Analyzing well-known countermeasures against distributed denial of service attacks

Beitollahi, Hakem

doi:10.1016/j.comcom.2012.04.008

Cited by 105 publications

(77 citation statements)

References 55 publications

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“…Attack detection and mitigation at distributed ends can be the most promising strategy against DDoS attacks [24]. As mentioned before, source-end is a better place for both filtering and rate-limiting the attacks.…”

Section: Ddos Detection and Mitigationmentioning

confidence: 99%

“…Numerous research papers have been published which review DDoS attacks and propose their detection & mitigation techniques. We find some comprehensive papers & articles to enrich our literature review on the topic [1][2][3][4][5][11][12][13][14][15][16][17][18][19][20][21][22][23][24][25][26][27][28][29]. Some reviewed methods have also been referred in tables of first author's previous work [30]; however this paper contains major changes as compared to the previous study.…”

Section: Ddos Detection and Mitigationmentioning

confidence: 99%

“…However, the filtering can also be based on some other criteria such as port number, protocol type etc. This method is a source-end, proactive technique capable of protecting against both direct and reflector types of DDoS attacks [24].…”

Section: Some Common Countermeasures Against Ddos Attacksmentioning

confidence: 99%

“…As far as the countermeasures against DDoS are concerned, they are usually categorized in three types of techniques mentioned below [24]:…”

Section: Ddos Detection and Mitigationmentioning

confidence: 99%

“…The above mentioned defense mechanisms can be applied by the control centers that may be located at different points [24] such as:…”

Section: Ddos Detection and Mitigationmentioning

confidence: 99%

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A Survey on DDoS Attack and Defense Strategies: From Traditional Schemes to Current Techniques

Aamir

Zaidi

2013

IIS

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Distributed Denial of Service (DDoS) attacks exhaust victim's bandwidth or services. Traditional architecture of Internet is vulnerable to DDoS attacks and an ongoing cycle of attack & defense is observed. A recent attack report of year 2013 -'Quarter 1' from Prolexic Technologies identifies that 1.75 percent increase in total number of DDoS attacks has been recorded as compared to similar attacks of previous year's last quarter. In this paper, different types and techniques of DDoS attacks and their countermeasures are surveyed. The significance of this paper is the coverage of many aspects of countering DDoS attacks including new research on the topic. We survey different papers describing methods of defense against DDoS attacks based on entropy variations, traffic anomaly parameters, neural networks, device level defense, botnet flux identifications, application layer DDoS defense and countermeasures in wireless networks, CCN & cloud computing environments. We also discuss some traditional methods of defense such as traceback and packet filtering techniques, so that readers can identify major differences between traditional and current techniques of defense against DDoS attacks. We identify that application layer DDoS attacks possess the ability to produce greater impact on the victim as they are driven by legitimate-like traffic, making it quite difficult to identify and distinguish from legitimate requests. The need of improved defense against such attacks is therefore more demanding in research. The study conducted in this paper can be helpful for readers and researchers to recognize better techniques of defense in current times against DDoS attacks and contribute with more research on this topic in the light of future challenges identified in this paper.

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Section: Ddos Detection and Mitigationmentioning

confidence: 99%

Section: Ddos Detection and Mitigationmentioning

confidence: 99%

Section: Some Common Countermeasures Against Ddos Attacksmentioning

confidence: 99%

“…As far as the countermeasures against DDoS are concerned, they are usually categorized in three types of techniques mentioned below [24]:…”

Section: Ddos Detection and Mitigationmentioning

confidence: 99%

“…The above mentioned defense mechanisms can be applied by the control centers that may be located at different points [24] such as:…”

Section: Ddos Detection and Mitigationmentioning

confidence: 99%

See 3 more Smart Citations

A Survey on DDoS Attack and Defense Strategies: From Traditional Schemes to Current Techniques

Aamir

Zaidi

2013

IIS

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What matters for financial inclusions? Evidence from emerging economy

2021

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The major objective of this research is to examine the influence of cybercrimes on financial inclusion in a developing country. Furthermore, the study also tends to examine the role of cybersecurity in controlling the impact of cybercrimes on financial inclusion. Data were collected from the banking sector of Pakistan using a close‐ended questionnaire. Partial least square‐structural equation modelling (PLS‐SEM) technique was employed to analyse the data. The findings of the study confirm that strong cybersecurity reduces the consequences of cyber threats to financial inclusion. This study suggests that numerous external and internal factors lead to criminals for illegal activities in the banking sector. Therefore, it is obligatory for the banks to enhance their cybersecurity control, to minimize the occurrences of cyber‐attacks. The present study focuses on the banking sector, so its finding cannot be generalized in other sectors. Further in‐depth comparative studies in other sectors with different cultural settings will help to authenticate the research findings.

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Distributed flood attack detection mechanism using artificial neural network in wireless mesh networks

Khan

Shams

et al. 2015

Security Comm Networks

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Multi-hop wireless mesh networks (WMNs) are increasingly growing interest as a promising technology for high-speed network access. WMNs are integrated with other networks such as Internet, sensor networks, and cellular networks through gateways. Therefore gateways in WMNs are prone to various security threads and can be easily exploited by the attacker from any part of the Internet to launch a distributed flooding attack to compromise computer systems, affect the network performance, and destruct the services. Many approaches have been proposed by researchers in this regard but still more efforts are needed in terms of accuracy and efficiency. In this research paper, we will propose an artificial neural network-based technique for detection of distributed flooding attacks to things such as sensors or actuators in WMNs called the distributed flood attack detector. In our simulation, sample dataset used to train and test the artificial neural network is generated using NS-2 network simulator. Simulation results and real system implementation proved that the distributed flood attack detector can be used in a real network environment to detect the intermediate and severe distributed flood attacks with low-false positive and false-negative rates.

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Analyzing well-known countermeasures against distributed denial of service attacks

Cited by 105 publications

References 55 publications

A Survey on DDoS Attack and Defense Strategies: From Traditional Schemes to Current Techniques

A Survey on DDoS Attack and Defense Strategies: From Traditional Schemes to Current Techniques

What matters for financial inclusions? Evidence from emerging economy

Distributed flood attack detection mechanism using artificial neural network in wireless mesh networks

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