di Troia, Corrado Aaron Visaggio, Thomas H. Austin
Clustering for malware classification. J. Comput. Virol. Hacking Tech. 13(2): 95-107 (2017) - [c4]Ankita Kapratwar, Fabio Di Troia, Mark Stamp
Static and Dynamic Analysis of Android Malware. ICISSP 2017: 653-662 - 2016
- [j2]Tanuvir Singh, Fabio Di Troia, Corrado Aaron Visaggio
Support vector machines and malware detection. J. Comput. Virol. Hacking Tech. 12(4): 203-212 (2016) - [j1]Usha Narra, Fabio Di Troia, Corrado Aaron Visaggio
Clustering versus SVM for malware detection. J. Comput. Virol. Hacking Tech. 12(4): 213-224 (2016) - [c3]Swapna Vemparala, Fabio Di Troia, Corrado Aaron Visaggio, Thomas H. Austin
Malware Detection Using Dynamic Birthmarks. IWSPA@CODASPY 2016: 41-46 - [c2]Nikitha Ganesh, Fabio Di Troia, Corrado Aaron Visaggio, Thomas H. Austin
Static Analysis of Malicious Java Applets. IWSPA@CODASPY 2016: 58-63 - [c1]Fabio Di Troia, Corrado Aaron Visaggio, Thomas H. Austin
Advanced transcriptase for JavaScript malware. MALWARE 2016: 121-128
Coauthor Index
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last updated on 2024-11-07 21:31 CET by the dblp team
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