Optimal response to attacks on the open science grid

Altunay, Mine; Leyffer, Sven; Linderoth, Jeff; Xie, Zhen

doi:10.1016/j.comnet.2010.07.012

Cited by 18 publications

(22 citation statements)

References 13 publications

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“…5) Cloud-computing-heterogeneity through cluster sizes: In cluster (or grid, or volunteer) computing [17], each cluster of CPUs in the cloud constitutes a type. Any two computers in the same cluster can communicate at faster rates than those in different clusters.…”

Section: Motivation Of the Models And Instantiationsmentioning

confidence: 99%

“…We can motivate heterogeneous epidemics in various ways: 1) Proximity-based spread, where locality causes heterogeneity; 2) Software/protocol diversity [11]- [13], which has even been envisioned as a defense mechanism against future threats [11]; 3) IP space diversity, e.g., worms that use the IP masks of specific Autonomous Systems (AS) to increase their yield [14]; 4) Differing clique sizes, especially for epidemics for which there is an underlying social network graph [3], [15]; 5) Behavioral patterns, specifically how much risky behaviour every agent engages in [16]; 6) Clusters in cloud computing [17]; 7) Technology adoption, belief-formation over social media, and health care [18]- [22].…”

Section: Introductionmentioning

confidence: 99%

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Optimal Patching in Clustered Malware Epidemics

Eshghi

Khouzani

Sarkar

et al. 2016

IEEE/ACM Trans. Networking

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Studies on the propagation of malware in mobile networks have revealed that the spread of malware can be highly inhomogeneous. Platform diversity, contact list utilization by the malware, clustering in the network structure, etc. can also lead to differing spreading rates. In this paper, a general formal framework is proposed for leveraging such heterogeneity to derive optimal patching policies that attain the minimum aggregate cost due to the spread of malware and the surcharge of patching. Using Pontryagin's Maximum Principle for a stratified epidemic model, it is analytically proven that in the mean-field deterministic regime, optimal patch disseminations are simple single-threshold policies. Through numerical simulations, the behavior of optimal patching policies is investigated in sample topologies and their advantages are demonstrated.

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Section: Motivation Of the Models And Instantiationsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Optimal Patching in Clustered Malware Epidemics

Eshghi

Khouzani

Sarkar

et al. 2016

IEEE/ACM Trans. Networking

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show abstract

“…The scale and scope of the diverse, and autonomous sites and use groups and the nature of the partnerships to supply the internationally integrated system for many of the science collaborations means that any banning or removal activities have wide impact. The actions taken to mitigate and respond to threats and incidents benefit from deep attention to the context and risks in the endto-end eco-system [31].…”

Section: Operationsmentioning

confidence: 99%

A Science Driven Production Cyberinfrastructure—the Open Science Grid

et al. 2010

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This article describes the Open Science Grid, a large distributed computational infrastructure in the United States which supports many different high-throughput scientific applications, and partners (federates) with other infrastructures nationally and internationally to form multi-domain integrated distributed systems for science. The Open Science Grid consortium not only provides services and software to an increasingly diverse set of scientific communities, but also fosters a collaborative team of practitioners and researchers who use, support and advance the state of the art M. Altunay · T. Levshina · R. Pordes (B) · C. Sehgal in large-scale distributed computing. The scale of the infrastructure can be expressed by the daily throughput of around seven hundred thousand jobs, just under a million hours of computing, a million file transfers, and half a petabyte of data movement. In this paper we introduce and reflect on some of the OSG capabilities, usage and activities.

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“…The list of these predetermined destinations can be further manipulated by a cyber-attacker to propagate the cyber-attack to other PMUs. The propagation of the cyber-attacks in shared communication networks has been also studied in [8]- [13]. Furthermore, it has been reported that the communication network shows poor network security and insufficient software security [14].…”

Section: Introductionmentioning

confidence: 99%

“…The authors of [13] have formulated an optimization model to avoid propagation of the cyber-attacks in open-science computer network where collaboration and communication exist among network sites. The optimization model is a mixed integer linear programming problem, which determines the sites to be disconnected from the network to maximize the number of users connected to the network resources.…”

Section: Introductionmentioning

confidence: 99%

A Probabilistic Risk Mitigation Model for Cyber-Attacks to PMU Networks

Mousavian

Valenzuela

Wang

2015

IEEE Trans. Power Syst.

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The power grid is becoming more dependent on information and communication technologies. Complex networks of advanced sensors such as phasor measurement units (PMUs) are used to collect real time data to improve the observability of the power system. Recent studies have shown that the power grid has significant cyber vulnerabilities which could increase when PMUs are used extensively. Therefore, recognizing and responding to vulnerabilities are critical to the security of the power grid. This paper proposes a risk mitigation model for optimal response to cyber-attacks to PMU networks. We model the optimal response action as a mixed integer linear programming (MILP) problem to prevent propagation of the cyber-attacks and maintain the observability of the power system.Index Terms-Cyber-attack, cyber-security, networks, observability, phasor measurement units.

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Optimal response to attacks on the open science grid

Cited by 18 publications

References 13 publications

Optimal Patching in Clustered Malware Epidemics

Optimal Patching in Clustered Malware Epidemics

A Science Driven Production Cyberinfrastructure—the Open Science Grid

A Probabilistic Risk Mitigation Model for Cyber-Attacks to PMU Networks

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