Continuous Proof of Presence based on Touchscreen Devices Interactions and Signals

依赖于静态或定点身份验证的传统访问控制系统被认为是不安全的，不适合关键任务系统，特别是当用户共享他们的凭据时，即使安全策略禁止这些行为。如果不不断检查“你就是你声称的那个人”，潜在的安全漏洞几乎肯定会在某个时候发生。为了解决HCI触摸屏数据的这一挑战，我们的方法将侧重于调查可用的HCI触摸屏数据集，并验证它们对身份识别和验证的适用性。在研究了触摸屏交互数据后，我们将重点关注工程相关特征，以描述用户在与触摸屏交互时的独特行为。我们将研究不同的特征选择和提取技术，以确定身份验证的最佳特征。下一阶段将专注于评估只需要积极训练的模式分类算法（例如人工免疫系统），以确定最有前途的新颖性检测算法。最后，我们将提出一种非侵入式连续身份验证的体系结构。本项目的预期成果包括：1。评估使用触摸屏数据进行连续认证的有效性。从触摸屏交互数据中进行模式分类的工程特性3。设计了一种新的基于触摸屏数据的非侵入式连续认证模型。

Traditional access control systems that rely on static or fixed-point authentication are considered insecure andnot suitable for mission-critical systems, especially when the users share their credentials, even when thesecurity policies in place forbid those behaviours. Without continually checking that "you are who you claimyou are", a potential security breach is almost certain to happen at some point. To solve this challenges withHCI touch screen data our approach will focus on investigating the available HCI touch screen datasets andvalidate their fitness for identity recognition and verification. After studying the touchscreen interaction data,we will focus on engineering relevant features to describe the unique behaviours of the user while interactingwith touchscreen. We will investigate different feature selection and extraction techniques to identify the bestfeatures for identity verification. The next stage will focus on evaluating pattern classification algorithms thatrequire positive training only (e.g. artificial immune system) to identify the most promising algorithm fornovelty detection. Finally, we will propose an architecture for a non-intrusive continuous authentication. Theexpected outcome of the project includes the following:1. Evaluate the effectiveness of using touchscreen data for continuous authentication.2. Engineering features for pattern classifications from touchscreen interaction data3. Design a new non-intrusive continuous authentication model based on touch screen data.