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All 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.

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.

Studying users’ adaptation to Android's run-time fine-grained access control system (2018)
Journal Article
Andriotis, P., Stringhini, G., & Sasse, A. (2018). Studying users’ adaptation to Android's run-time fine-grained access control system. Journal of Information Security and Applications, 40, 31-43. https://doi.org/10.1016/j.jisa.2018.02.004

© 2018 Elsevier Ltd The advent of the sixth Android version brought a significant security and privacy advancement to its users. The platform's security model has changed dramatically, allowing users to grant or deny access to resources when requeste... Read More about Studying users’ adaptation to Android's run-time fine-grained access control system.

MAMADROID: Detecting Android Malware by Building Markov Chains of Behavioral Models (2017)
Presentation / Conference
Mariconti, E., Onwuzurike, L., Andriotis, P., De Cristofaro, E., Ross, G., & Stringhini, G. (2017, February). MAMADROID: Detecting Android Malware by Building Markov Chains of Behavioral Models. Paper presented at NDSS Symposium 2017, San Diego, USA

The rise in popularity of the Android platform has resulted in an explosion of malware threats targeting it. As both Android malware and the operating system itself constantly evolve, it is very challenging to design robust malware mitigation techniq... Read More about MAMADROID: Detecting Android Malware by Building Markov Chains of Behavioral Models.

Permissions snapshots: Assessing users' adaptation to the Android runtime permission model (2017)
Conference Proceeding
Andriotis, P., Sasse, M. A., & Stringhini, G. (2017). Permissions snapshots: Assessing users' adaptation to the Android runtime permission model. . https://doi.org/10.1109/WIFS.2016.7823922

© 2016 IEEE. The Android operating system changed its security-and privacy-related permission model recently, offering its users the ability to control resources that applications are allowed to access on their devices. This major change to the tradi... Read More about Permissions snapshots: Assessing users' adaptation to the Android runtime permission model.

Privacy decision-making in the digital era: A game theoretic review (2017)
Journal Article
Anastasopoulou, K., Kokolakis, S., & Andriotis, P. (2017). Privacy decision-making in the digital era: A game theoretic review. Lecture Notes in Artificial Intelligence, 10292 LNCS, 589-603. https://doi.org/10.1007/978-3-319-58460-7_41

© Springer International Publishing AG 2017. Information privacy is constantly negotiated when people interact with enterprises and government agencies via the Internet. In this context, all relevant stakeholders take privacy-related decisions. Indiv... Read More about Privacy decision-making in the digital era: A game theoretic review.

A comparative study of android users’ privacy preferences under the runtime permission model (2017)
Journal Article
Andriotis, P., Li, S., Spyridopoulos, T., & Stringhini, G. (2017). A comparative study of android users’ privacy preferences under the runtime permission model. Lecture Notes in Artificial Intelligence, 10292 LNCS, 604-622. https://doi.org/10.1007/978-3-319-58460-7_42

© Springer International Publishing AG 2017. Android users recently were given the ability to selectively grant access to sensitive resources of their mobile devices when apps request them at runtime. The Android fine-grained runtime permission model... Read More about A comparative study of android users’ privacy preferences under the runtime permission model.

Risk Assessment for Mobile Systems Through a Multilayered Hierarchical Bayesian Network (2016)
Journal Article
Li, S., Tryfonas, T., Russell, G., & Andriotis, P. (2016). Risk Assessment for Mobile Systems Through a Multilayered Hierarchical Bayesian Network. IEEE Transactions on Cybernetics, 46(8), 1749-1759. https://doi.org/10.1109/TCYB.2016.2537649

© 2015 IEEE. Mobile systems are facing a number of application vulnerabilities that can be combined together and utilized to penetrate systems with devastating impact. When assessing the overall security of a mobile system, it is important to assess... Read More about Risk Assessment for Mobile Systems Through a Multilayered Hierarchical Bayesian Network.

A study on usability and security features of the Android pattern lock screen (2016)
Journal Article
Andriotis, P., Oikonomou, G., Mylonas, A., & Tryfonas, T. (2016). A study on usability and security features of the Android pattern lock screen. Information and Computer Security, 24(1), 53-72. https://doi.org/10.1108/ICS-01-2015-0001

© Emerald Group Publishing Limited. Purpose: - The Android pattern lock screen (or graphical password) is a popular user authentication method that relies on the advantages provided by the visual representation of a password, which enhance its memora... Read More about A study on usability and security features of the Android pattern lock screen.

Optimizing short message text sentiment analysis for mobile device forensics (2016)
Journal Article
Aboluwarin, O., Andriotis, P., Takasu, A., & Tryfonas, T. (2016). Optimizing short message text sentiment analysis for mobile device forensics. IFIP Advances in Information and Communication Technology, 484, 69-87. https://doi.org/10.1007/978-3-319-46279-0_4

© IFIP International Federation for Information Processing 2016. Mobile devices are now the dominant medium for communications. Humans express various emotions when communicating with others and these communications can be analyzed to deduce their em... Read More about Optimizing short message text sentiment analysis for mobile device forensics.

Mass surveillance in cyberspace and the lost art of keeping a secret: Policy lessons for government after the snowden leaks (2016)
Journal Article
Tryfonas, T., Carter, M., Crick, T., & Andriotis, P. (2016). Mass surveillance in cyberspace and the lost art of keeping a secret: Policy lessons for government after the snowden leaks. Lecture Notes in Artificial Intelligence, 9750, 174-185. https://doi.org/10.1007/978-3-319-39381-0_16

© Springer International Publishing Switzerland 2016. Global security concerns, acts of terrorism and organised crime activity have motivated nation states to delve into implementing measures of mass surveillance in cyberspace, the breadth of which w... Read More about Mass surveillance in cyberspace and the lost art of keeping a secret: Policy lessons for government after the snowden leaks.

Impact of user data privacy management controls on mobile device investigations (2016)
Journal Article
Andriotis, P., & Tryfonas, T. (2016). Impact of user data privacy management controls on mobile device investigations. IFIP Advances in Information and Communication Technology, 484, 89-105. https://doi.org/10.1007/978-3-319-46279-0_5

© IFIP International Federation for Information Processing 2016. There are many different types of mobile device users, but most of them do not seek to expand the functionality of their smartphones and prefer to interact with them using predefined us... Read More about Impact of user data privacy management controls on mobile device investigations.