Creating complex congestion patterns via multi-objective optimal freeway traffic control with application to cyber-security

Reilly, Jack; Martin, Sébastien; Payer, Mathias; Bayen, Alexandre M.

doi:10.1016/j.trb.2016.05.017

Cited by 68 publications

(26 citation statements)

References 37 publications

(56 reference statements)

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“…Existing works on ITS security include case studies on traffic control wireless networks ( Ghena et al, 2014;Cerrudo, 2015 ), connected and autonomous cars ( Evtimov et al, 2017;Thing and Wu, 2016;Chen et al, 2018;Checkoway et al, 2011;Hubaux et al, 2004;Wan et al, 2016 ), ride sharing applications ( Yuan et al, 2016 ) and sensors in freeway traffic control systems ( Reilly et al, 2016;1755 ). Works ( Ghena et al, 2014;Cerrudo, 2015 ) have demonstrated that networked traffic systems are vulnerable to a variety of cyber attacks.…”

Section: Motivationmentioning

confidence: 99%

Security analysis for fixed-time traffic control systems

Lopez

Jin

Faruque

2020

Transportation Research Part B: Methodological

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Wireless communication is being used as an enabling technology with traditional fixed traffic control systems in this transitional era toward Intelligent Transportation Systems (ITS). Unfortunately, major security concerns have arisen with respect to ever-increasing complexity and interconnectivity, and a noticeable lack of attention for security in these systems. Addressing concerns is a colossal challenge as it requires thorough development and formal analysis of a system model with respect to security. To tackle this challenge, we present a novel formal attack modeling and impact analysis methodology based on the Link Queue Model (LQM) of traffic flow inside a double ring road network, which is equivalent to a grid network with homogeneous links. We develop attack models as functions of tampered traffic control settings (e.g., green time ratios, cycle length, retaining ratios) with outputs equivalent to mobility impacts on the traffic network (e.g., time until system reaches state convergence, asymptotic average network flow). Further, for a given attack model, we define and identify vulnerable states: states that are critical to protect because they lead to negative impacts under the given attack model. Using our methodology we found that for certain vulnerable states, after only a few cycles of tampered control settings an attacker could cause a real impact of 1.5x speed-up in gridlock state convergence or 37%-99% drop in the asymptotic average flow rate. These results imply potentially drastic financial costs for cities and all involved drivers if similar attacks were performed on a real traffic control system.

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Section: Motivationmentioning

confidence: 99%

Security analysis for fixed-time traffic control systems

Lopez

Jin

Faruque

2020

Transportation Research Part B: Methodological

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“…For example, Reilly et al. () evaluated the impact of cyberattacks on freeway traffic using the optimal control and multiobjective optimization strategies; Amoozadeh et al. () investigated the effects of security attacks on the connected vehicle platoon by using VEhicular NeTwork Open Simulator (VENTOS) framework; and Dadras et al.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Although much research focuses on cyberattack itself, an equally important aspect is to study the impact of malicious attacks on connected vehicles, particularly the behaviors of vehicles under cyberattack during driving. For example, Reilly et al (2016) evaluated the impact of cyberattacks on freeway traffic using the optimal control and multiobjective optimization strategies; investigated the effects of security attacks on the connected vehicle platoon by using VEhicular NeTwork Open Simulator (VENTOS) framework; and Dadras et al (2015) demonstrated that an attacker can cause the platoon to be unstable and even serious injury or death. Furthermore, Amir et al (2017) considered the stability of a platoon under a jamming attack on realistic wireless channel; and Wang et al (2018) investigated the linear and nonlinear stability of traffic flow with different cyberattacks.…”

Section: Denial Of Servicementioning

confidence: 99%

Spreading Patterns of Malicious Information on Single‐Lane Platooned Traffic in a Connected Environment

Wang

et al. 2018

Computer aided Civil Eng

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The connected vehicle can be easily attacked by cyber threats due to its communication through the wireless network in an open‐access environment. But very few studies have paid attention to the spreading of malicious information such as denial of service, message delay/replay, and eavesdropping generated by cyberattacks. To this end, this article introduces an analytical model, named vehicular malicious information propagation (VMIP), which integrates a classical epidemic model through two‐layer system structure, in which the upper layer describes the malicious information spreading and the lower describes the traffic flow dynamics. The proposed VMIP model is designated for platooned (one‐lane, particularly) traffic. Numerical experiments show the proposed model can efficiently describe the interactions between traffic dynamics and malicious information spreading; and the information propagation highly depends on traffic flow patterns. This article is expected to contribute to a better understanding of the impacts of cyberattacks on traffic and lays a foundation for future development of control strategies on mitigating the disastrous effects of cyberattacks.

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“…Physical attacks are direct attacks on the hardware. These attacks include clipping wires, theft and replacement of sensors or actuators [19]. Ghena et al [18] describe methods of attacking the hardware infrastructure of a currently deployed traffic signal system in Michigan, USA.…”

Section: Introductionmentioning

confidence: 99%

Noticeability Versus Impact in Traffic Signal Tampering

Thodi¹,

Mulumba²,

Jabari

2020

IEEE Access

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This paper investigates the vulnerability of urban traffic networks to cyber attacks on traffic lights. We model traffic signal tampering as a bi-objective optimization problem that simultaneously seeks to reduce vehicular throughput in the network over time (maximize impact) while introducing minimal changes to network signal timings (minimize noticeability). We represent the Spatio-temporal traffic dynamics as a static network flow problem on a time-expanded graph. This allows us to reduce the (non-convex) attack problem to a tractable form, which can be solved using traditional techniques used to solve linear network programming problems. We show that minor but objective adjustments in the signal timings over time can severely impact traffic conditions at the network level. We investigate network vulnerability by examining the concavity of the Pareto-optimal frontier obtained by solving the bi-objective attack problem. Numerical experiments are carried to illustrate the types of insights that can be extracted from the Pareto-optimal frontier. For instance, our experiments suggest that the vulnerability of a traffic network to signal tampering is independent of the demand levels. INDEX TERMS Network vulnerability, signal tampering, traffic flow dynamics, urban traffic networks, adversarial attacks, cybersecurity.

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Creating complex congestion patterns via multi-objective optimal freeway traffic control with application to cyber-security

Cited by 68 publications

References 37 publications

Security analysis for fixed-time traffic control systems

Security analysis for fixed-time traffic control systems

Spreading Patterns of Malicious Information on Single‐Lane Platooned Traffic in a Connected Environment

Noticeability Versus Impact in Traffic Signal Tampering

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