TY - GEN
T1 - Proactive Defense Against Physical Denial of Service Attacks Using Poisson Signaling Games
AU - Pawlick, Jeffrey
AU - Zhu, Quanyan
N1 - Publisher Copyright:
© 2017, Springer International Publishing AG.
PY - 2017
Y1 - 2017
N2 - While the Internet of things (IoT) promises to improve areas such as energy efficiency, health care, and transportation, it is highly vulnerable to cyberattacks. In particular, distributed denial-of-service (DDoS) attacks overload the bandwidth of a server. But many IoT devices form part of cyber-physical systems (CPS). Therefore, they can be used to launch “physical” denial-of-service attacks (PDoS) in which IoT devices overflow the “physical bandwidth” of a CPS. In this paper, we quantify the population-based risk to a group of IoT devices targeted by malware for a PDoS attack. In order to model the recruitment of bots, we develop a “Poisson signaling game,” a signaling game with an unknown number of receivers, which have varying abilities to detect deception. Then we use a version of this game to analyze two mechanisms (legal and economic) to deter botnet recruitment. Equilibrium results indicate that (1) defenders can bound botnet activity, and (2) legislating a minimum level of security has only a limited effect, while incentivizing active defense can decrease botnet activity arbitrarily. This work provides a quantitative foundation for proactive PDoS defense.
AB - While the Internet of things (IoT) promises to improve areas such as energy efficiency, health care, and transportation, it is highly vulnerable to cyberattacks. In particular, distributed denial-of-service (DDoS) attacks overload the bandwidth of a server. But many IoT devices form part of cyber-physical systems (CPS). Therefore, they can be used to launch “physical” denial-of-service attacks (PDoS) in which IoT devices overflow the “physical bandwidth” of a CPS. In this paper, we quantify the population-based risk to a group of IoT devices targeted by malware for a PDoS attack. In order to model the recruitment of bots, we develop a “Poisson signaling game,” a signaling game with an unknown number of receivers, which have varying abilities to detect deception. Then we use a version of this game to analyze two mechanisms (legal and economic) to deter botnet recruitment. Equilibrium results indicate that (1) defenders can bound botnet activity, and (2) legislating a minimum level of security has only a limited effect, while incentivizing active defense can decrease botnet activity arbitrarily. This work provides a quantitative foundation for proactive PDoS defense.
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U2 - 10.1007/978-3-319-68711-7_18
DO - 10.1007/978-3-319-68711-7_18
M3 - Conference contribution
AN - SCOPUS:85032860002
SN - 9783319687100
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 336
EP - 356
BT - Decision and Game Theory for Security - 8th International Conference, GameSec 2017, Proceedings
A2 - Kiekintveld, Christopher
A2 - Schauer, Stefan
A2 - An, Bo
A2 - Rass, Stefan
A2 - Fang, Fei
PB - Springer Verlag
T2 - 8th International Conference on Decision and Game Theory for Security, GameSec 2017
Y2 - 23 October 2017 through 25 October 2017
ER -