University of the Aegean

About: University of the Aegean is a education organization based out in Mytilene, Greece. It is known for research contribution in the topics: Population & Tourism. The organization has 2818 authors who have published 8100 publications receiving 179275 citations. The organization is also known as: UAEG.

Toward an integrated HF radar network in the Mediterranean Sea to improve search and rescue and oil spill response: the TOSCA project experience

Abstract: High-frequency (HF) coastal radars measure current velocity at the ocean surface with a 30–100 km range and 1–3 km resolution, every 0.25–1 h. HF radars are well suited to many applications, such as search and rescue (SaR), oil-spill mitigation and ecosystem management. Here we present a first organized core of 12 HF radars installed in five sites in four countries (Greece, Italy, France and Spain) within the European MED project, the Tracking Oil Spill and Coastal Awareness (TOSCA) network. Dedicated experiments tested radar capabilities to estimate transport driven by currents, which is the key feature for all the above applications. Experiments involved the deployment of drifters, i.e., floating buoys, acting as proxies for substances passively advected by currents. Using HF radars the search range is reduced by a factor of 1.6 to 5.3 after 24 h. The paper also underlines the importance of sharing common tools for HF radar data processing and the need to mitigate radio frequency interference. The effor...

Measurement of the production cross section of prompt J/ψ mesons in association with a W± boson in pp collisions at √s = 7 TeV with the ATLAS detector

Abstract: Measurement of the production cross section of prompt j/psi mesons in association with a W (+/-) boson in pp collisions root s=7 TeV with the ATLAS detector

New facets of mobile botnet: architecture and evaluation

Abstract: It is without a doubt that botnets pose a growing threat to the Internet, with DDoS attacks of any kind carried out by botnets to be on the rise. Nowadays, botmasters rely on advanced Command and Control (C&C) infrastructures to achieve their goals and most importantly to remain undetected. This work introduces two novel botnet architectures that consist only of mobile devices and evaluates both their impact in terms of DNS amplification and TCP flooding attacks, and their cost pertaining to the maintenance of the C&C channel. The first one puts forward the idea of using a continually changing mobile HTTP proxy in front of the botherder, while the other capitalizes on DNS protocol as a covert channel for coordinating the botnet. That is, for the latter, the messages exchanged among the bots and the herder appear as legitimate DNS transactions. Also, a third architecture is described and assessed, which is basically an optimized variation of the first one. Namely, it utilizes a mixed layout where all the attacking bots are mobile, but the proxy machines are typical PCs not involved in the actual attack. For the DNS amplification attack, which is by nature more powerful, we report an amplification factor that fluctuates between 32.7 and 34.1. Also, regarding the imposed C&C cost, we assert that it is minimal (about 0.25 Mbps) per bot in the worst case happening momentarily when the bot learns about the parameters of the attack.

QCSP-solve: a solver for quantified constraint satisfaction problems

Abstract: The Quantified Constraint Satisfaction Problem (QCSP) is a generalization of the CSP in which some variables are universally quantified. It has been shown that a solver based on an encoding of QCSP into QBF can outperform the existing direct QCSP approaches by several orders of magnitude. In this paper we introduce an efficient QCSP solver. We show how knowledge learned from the successful encoding of QCSP into QBF can be utilized to enhance the existing QCSP techniques and speed up search by orders of magnitude. We also show how the performance of the solver can be further enhanced by incorporating advanced look-back techniques such as CBJ and solution-directed pruning. Experiments demonstrate that our solver is several orders of magnitude faster than existing direct approaches to QCSP solving, and significantly outperforms approaches based on encoding QCSPs as QBFs.