| Title | Password Guessing Using Machine Learning on Wearables |
| Publication Type | Conference Paper |
| Year of Publication | 2019 |
| Authors | Pandelea, Alexandru-Ionut, Chiroiu, Mihai-Daniel |
| Conference Name | 2019 22nd International Conference on Control Systems and Computer Science (CSCS) |
| Keywords | accelerometer, Accelerometers, Bluetooth, GPS, health context, Human Behavior, IoT, learning (artificial intelligence), machine learning, machine learning algorithms, password guessing, privacy, pubcrawl, raw data, Resiliency, Scalability, security, security of data, security purposes, sensitive data, ubiquitous items, wearable computers, Wearable Device, wearables, wearables security |
| Abstract | Wearables are now ubiquitous items equipped with a multitude of sensors such as GPS, accelerometer, or Bluetooth. The raw data from this sensors are typically used in a health context. However, we can also use it for security purposes. In this paper, we present a solution that aims at using data from the sensors of a wearable device to identify the password a user is typing on a keyboard by using machine learning algorithms. Hence, the purpose is to determine whether a malicious third party application could extract sensitive data through the raw data that it has access to. |
| DOI | 10.1109/CSCS.2019.00055 |
| Citation Key | pandelea_password_2019 |
Password Guessing Using Machine Learning on Wearables