Dr Panos Andriotis' Outputs (4)

Defending against adversarial machine learning attacks using hierarchical learning: A case study on network traffic attack classification (2022)
Journal Article

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

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)
Presentation / Conference Contribution

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

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.