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Modeling and Evaluating the Impact o...

Lu, Zhuo.

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Modeling and Evaluating the Impact of Denial-of-Service Attacks in Emerging Wireless and Mobile Applications.

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Modeling and Evaluating the Impact of Denial-of-Service Attacks in Emerging Wireless and Mobile Applications./
作者:	Lu, Zhuo.
面頁冊數:	154 p.
附註:	Source: Dissertation Abstracts International, Volume: 75-03(E), Section: B.
Contained By:	Dissertation Abstracts International75-03B(E).
標題:	Engineering, Computer. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3575788
ISBN:	9781303547690

Modeling and Evaluating the Impact of Denial-of-Service Attacks in Emerging Wireless and Mobile Applications.
Lu, Zhuo.

Modeling and Evaluating the Impact of Denial-of-Service Attacks in Emerging Wireless and Mobile Applications. - 154 p.

Source: Dissertation Abstracts International, Volume: 75-03(E), Section: B.

Thesis (Ph.D.)--North Carolina State University, 2013.

The proliferation of wireless networks has brought significant change to people's daily life, such as WiFi and cellular networks. It further introduces new applications and services, including smart grid systems and emerging mobile services. However, due to the shared nature of wireless channels, these emerging applications are vulnerable to denial-of-service attacks, which come with various intents, from selfish sharing of channel resources to disrupting the communication among other users. A direct consequence of such attacks is performance degradation or even denial-of-service in the network. Moreover, they can lead to potentially devastating system failures, such as in the smart grid where physical control is all based on successful message delivery in the network. As a result, it is critical to understand the impact of denial-of-service attacks in emerging wireless applications.

ISBN: 9781303547690Subjects--Topical Terms:

1669061
Engineering, Computer.

Modeling and Evaluating the Impact of Denial-of-Service Attacks in Emerging Wireless and Mobile Applications.
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245 1 0 $a Modeling and Evaluating the Impact of Denial-of-Service Attacks in Emerging Wireless and Mobile Applications.
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500 $a Source: Dissertation Abstracts International, Volume: 75-03(E), Section: B.
500 $a Adviser: Wenye Wang.
502 $a Thesis (Ph.D.)--North Carolina State University, 2013.
520 $a The proliferation of wireless networks has brought significant change to people's daily life, such as WiFi and cellular networks. It further introduces new applications and services, including smart grid systems and emerging mobile services. However, due to the shared nature of wireless channels, these emerging applications are vulnerable to denial-of-service attacks, which come with various intents, from selfish sharing of channel resources to disrupting the communication among other users. A direct consequence of such attacks is performance degradation or even denial-of-service in the network. Moreover, they can lead to potentially devastating system failures, such as in the smart grid where physical control is all based on successful message delivery in the network. As a result, it is critical to understand the impact of denial-of-service attacks in emerging wireless applications.
520 $a In this dissertation, we aim at understanding the impact of denial-of-service attacks against emerging wireless applications. Because it is not practical to provide a unified framework to study denial-of-service attacks in all applications with distinct objectives and requirements, we adopt an application-specific methodology to model and evaluate denial-of-service attacks. We focus on three emerging applications: multi-modal CSMA/CA networks, time-critical networks for the smart grid, and smart phone applications.
520 $a In particular, we first study the multi-modal CSMA/CA networks that provide configurable MAC-layer parameters for wireless nodes to support multiple modality. Such configurability, however, induces a selfish behavior: a node deliberately reduces its MAC-layer backoff time to gain unfair access to the channel, which is called backoff misbehavior. We define a new performance metric to quantify the benefits of backoff misbehavior and show the impacts of a wide range of backoff misbehaving nodes on the network performance. Second, we study jamming attacks that can cause severe network problems by broadcasting radio interference in time-critical wireless networks for the smart grid. We analyze the jamming impact on time-critical message delivery, and implement a detector to accurately identify attacks. In addition, we propose a scheme to minimize the delay of time-critical message delivery under jamming attacks in smart grid applications. Finally, we investigate the propagation and impact of a mobile botnet, a collection of compromised smart phones able to perform coordinated attacks against mobile network infrastructures. The work in this dissertation advances our understanding of network vulnerabilities associated with emerging wireless networks, and offers instrumental guidance into the security design for future wireless and mobile applications.
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