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Filters: Author is Anagnostopoulos, Nikolaos Athanasios  [Clear All Filters]
2022-02-04
Anagnostopoulos, Nikolaos Athanasios, Fan, Yufan, Heinrich, Markus, Matyunin, Nikolay, Püllen, Dominik, Muth, Philipp, Hatzfeld, Christian, Rosenstihl, Markus, Arul, Tolga, Katzenbeisser, Stefan.  2021.  Low-Temperature Attacks Against Digital Electronics: A Challenge for the Security of Superconducting Modules in High-Speed Magnetic Levitation (MagLev) Trains. 2021 IEEE 14th Workshop on Low Temperature Electronics (WOLTE). :1–4.
This work examines volatile memory modules as ephemeral key storage for security applications in the context of low temperatures. In particular, we note that such memories exhibit a rising level of data remanence as the temperature decreases, especially for temperatures below 280 Kelvin. Therefore, these memories cannot be used to protect the superconducting modules found in high-speed Magnetic Levitation (MagLev) trains, as such modules most often require extremely low temperatures in order to provide superconducting applications. Thus, a novel secure storage solution is required in this case, especially within the oncoming framework concept of the internet of railway things, which is partially based on the increasing utilisation of commercial off-the-shelf components and potential economies of scale, in order to achieve cost efficiency and, thus, widespread adoption. Nevertheless, we do note that volatile memory modules can be utilised as intrinsic temperature sensors, especially at low temperatures, as the data remanence they exhibit at low temperatures is highly dependent on the ambient temperature, and can, therefore, be used to distinguish between different temperature levels.
2020-03-23
Arul, Tolga, Anagnostopoulos, Nikolaos Athanasios, Katzenbeisser, Stefan.  2019.  Privacy Usability of IPTV Recommender Systems. 2019 IEEE International Conference on Consumer Electronics (ICCE). :1–2.
IPTV is capable of providing recommendations for upcoming TV programs based on consumer feedback. With the increasing popularity and performance of recommender systems, risks of user privacy breach emerge. Although several works about privacy-preserving designs of recommender systems exist in the literature, a detailed analysis of the current state-of-the-art regarding privacy as well as an investigation of the usability aspects of such systems, so far, have not received consideration. In this paper, we survey current approaches for recommender systems by studying their privacy and usability properties in the context of IPTV.