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Angelos K. Marnerides
Lancaster University
Distributed computingComputer networkComputer scienceAnomaly detectionCloud computing
52Publications
9H-index
324Citations
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#2Anish JindalH-Index: 12
Last. Angelos K. MarneridesH-Index: 9
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#1Amit Dvir (Ariel University)H-Index: 9
#2Angelos K. Marnerides (Lancaster University)H-Index: 9
Last. Chen Hajaj (Ariel University)H-Index: 3
view all 5 authors...
Abstract Cyber threat intelligence officers and forensics investigators often require the behavioural profiling of groups based on their online video viewing activity. It has been demonstrated that encrypted video traffic can be classified under the assumption of using a known subset of video titles based on temporal video viewing trends of particular groups. Nonetheless, composing such a subset is extremely challenging in real situations. Therefore, this work exhibits a novel profiling scheme f...
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#1Anish Jindal (Lancaster University)H-Index: 12
#2Alberto Schaeffer-Filho (UFRGS: Universidade Federal do Rio Grande do Sul)H-Index: 15
Last. Lisandro Zambenedetti Granville (UFRGS: Universidade Federal do Rio Grande do Sul)H-Index: 21
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The increasing use of information and communication technology (ICT) in electricity grid infrastructures facilitates improved energy generation, transmission, and distribution. However, smart grids are still in their infancy with a disparate regional role out. Due to the involved costs utility providers are only embedding ICT in selected parts of the grid, thereby creating only partial smart grid infrastructures. We argue that using the data provided by these partial smart grid deployments can s...
3 CitationsSource
Jul 15, 2019 in GLOBECOM (Global Communications Conference)
#1Owen P. Dwyer (Lancaster University)
#2Angelos K. Marnerides (Lancaster University)H-Index: 9
Last. Troy MurschH-Index: 1
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Internet-wide security and resilience have traditionally been subject to large-scale DDoS attacks initiated by various types of botnets. Since the Mirai outbreak in 2016 myriads of Mirai-alike IoT-based botnets have emerged. Such botnets rely on Mirai's base malware code and they infiltrate vulnerable IoT devices on an Internet-wide scale such as to instrument them to perform large-scale attacks such as DDoS. As recently shown, DDoS attacks triggered by Mirai-alike IoT-based botnets go far beyon...
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#1Angelos K. Marnerides (Lancaster University)H-Index: 9
#2Vasileios Giotsas (Lancaster University)H-Index: 10
Last. Troy MurschH-Index: 1
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The 2016 Mirai outbreak established an entirely new mindset in the history of large-scale Internet attacks. A plethora of Mirai-like variants have emerged in the last two years that are capable to infiltrate any type of device. In this paper we provide a 7-month retrospective analysis of Internet-connected energy systems that are infected by Mirai-like malware variants. By utilizing network measurements from several Internet vantage points, we demonstrate that a number of energy systems on a glo...
1 CitationsSource
#1Martin Bor (Lancaster University)H-Index: 5
#2Angelos K. Marnerides (Lancaster University)H-Index: 9
Last. Utz Roedig (Information Technology University)H-Index: 26
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Smart Energy Systems represent a radical shift in the approach to energy generation and demand, driven by decentralisation of the energy system to large numbers of low-capacity devices. Managing this flexibility is often driven by machine learning, and requires real-time control and aggregation of these devices, involving a diverse set of companies and devices and creating a longer chain of trust. This poses a security risk, as it is sensitive to adversarial machine learning, whereby models are ...
2 CitationsSource
#1Anish Jindal (Lancaster University)H-Index: 12
#2Angelos K. Marnerides (Lancaster University)H-Index: 9
Last. David Hutchison (Lancaster University)H-Index: 31
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Distributed renewable energy systems (DRESs) and their interconnection network, typically using Internet-based protocols, are susceptible to a wide range of cybersecurity and resilience challenges. These challenges have been shown to cause problems for the overall grid optimization process. In order to detect such events, we argue that an adequate correlation between network and energy generation data is required. Therefore, in this study, we provide a work-in-progress insight related to the pro...
3 CitationsSource
May 12, 2019 in ICASSP (International Conference on Acoustics, Speech, and Signal Processing)
#1Anish Jindal (Lancaster University)H-Index: 12
#2Angelos K. Marnerides (Lancaster University)H-Index: 9
Last. David Hutchison (Lancaster University)H-Index: 31
view all 5 authors...
Distributed Renewable Energy Sources (DRESs) such as wind and solar are becoming a promising alternative for the energy supply in modern (smart) electricity grids as part of future sustainable smart cities. Successful integration of DRESs requires efficient, resilient, and secure communication in order to satisfy the highly challenging and real-time constraints of smart city applications. Regardless of the various research solutions proposed in this context within the last decade, the relevant s...
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Last. Angelos K. MarneridesH-Index: 9
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Despite the large number of research efforts that applied specific machine learning algorithms for network traffic classification, recent work has highlighted limitations and particularities of individual algorithms that make them more suitable to specific types of traffic and scenarios. As such, an important topic in this area is how to combine individual algorithms using meta-learning techniques in order to obtain more robust traffic classification metrics. This paper presents a comparative an...
1 CitationsSource
#1Amit Dvir (Ariel University)H-Index: 9
#2Angelos K. Marnerides (Lancaster University)H-Index: 9
Last. Nehor Golan (Ariel University)H-Index: 1
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Recent stringent end-user security and privacy requirements caused the dramatic rise of encrypted video streams in which YouTube encrypted traffic is one of the most prevalent. Regardless of their encrypted nature, metadata derived from such traffic flows can be utilized to identify the title of a video, thus enabling the classification of video streams into a single video title using a given video title set. Nonetheless, scenarios where no video title set is present and a supervised approach is...
1 CitationsSource
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