@article{Diamantoulakis20201,

title = {Game theoretic honeypot deployment in smart grid},

author = { P. Diamantoulakis and C. Dalamagkas and P. Radoglou-Grammatikis and P. Sarigiannidis and G. Karagiannidis},

url = {https://www.researchgate.net/publication/343188880_Game_Theoretic_Honeypot_Deployment_in_Smart_Grid},

doi = {10.3390/s20154199},

year  = {2020},

date = {2020-01-01},

journal = {Sensors (Switzerland)},

volume = {20},

number = {15},

pages = {1-24},

abstract = {The smart grid provides advanced functionalities, including real-time monitoring, dynamic energy management, advanced pricing mechanisms, and self-healing, by enabling the two-way flow of power and data, as well as the use of Internet of Things (IoT) technologies and devices. However, converting the traditional power grids to smart grids poses severe security challenges and makes their components and services prone to cyber attacks. To this end, advanced techniques are required to mitigate the impact of the potential attacks. In this paper, we investigate the use of honeypots, which are considered to mimic the common services of the smart grid and are able to detect unauthorized accesses, collect evidence, and help hide the real devices. More specifically, the interaction of an attacker and a defender is considered, who both optimize the number of attacks and the defending system configuration, i.e., the number of real devices and honeypots, respectively, with the aim to maximize their individual payoffs. To solve this problem, game theoretic tools are used, considering an one-shot game and a repeated game with uncertainty about the payoff of the attacker, where the Nash Equilibrium (NE) and the Bayesian NE are derived, respectively. Finally, simulation results are provided, which illustrate the effectiveness of the proposed framework. © 2020 by the authors. Licensee MDPI, Basel, Switzerland.},

keywords = {Cybersecurity, Game theory, Honeypots, Smart Grid},

pubstate = {published},

tppubtype = {article}

}

@article{Dalamagkas2019103,

title = {Dynamic scheduling in TWDM-PONs using game theory},

author = { C. Dalamagkas and P. Sarigiannidis and S. Kapetanakis and I. Moscholios},

url = {https://www.researchgate.net/publication/321881881_Dynamic_scheduling_in_TWDM-PONs_using_game_theory},

doi = {10.1016/j.osn.2017.12.004},

year  = {2019},

date = {2019-01-01},

journal = {Optical Switching and Networking},

volume = {33},

pages = {103-113},

abstract = {Efficient utilization of Passive Optical Networks (PONs) within a broad region of high user numbers, heavy bandwidth demand and large-scale central servicing stations seems a challenging task in explosive high-bandwidth environments. New Generation PONs (NG-PONs) enable multiple channels in both directions and they seem promising towards meeting advanced user applications and services. However, sophisticated bandwidth distribution should be in place to ensure appropriate allocation and efficient management of heavy user demands subject to the available channels. Most of the literature on dynamic bandwidth distribution in NG-PONs usually pertains to heuristic techniques that may be susceptible to expert bias, require substantial knowledge and experience to be applied and their evaluation may focus primarily on minor issues vs. few fundamental major ones. To surpass these limitations game theory can be applied to address efficiently the above heuristic disadvantages and solve the heavy user load-heavy demand over large bandwidth problem in a stochastic way. This work presents the next step forwards using multi-channel multi-stochastic reasoning by utilizing the full channel range to satisfy fairly user requests and high network traffic within a NG-PON2 network. We present the full algorithm as applied to standardized NG-PON2 as well as a series of evaluation experiments to prove its applicability in terms of fairness, goodput and delay. According to the simulation results, the proposed scheme succeeds to provide a fair bandwidth distribution, when triggered, while it is able to a) reduce the experienced delay from 1 to 6 msec and b) double the offered goodput compared to the pure allocation scheme. © 2018 Elsevier B.V.},

keywords = {Game theory, Next-generation passive optical network 2, Scheduling, Time and wavelength division multiplexing},

pubstate = {published},

tppubtype = {article}

}