Outputs (52)

Cloud Security, Privacy and Trust Baselines (2020)
Book Chapter
Pitropakis, N., Katsikas, S., & Lambrinoudakis, C. (2020). Cloud Security, Privacy and Trust Baselines. In J. R. Vacca (Ed.), Cloud Computing Security: Foundations and Challenges. Boca Raton, US: CRC Press. https://doi.org/10.1201/9780429055126

Cloud services vary from data storage and processing to software provision, posing requirements for high availability and on-demand commitment-free provision of services. Cloud providers must provide information through their privacy policy and/or up... Read More about Cloud Security, Privacy and Trust Baselines.

Exploring Adversarial Attacks and Defences for Fake Twitter Account Detection (2020)
Journal Article
Kantartopoulos, P., Pitropakis, N., Mylonas, A., & Kylilis, N. (2020). Exploring Adversarial Attacks and Defences for Fake Twitter Account Detection. Technologies, 8(4), Article 64. https://doi.org/10.3390/technologies8040064

Social media has become very popular and important in people’s lives, as personal ideas, beliefs and opinions are expressed and shared through them. Unfortunately, social networks, and specifically Twitter, suffer from massive existence and perpetual... Read More about Exploring Adversarial Attacks and Defences for Fake Twitter Account Detection.

A Distributed Trust Framework for Privacy-Preserving Machine Learning (2020)
Presentation / Conference Contribution
Abramson, W., Hall, A. J., Papadopoulos, P., Pitropakis, N., & Buchanan, W. J. (2020, September). A Distributed Trust Framework for Privacy-Preserving Machine Learning. Presented at The 17th International Conference on Trust, Privacy and Security in Digit

When training a machine learning model, it is standard procedure for the researcher to have full knowledge of both the data and model. However, this engenders a lack of trust between data owners and data scientists. Data owners are justifiably reluct... Read More about A Distributed Trust Framework for Privacy-Preserving Machine Learning.

Microtargeting or Microphishing? Phishing Unveiled (2020)
Presentation / Conference Contribution
Khursheed, B., Pitropakis, N., McKeown, S., & Lambrinoudakis, C. (2020). Microtargeting or Microphishing? Phishing Unveiled. In Trust, Privacy and Security in Digital Business (89-105). https://doi.org/10.1007/978-3-030-58986-8_7

Online advertisements delivered via social media platforms function in a similar way to phishing emails. In recent years there has been a growing awareness that political advertisements are being microtargeted and tailored to specific demographics, w... Read More about Microtargeting or Microphishing? Phishing Unveiled.

Privacy-Preserving Passive DNS (2020)
Journal Article
Papadopoulos, P., Pitropakis, N., Buchanan, W. J., Lo, O., & Katsikas, S. (2020). Privacy-Preserving Passive DNS. Computers, 9(3), Article 64. https://doi.org/10.3390/computers9030064

The Domain Name System (DNS) was created to resolve the IP addresses of web servers to easily remembered names. When it was initially created, security was not a major concern; nowadays, this lack of inherent security and trust has exposed the global... Read More about Privacy-Preserving Passive DNS.

Monitoring Users’ Behavior: Anti-Immigration Speech Detection on Twitter (2020)
Journal Article
Pitropakis, N., Kokot, K., Gkatzia, D., Ludwiniak, R., Mylonas, A., & Kandias, M. (2020). Monitoring Users’ Behavior: Anti-Immigration Speech Detection on Twitter. Machine Learning and Knowledge Extraction, 2(3), 192-215. https://doi.org/10.3390/make203

The proliferation of social media platforms changed the way people interact online. However, engagement with social media comes with a price, the users’ privacy. Breaches of users’ privacy, such as the Cambridge Analytica scandal, can reveal how the... Read More about Monitoring Users’ Behavior: Anti-Immigration Speech Detection on Twitter.

Testing And Hardening IoT Devices Against the Mirai Botnet (2020)
Presentation / Conference Contribution
Kelly, C., Pitropakis, N., McKeown, S., & Lambrinoudakis, C. (2020, June). Testing And Hardening IoT Devices Against the Mirai Botnet. Presented at IEEE International Conference on Cyber Security and Protection of Digital Services (Cyber Security 2020), D

A large majority of cheap Internet of Things (IoT) devices that arrive brand new, and are configured with out-of-the-box settings, are not being properly secured by the manufactures, and are vulnerable to existing malware lurking on the Internet. Amo... Read More about Testing And Hardening IoT Devices Against the Mirai Botnet.

Towards The Creation of A Threat Intelligence Framework for Maritime Infrastructures (2020)
Presentation / Conference Contribution
Pitropakis, N., Logothetis, M., Andrienko, G., Karapistoli, I., Stephanatos, J., & Lambrinoudakis, C. (2020). Towards The Creation of A Threat Intelligence Framework for Maritime Infrastructures. In Computer Security: ESORICS 2019 International Workshops

The maritime ecosystem has undergone through changes due to the increasing use of information systems and smart devices. The newly introduced technologies give rise to new attack surface in maritime infrastructures. In this position paper, we propose... Read More about Towards The Creation of A Threat Intelligence Framework for Maritime Infrastructures.

A Taxonomy and Survey of Attacks Against Machine Learning (2019)
Journal Article
Pitropakis, N., Panaousis, E., Giannetsos, T., Anastasiadis, E., & Loukas, G. (2019). A Taxonomy and Survey of Attacks Against Machine Learning. Computer Science Review, 34, https://doi.org/10.1016/j.cosrev.2019.100199

The majority of machine learning methodologies operate with the assumption that their environment is benign. However, this assumption does not always hold, as it is often advantageous to adversaries to maliciously modify the training (poisoning attac... Read More about A Taxonomy and Survey of Attacks Against Machine Learning.

An Enhanced Cyber Attack Attribution Framework (2018)
Presentation / Conference Contribution
Pitropakis, N., Panaousis, E., Giannakoulias, A., Kalpakis, G., Rodriguez, R. D., & Sarigiannidis, P. (2018). An Enhanced Cyber Attack Attribution Framework. In S. Furnell, H. Mouratidis, & G. Pernul (Eds.), Trust, Privacy and Security in Digital Business

Advanced Persistent Threats (APTs) are considered as the threats that are the most challenging to detect and defend against. As APTs use sophisticated attack methods, cyber situational awareness and especially cyber attack attribution are necessary f... Read More about An Enhanced Cyber Attack Attribution Framework.