A composable approach to design of newer techniques for large-scale denial-of-service attack attribution

Muthuprasanna, M.

doi:10.31274/etd-180810-172

Cited by 3 publications

(2 citation statements)

References 91 publications

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“…A victim of a nonrecoverable attack cannot automatically recover after the attack is stopped, but requires some human intervention. For example, an attack that causes the victim machine to crash, freeze or re-boot would be classified as a non-recoverable attack, as manual initialization might be required [16].…”

Section: Disruptive Attacksmentioning

confidence: 99%

Distributed denial of service attacks and detection mechanisms

Rafsanjani

Kazeminejad

2015

JCM

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Distributed Denial of Service (DDoS) attack is a coordinated effort between several machines to attack one or multiple target systems. Indeed, the attack is through imposing additional burden on system resources or flood computation and communication resources, the server services for legitimate users, are unavailable. In general, if we have categorized security into three areas of confidentiality, integrity and availability, distributed denial of service attacks threaten a third option. Since the distributed denial of service attacks caused by improper operation of information system and its users from accessing the services excluded and also to maintain vital system resources, such attacks are detected immediately. Hence, in this paper, we investigate such attacks and some of their detection mechanisms. In this paper, initially introduced such attacks, then are presented the various categories of these attacks, afterwards, several methods have been proposed to detect distributed denial of service attacks. Finally, these methods are compared and the advantages and disadvantages of them are briefly mentioned.

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Section: Disruptive Attacksmentioning

confidence: 99%

Distributed denial of service attacks and detection mechanisms

Rafsanjani

Kazeminejad

2015

JCM

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“…In severe cases, a website could shut operations for extended periods of time. DoS attacks are used to strategically target e‐commerce businesses, financial sectors, transportation departments, and other web‐based business operations that utilize physical platforms such as wireless systems, local area networks (LANs) and the Internet [Muthusrinivasan, ]. Such attacks can also be coordinated from multiple geographically dispersed locations and are known as distributed DoS (DDoS) attacks [Huang, ].…”

Section: Literature Reviewmentioning

confidence: 99%

Modeling the Ripple Effects of IT‐Based Incidents on Interdependent Economic Systems

Ali

Santos

2014

Systems Engineering

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The information technology (IT) sector is one of the most critically utilized infrastructures within the U.S. economic system. The IT sector is vulnerable to man-made attacks and it is challenging to assess the consequences of disruptions to the production and delivery of essential IT services to other economic systems. In this paper, we developed a dynamic model based on economic input-output analysis to assess time-varying disruptions on the IT sector over multiple periods. The model is applied in an ex post analysis of an actual denial-of-service (DoS) attack scenario on the IT infrastructure to estimate the consequences propagated to interdependent economic systems. The model uses Bureau of Economic Analysis data to simulate the effects of IT-based incidents and subsequently identify the critically affected economic sectors. Key results of the case study include assessments of ripple effects to vulnerable sectors in the form of inoperability and economic loss measures. An investigation of the DoS attack in year 2000 using the proposed dynamic model revealed significant losses that are consistent with the magnitude of losses from previous studies. Furthermore, the model is capable of depicting the breakdown of losses across various economic sectors, which is a significant improvement relative to previously published results. This research also extends into a multiyear trend analysis (1999)(2000)(2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)) to aid in developing policies for reducing the effects of IT risks across the interdependent sectors of the U

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Defending against DDoS Attacks under IP Spoofing Using Image Processing Approach

Kim

Jung

2016

IEICE Trans. Commun.

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A composable approach to design of newer techniques for large-scale denial-of-service attack attribution

Cited by 3 publications

References 91 publications

Distributed denial of service attacks and detection mechanisms

Distributed denial of service attacks and detection mechanisms

Modeling the Ripple Effects of IT‐Based Incidents on Interdependent Economic Systems

Defending against DDoS Attacks under IP Spoofing Using Image Processing Approach

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