Development of an indicator to distinguish DDoS attacks from other anomalous events

Piggott, Paige; Carter, Camille; Patterson, Wayne; Gutiérrez, Fredy; Mujica, Sergio; Rojas, Esteban; Valenzuela, Cristhofer

doi:10.1109/secon.2013.6567393

Cited by 1 publication

(3 citation statements)

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“…The paper considers client puzzle protocol, ingress filtering, intrusion detection system and threshold value based systems' features and limitations to build its own system of detection of flooding DDOS attacks in cloud. The authors in [21] [26], [33], which includes perception layer, transportation layer and application layer. This has some contrast with respect to traditional networks especially in case of security domain.…”

Section: Review Studymentioning

confidence: 99%

“…Detection of such scenario is a problem to be solved in this research work. This must be done by a numerically stable algorithm so that anomaly detection [21] threshold is correctly identified for detection of adversity points during such slow HTTP based DDOS attacks in cloud environment.…”

Section: Problem Statementmentioning

confidence: 99%

“…It leads to degrade network service to cloud users or entirely make it unusable during the time it is active. Traffic from unknown/ghost referral [9] Spoofing type attacks It leads to failure to detect IP Spoofing [21].…”

Section: Mean Time Spent Between1 Sec To 2 Secsmentioning

confidence: 99%

See 2 more Smart Citations

Slow flooding attack detection in cloud using change point detection approach

Singh¹,

Panda²,

Samra³

2018

IJET

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Cloud computing is one of the high-demand services and prone to numerous types of attacks due to its Internet based backbone. Flooding based attack is one such type of attack over the cloud that exhausts the numerous resources and services of an individual or an enterprise by way of sending useless huge traffic. The nature of this traffic may be of slow or fast type. Flooding attacks are caused by way of sending massive volume of packets of TCP, UDP, ICMP traffic and HTTP Posts. The legitimate volume of traffic is suppressed and lost in traffic flooding traffics. Early detection of such attacks helps in minimization of the unauthorized utilization of resources on the target machine. Various inbuilt load balancing and scalability options to absorb flooding attacks are in use by cloud service providers up to ample extent still to maintain QoS at the same time by cloud service providers is a challenge. In this proposed technique. Change Point detection approach is proposed here to detect flooding DDOS attacks in cloud which are based on the continuous variant pattern of voluminous (flooding) traffic and is calculated by using various traffic data based metrics that are primary and computed in nature. Golden ration is used to compute the threshold and this threshold is further used along with the computed metric values of normal and malicious traffic for flooding attack detection. Traffic of websites is observed by using remote java script.

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Section: Review Studymentioning

confidence: 99%

Section: Problem Statementmentioning

confidence: 99%