Malicious entity detection using fine-grained DNA-inspired behavioural modelling

我们对社交媒体网络（主要是Twitter）上的机器人检测问题的论文进行了文献综述，因为该项目的灵感来自于这个问题。很明显，自该项目设想以来，Twitter上的自动账户变得更加复杂，更难检测，因为它们现在更能够模仿人类行为。因此，我们投资将网络安全与生物信息学结合起来。我们致力于三个方面，以实现生物信息学原则在网络安全研究中的整合：（1）对使用“k-mers”的新颖图形密码方案的复杂性的理论评估，（2）在社交网络的突破性研究领域内的受DNA启发的行为建模的聚合，以及（3）设想将从后一研究方向学到的知识转移到移动的环境中的恶意软件检测问题，我们最初探索了如何将生物信息学（在理论层面）嵌入到量化图形密码复杂性（和安全性）的问题中。因此，我们实现了一个图形密码方案，并在运行Android操作系统的移动的设备上测试其可用性。然后，我们使用Lothaire的组合理论（“有限字”的定义，其次是简单的度量“一个字的复杂性”）与基本的生物信息学（k-mers），我们引入了一个复杂性度量来量化所提出的图形密码方案空间，旨在确定它与其他图形密码方案的比较。

We did a literature review of papers dealing with the problem of bot detection on social media networks (focused on Twitter) because the inspiration for the project was driven from this problem. It was obvious that since the project was envisioned, automated accounts on Twitter have become more sophisticated and more difficult to detect, as they are now more able to mimic human behaviour. Thus, we invested to aggregate Cyber Security with Bioinformatics. We worked towards three strands to achieve the integration of Bioinformatics principles in Cyber Security research: (1) a theoretical assessment of the complexity of a novel graphical password scheme using “k-mers”, (2) aggregation of DNA-inspired behavioural modelling within a ground-breaking field of research for social networks, and (3) envision to transfer knowledge learned from the latter direction of research to the problem of malicious software detection in mobile environments, using GNNs.We initially explored how we can embed Bioinformatics (in a theoretical level) to the problem of quantifying complexity (and security) for graphical passwords. We therefore implemented a graphical password scheme and tested its usability on mobile devices running the Android operating system. Then, we used Lothaire’s Combinatorics theory (definition of “finite word”, followed by the simple metric “complexity of a word”) with basic Bioinformatics (k-mers) and we introduced a complexity metric to quantify the proposed graphical password scheme space, aiming to identify how it compares with other graphical password schemes.