![]() Finally, we prove that our models enhanced password strength estimation through a comparison with zxcvbn.Īs the computing power of IoT devices such as drones and smartwatches have improved, they have been utilized not only for entertainment purposes but also in various fields, such as military services and delivery services. Through additional performance experiments with PCFG, we identified the cracking performance advantages of PassGAN and our models over PCFG. In the password cracking performance experiments, our models showed 10–15% better performance than PassGAN. We studied some methods of improving the performance of PassGAN, and developed two approaches for better password cracking: the first was changing the convolutional neural network (CNN)-based improved Wasserstein GAN (IWGAN) cost function to an RNN-based cost function the second was employing the dual-discriminator GAN structure. These advanced password cracking techniques contribute to the development of better password strength checkers. ![]() The Markov model and probabilistic context-free-grammar (PCFG) are representative research results, and PassGAN, which uses generative adversarial networks (GANs), was recently introduced. Research has been conducted to better exploit weak passwords to improve password-cracking performance. Finally, this weakness creates a security hole in networks by giving hackers access to an IoT device easily. This weakness enables free password cracking tools such as Hashcat and JtR to execute millions of cracking attempts per second. The default passwords of IoT also are text-based passwords and are easy to crack. However, these sample passwords are not difficult to crack. This reliance on memory is a weakness of passwords, and people therefore usually use easy-to-remember passwords, such as “iloveyou1234”. Password authentication can be simply implemented because it does not require any equipment, unlike biometric authentication, and it relies only on the users’ memory. ![]() Text-based passwords are a fundamental and popular means of authentication. ![]()
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