An Optimal Sensor Network for Intrusion Detection

Olteanu, Alina; Xiao, Yang; Wu, Kui; Du, Xiaojiang

doi:10.1109/icc.2009.5198738

Cited by 9 publications

(4 citation statements)

References 13 publications

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“…Our proposed algorithm (with 2-bit quantization) is essentially optimal in the Bayesian sense. 2 In the following results the optimal values of the window size are used and are obtained through exhaustive search. The efficient way to obtain T opt is out of the scope of this paper and will be pursued in the future.…”

Section: B Performance Evaluationmentioning

confidence: 99%

“…Sensor networks have been of great interest in recent years because of their various applications including environmental monitoring [1], battlefield surveillance [2], and system health management [3][4][5], etc. A sensor network may consist of a large number of geographically distributed sensor nodes, which enables monitoring the phenomena of interest on a potentially unprecedented scale and with high precision.…”

Section: Introductionmentioning

confidence: 99%

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Online Dynamic Event Region Detection Using Distributed Sensor Networks

Cheng

2014

IEEE Trans. Aerosp. Electron. Syst.

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Event region detection refers to the process of detecting regions with distinguishable characteristics in an environment, and it can find a broad range of applications from environmental monitoring to system health management. The problem of online dynamic event region detection is studied here. The spatiotemporal relationship of the evolving event regions is assumed and modeled by dynamic Markov random fields. Observations are collected from a network of sensors distributed in the field. To provide detection results at each time step, a distributed event region tracking algorithm is proposed. The system dynamics and information collected from neighbors are used to predict the underlying hypothesis at each sensor node and its local observation is used for update. Mean field approximation is adopted in the algorithm for tractability. The performance of the proposed algorithm is analyzed both theoretically and through simulations. By comparing with static event region detection algorithms and a centralized algorithm (with certain approximation), we demonstrate the effectiveness and efficiency of the proposed algorithm, especially its robustness in low signal-to-noise ratio (SNR) situations.

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Section: B Performance Evaluationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Online Dynamic Event Region Detection Using Distributed Sensor Networks

Cheng

2014

IEEE Trans. Aerosp. Electron. Syst.

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“…These small sensors, can work collaboratively in a distributed fashion to collect information more efficiently [1], [2], [3], [4]. Some of the diverse range of applications of sensor networks include monitoring [5], [6], intrusion detection [7] and surveillance [8]. One of the important applications of such networks is target tracking.…”

Section: Introductionmentioning

confidence: 99%

Maximum life span strategy for target tracking in mobile sensor networks

Mahboubi

Masoudimansour

Aghdam

et al. 2012

2012 American Control Conference (ACC)

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In this paper, an energy-efficient technique is proposed for tracking a target in a field using a network of mobile sensors while maximizing the life span of the network. The most important energy consumption sources in a mobile sensor network (MSN) are sensing, communication and movement of the sensors. In the proposed technique, first the field is divided into a grid of arbitrarily small cells. This grid is then used to obtain a graph with properly weighted edges. The weight assignment is done in such a way that it results in a close estimate of the maximum lifetime for the network. Finally, using a shortest path algorithm, an efficient route is found to transfer information from the target to destination.

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“…We focus on the scenario of one single network function that requires all the data packets of the flows to be processed before they leave the network. This is common for many network services related to security and analytics, such as Intrusion Detection Systems (IDSs) [4], [5], Intrusion Prevention Systems (IPSs) [6], Deep Packet Inspection (DPI) 1 , and network analytics/billing services. Each VNF instance is implemented at a virtual machine with limited resources and processing capacity.…”

Section: Introductionmentioning

confidence: 99%

Provably efficient algorithms for joint placement and allocation of virtual network functions

Sang

Gupta

et al. 2017

IEEE INFOCOM 2017 - IEEE Conference on Computer Communications

122

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Abstract-Network Function Virtualization (NFV) has the potential to significantly reduce the capital and operating expenses, shorten product release cycle, and improve service agility. In this paper, we focus on minimizing the total number of Virtual Network Function (VNF) instances to provide a specific service (possibly at different locations) to all the flows in a network. Certain network security and analytics applications may allow fractional processing of a flow at different nodes (corresponding to datacenters), giving an opportunity for greater optimization of resources. Through a reduction from the set cover problem, we show that this problem is NP-hard and cannot even be approximated within a factor of (1 − o(1)) ln m (where m is the number of flows) unless P=NP. Then, we design two simple greedy algorithms and prove that they achieve an approximation ratio of (1 − o(1)) ln m + 2, which is asymptotically optimal. For special cases where each node hosts multiple VNF instances (which is typically true in practice), we also show that our greedy algorithms have a constant approximation ratio. Further, for tree topologies we develop an optimal greedy algorithm by exploiting the inherent topological structure. Finally, we conduct extensive numerical experiments to evaluate the performance of our proposed algorithms in various scenarios.

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An Optimal Sensor Network for Intrusion Detection

Cited by 9 publications

References 13 publications

Online Dynamic Event Region Detection Using Distributed Sensor Networks

Online Dynamic Event Region Detection Using Distributed Sensor Networks

Maximum life span strategy for target tracking in mobile sensor networks

Provably efficient algorithms for joint placement and allocation of virtual network functions

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