Machine learning enabled industrial iot security: Challenges, trends and solutions

C Ni, SC Li - Journal of Industrial Information Integration, 2024 - Elsevier
Abstract Introduction: The increasingly integrated Industrial IoT (IIoT) with industrial systems
brings benefits such as intelligent analytics, predictive maintenance, and remote monitoring …

[HTML][HTML] Bridging the gap: A survey and classification of research-informed Ethical Hacking tools

P Modesti, L Golightly, L Holmes, C Opara… - Journal of Cybersecurity …, 2024 - mdpi.com
The majority of Ethical Hacking (EH) tools utilised in penetration testing are developed by
practitioners within the industry or underground communities. Similarly, academic …

Passgan: A deep learning approach for password guessing

B Hitaj, P Gasti, G Ateniese, F Perez-Cruz - Applied Cryptography and …, 2019 - Springer
State-of-the-art password guessing tools, such as HashCat and John the Ripper, enable
users to check billions of passwords per second against password hashes. In addition to …

Fast, lean, and accurate: Modeling password guessability using neural networks

W Melicher, B Ur, SM Segreti, S Komanduri… - 25th USENIX Security …, 2016 - usenix.org
Human-chosen text passwords, today's dominant form of authentication, are vulnerable to
guessing attacks. Unfortunately, existing approaches for evaluating password strength by …

Measuring {Real-World} Accuracies and Biases in Modeling Password Guessability

B Ur, SM Segreti, L Bauer, N Christin… - 24th USENIX Security …, 2015 - usenix.org
Parameterized password guessability—how many guesses a particular cracking algorithm
with particular training data would take to guess a password—has become a common metric …

On the accuracy of password strength meters

M Golla, M Dürmuth - Proceedings of the 2018 ACM SIGSAC conference …, 2018 - dl.acm.org
Password strength meters are an important tool to help users choose secure passwords.
Strength meters can only then provide reasonable guidance when they are accurate, ie …

[PDF][PDF] Who Are You? A Statistical Approach to Measuring User Authenticity.

D Freeman, S Jain, M Dürmuth, B Biggio, G Giacinto - NDSS, 2016 - iris.unica.it
Passwords are used for user authentication by almost every Internet service today, despite a
number of wellknown weaknesses. Numerous attempts to replace passwords have failed, in …

Improving password guessing via representation learning

D Pasquini, A Gangwal, G Ateniese… - … IEEE Symposium on …, 2021 - ieeexplore.ieee.org
Learning useful representations from unstructured data is one of the core challenges, as
well as a driving force, of modern data-driven approaches. Deep learning has demonstrated …

Better managed than memorized? Studying the Impact of Managers on Password Strength and Reuse

SG Lyastani, M Schilling, S Fahl, M Backes… - 27th USENIX Security …, 2018 - usenix.org
Despite their well-known security problems, passwords are still the incumbent authentication
method for virtually all online services. To remedy the situation, users are very often referred …

Chunk-level password guessing: Towards modeling refined password composition representations

M Xu, C Wang, J Yu, J Zhang, K Zhang… - Proceedings of the 2021 …, 2021 - dl.acm.org
Textual password security hinges on the guessing models adopted by attackers, in which a
suitable password composition representation is an influential factor. Unfortunately, the …