A Recent Survey on DDoS Attacks and Defense Mechanisms

Srivastava, Akshay; Gupta, Brij B.; Tyagi, A.K.; Sharma, Anupama; Mishra, Anupama

doi:10.1007/978-3-642-24037-9_57

Cited by 67 publications

(30 citation statements)

References 8 publications

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“…Attacks on CIDSs can be classified into internal and external attacks based on the scope of the attackers. In an external attack, the adversary may try to detect the presence of a CIDS, launch evasion attacks, or attack specific components of the IDS directly, for example by degrading its service availability via a Distributed Denial of Service (DDoS) attack [Srivastava et al 2011]. Internal attacks refer to malicious behavior originated from within the monitored network.…”

Section: Attacks On Cidsmentioning

confidence: 99%

Taxonomy and Survey of Collaborative Intrusion Detection

et al. 2015

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The dependency of our society on networked computers has become frightening: In the economy, all-digital networks have turned from facilitators to drivers; as cyber-physical systems are coming of age, computer networks are now becoming the central nervous systems of our physical world-even of highly critical infrastructures such as the power grid. At the same time, the 24/7 availability and correct functioning of networked computers has become much more threatened: The number of sophisticated and highly tailored attacks on IT systems has significantly increased. Intrusion Detection Systems (IDSs) are a key component of the corresponding defense measures; they have been extensively studied and utilized in the past. Since conventional IDSs are not scalable to big company networks and beyond, nor to massively parallel attacks, Collaborative IDSs (CIDSs) have emerged. They consist of several monitoring components that collect and exchange data. Depending on the specific CIDS architecture, central or distributed analysis components mine the gathered data to identify attacks. Resulting alerts are correlated among multiple monitors in order to create a holistic view of the network monitored. This article first determines relevant requirements for CIDSs; it then differentiates distinct building blocks as a basis for introducing a CIDS design space and for discussing it with respect to requirements. Based on this design space, attacks that evade CIDSs and attacks on the availability of the CIDSs themselves are discussed. The entire framework of requirements, building blocks, and attacks as introduced is then used for a comprehensive analysis of the state of the art in collaborative intrusion detection, including a detailed survey and comparison of specific CIDS approaches.

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Section: Attacks On Cidsmentioning

confidence: 99%

Taxonomy and Survey of Collaborative Intrusion Detection

et al. 2015

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“…Authors of [1] have classified DDoS attacks in two categories as flooding and logical (software) attacks. In flooding attacks, they have highlighted SYN flooding, ICMP attack, UDP flooding and in logical attack they have identified ping of death, teardrop attack, and land attack.…”

Section: Literature Reviewmentioning

confidence: 99%

DoS/DDoS Detection for E-Healthcare in Internet of Things

Sami¹,

Ahmad²,

Asif³

et al. 2018

ijacsa

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Abstract-Internet of Things (IoT) has emerged as a new horizon in communication age. IoT has provided platform to various emerging technologies and applications for growth. EHealth services have also been integrated and greatly benefitted from IoT. Due to the increased use of computer technology, computer networks have faced serious security challenges and IoT is also facing the same security threats. As IoT has provided platform to other fields, like E-Health, these services are also prone to such threats. Denial of Service (DoS) and Distributed Denial of Service (DDoS) attacks on E-Health servers in IoT would endanger real-time monitoring of patients and also overall reliability of the E-Health services. In this paper, existing solutions to DoS/DDoS attacks in IoT have been reviewed and a reliable solution is presented for securing the servers against these attacks.

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“…The DDoS attacks can be launched from multiple environments, likefromsome specific service,virtual machine, some node, some cluster or in the whole cloud environment.In this article we present different DDoS attack detection and prevention techniques at different levels [26].…”

Section: Fig1: Ddos Attackmentioning

confidence: 99%

A Review of Techniques to Detect and Prevent Distributed Denial of Service (DDoS) Attack in Cloud Computing Environment

Sattar¹,

Shahid²,

Abbas³

2015

IJCA

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Cloud computing has become one of the most demanding services over the internet. It has gained remarkable fame for past few years.But it is under the severe threats of internet security. One of the severe threats is Distributed Denial of Service (DDoS). DDoS occurs when a huge amount of packets are sent to a server from various computers. Botnet is one of the major causes that launch DDoS attack. Botnet is actually a network of bots or zombie computers that are under the control of attacker. Several techniques are available in the literature that provides solution to avoid DDoS attack.A survey on DDoS detection and prevention techniques and their comparative analysishave been done in this paper.

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A Recent Survey on DDoS Attacks and Defense Mechanisms

Cited by 67 publications

References 8 publications

Taxonomy and Survey of Collaborative Intrusion Detection

Taxonomy and Survey of Collaborative Intrusion Detection

DoS/DDoS Detection for E-Healthcare in Internet of Things

A Review of Techniques to Detect and Prevent Distributed Denial of Service (DDoS) Attack in Cloud Computing Environment

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