Outputs (32)

Defending against adversarial machine learning attacks using hierarchical learning: A case study on network traffic attack classification (2022)
Journal Article
McCarthy, A., Ghadafi, E., Andriotis, P., & Legg, P. (2023). Defending against adversarial machine learning attacks using hierarchical learning: A case study on network traffic attack classification. Journal of Information Security and Applications, 72, Article 103398. https://doi.org/10.1016/j.jisa.2022.103398

Machine learning is key for automated detection of malicious network activity to ensure that computer networks and organizations are protected against cyber security attacks. Recently, there has been growing interest in the domain of adversarial mach... Read More about Defending against adversarial machine learning attacks using hierarchical learning: A case study on network traffic attack classification.

AI hyped? A horizon scan of discourse on artificial intelligence in education (AIED) and development (2022)
Journal Article
Nemorin, S., Vlachidis, A., Ayerakwa, H. M., & Andriotis, P. (2023). AI hyped? A horizon scan of discourse on artificial intelligence in education (AIED) and development. Learning, Media and Technology, 48(1), 38-51. https://doi.org/10.1080/17439884.2022.2095568

The study seeks to understand how the AI ecosystem might be implicated in a form of knowledge production which reifies particular kinds of epistemologies over others. Using text mining and thematic analysis, this paper offers a horizon scan of the ke... Read More about AI hyped? A horizon scan of discourse on artificial intelligence in education (AIED) and development.

Bu-Dash: A universal and dynamic graphical password scheme (2022)
Conference Proceeding
Andriotis, P., Kirby, M., & Takasu, A. (2022). Bu-Dash: A universal and dynamic graphical password scheme. In A. Moallem (Ed.), HCI for Cybersecurity, Privacy and Trust: 4th International Conference, HCI-CPT 2022, Held as Part of the 24th HCI International Conference, HCII 2022, Virtual Event, June 26 – July 1, 2022, Proceedings (209-227). https://doi.org/10.1007/978-3-031-05563-8_14

Biometric authentication gradually replaces knowledge-based methods on mobile devices. However, Personal Identification Numbers, passcodes, and graphical password schemes such as the Android Pattern Unlock (APU) are often the primary means for authen... Read More about Bu-Dash: A universal and dynamic graphical password scheme.

Functionality-preserving adversarial machine learning for robust classification in cybersecurity and intrusion detection domains: A survey (2022)
Journal Article
McCarthy, A., Ghadafi, E., Andriotis, P., & Legg, P. (2022). Functionality-preserving adversarial machine learning for robust classification in cybersecurity and intrusion detection domains: A survey. Journal of Cybersecurity and Privacy, 2(1), 154-190. https://doi.org/10.3390/jcp2010010

Machine learning has become widely adopted as a strategy for dealing with a variety of cybersecurity issues, ranging from insider threat detection to intrusion and malware detection. However, by their very nature, machine learning systems can introdu... Read More about Functionality-preserving adversarial machine learning for robust classification in cybersecurity and intrusion detection domains: A survey.

Feature vulnerability and robustness assessment against adversarial machine learning attacks (2021)
Conference Proceeding
Mccarthy, A., Andriotis, P., Ghadafi, E., & Legg, P. (2021). Feature vulnerability and robustness assessment against adversarial machine learning attacks. In 2021 International Conference on Cyber Situational Awareness, Data Analytics and Assessment (CyberSA). https://doi.org/10.1109/CyberSA52016.2021.9478199

Whilst machine learning has been widely adopted for various domains, it is important to consider how such techniques may be susceptible to malicious users through adversarial attacks. Given a trained classifier, a malicious attack may attempt to craf... Read More about Feature vulnerability and robustness assessment against adversarial machine learning attacks.

To allow, or deny? That is the question (2020)
Conference Proceeding
Andriotis, P., & Takasu, A. (2020). To allow, or deny? That is the question. In HCI for Cybersecurity, Privacy and Trust (287-304). https://doi.org/10.1007/978-3-030-50309-3_20

The Android ecosystem is dynamic and diverse. Controls have been set in place to allow mobile device users to regulate exchanged data and restrict apps from accessing sensitive personal information and system resources. Modern versions of the operati... Read More about To allow, or deny? That is the question.

Dataset: To Allow, or Deny? That is the Question (2019)
Dataset
Andriotis, P., & Takasu, A. (in press). Dataset: To Allow, or Deny? That is the Question. [Dataset]

MaMaDroid: Detecting Android malware by building Markov chains of behavioral models (extended version) (2019)
Journal Article
Onwuzurike, L., Mariconti, E., Andriotis, P., De Cristofaro, E., Ross, G., & Stringhini, G. (2019). MaMaDroid: Detecting Android malware by building Markov chains of behavioral models (extended version). ACM Transactions on Privacy and Security, 22(2), Article 14. https://doi.org/10.1145/3313391

As Android has become increasingly popular, so has malware targeting it, thus motivating the research community to propose different detection techniques. However, the constant evolution of the Android ecosystem, and of malware itself, makes it hard... Read More about MaMaDroid: Detecting Android malware by building Markov chains of behavioral models (extended version).

Distributed consensus algorithm for events detection in cyber-physical systems (2019)
Journal Article
Li, S., Zhao, S., Yang, P., Andriotis, P., Xu, L., & Sun, Q. (2019). Distributed consensus algorithm for events detection in cyber-physical systems. IEEE Internet of Things, 6(2), 2299-2308. https://doi.org/10.1109/JIOT.2019.2906157

In the harsh environmental conditions of cyber-physical systems (CPSs), the consensus problem seems to be one of the central topics that affect the performance of consensus-based applications, such as events detection, estimation, tracking, blockchai... Read More about Distributed consensus algorithm for events detection in cyber-physical systems.

Emotional bots: Content-based spammer detection on social media (2019)
Conference Proceeding
Andriotis, P., & Takasu, A. (2019). Emotional bots: Content-based spammer detection on social media. . https://doi.org/10.1109/WIFS.2018.8630760

Recent research indicates that a considerable amount of content on social media is generated by automated accounts. The automata present sophisticated behavior – mimicking humans– aiming at evading traditional detection methods. In this paper, we... Read More about Emotional bots: Content-based spammer detection on social media.