A service governance and isolation based approach to mitigate internal collateral damages in cloud caused by DDoS attack

Verma, Priyanka; Tapaswi, Shashikala; Godfrey, W. Wilfred

doi:10.1007/s11276-021-02604-3

Cited by 8 publications

(4 citation statements)

References 35 publications

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Section: Resource and Service-oriented Collateral Damagesmentioning

confidence: 99%

“…Existing methods in the literature are not sufficiently effective at handling internal collateral damages. In order to provide resource governance and separation between co‐located services and improve service performance for good users, the author 69 thus proposes a novel service containerization technique. The outcomes show that by improving service performance, the suggested technique can lessen the side effects of DDoS attacks on co‐located services like SSH and disc I/O. Container separation : Kumar et al 70 proposed an approach that aims to mitigate DDoS attacks by separating incoming requests at the container level and applying scale‐inside‐out for attack requests within a separate container.…”

Section: Defense Mechanism For Indirect Attackmentioning

confidence: 99%

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Uncovering collateral damages and advanced defense strategies in cloud environments against DDoS attacks: A comprehensive review

Verma,

Bharot,

Breslin

et al. 2024

Trans Emerging Tel Tech

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Cloud computing (CC) offers on‐demand computing and resources to users, and organizations, and is also used in many human‐centric intelligent systems. Attacks in cloud networks cause huge damage to service providers and users. Distributed Denial of Service (DDoS) is one of them that greatly impacts the cloud network. The unavailability of resources is the major concern pertaining to cloud service and resources. Apart from the direct targets of a DDoS attack, there are also indirect effects on non‐targets within a cloud network. These effects on the non‐target stakeholders of the cloud are called collateral damages. However, this area of research is not explored much by researchers. Thus, the defense methods pertaining to direct and indirect effects need to be explored. This article aims to describe the consequences of DDoS attacks and the solutions available in the cloud network. The novelty of this article lies in shedding light on the indirect impacts of DDoS in cloud networks and possible solution approaches. The article also provides a comparative analysis of the existing defense solution under different categories and available tools and datasets to evaluate the proposed solutions. The article also mentions the solution considerations and effective solution scenarios. The idea behind this article is to impart guidelines to the researchers, for developing efficient defense solutions against direct target and indirect target DDoS attacks. Moreover, the research shortcomings, pros–cons, and existing challenges are outlined, and directions for future research are mentioned.

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Section: Resource and Service-oriented Collateral Damagesmentioning

confidence: 99%

Section: Defense Mechanism For Indirect Attackmentioning

confidence: 99%

Uncovering collateral damages and advanced defense strategies in cloud environments against DDoS attacks: A comprehensive review

Verma,

Bharot,

Breslin

et al. 2024

Trans Emerging Tel Tech

Self Cite

View full text Add to dashboard Cite

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“…Hence, low-rate DDoS attacks are more difficult to identify rather than high-rate DDoS attacks. 19,20 Data sets representing legitimate traffic produced by IoT devices are necessary for the creation of an anomaly detection system. 21 Many machine learning 22 related models are presented to detect DDoS attacks in cloud computing.…”

Section: Introductionmentioning

confidence: 99%

“…This type of attack is termed a low‐rate DDoS attack like legitimate traffic. Hence, low‐rate DDoS attacks are more difficult to identify rather than high‐rate DDoS attacks 19,20 . Data sets representing legitimate traffic produced by IoT devices are necessary for the creation of an anomaly detection system 21 …”

Section: Introductionmentioning

confidence: 99%

DDoS attack detection in cloud using ensemble model tuned with optimal hyperparameter

Reddy,

Meera

2024

Adaptive Control & Signal

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SummaryDDoS attacks are a type of cloud incursion that lessen service degradation. DDoS attacks target the cloud network with invalid requests, rejecting legitimate requests. Such attacks disrupt the entire cloud architecture, thus it needs efficient detection methods to spot their presence. This study proposes a novel ensemble classification model for DDoS incursion detection. Pre‐processing, feature extraction, and attack detection are the three main components of the suggested intrusion detection system. Improved data imbalance processing is processed during pre‐processing. Features including HOS‐based features enhanced entropy‐based features, correlation features, and raw features are extracted from the pre‐processed data. The generated features are trained using an ensemble model, which integrates classifiers like SVM, RF, NN, LSTM, and DRN, during the attack detection phase. A new hybrid approach known as TUDMA optimally trains the model by setting the ideal weight because DRN provides the final detected outcome. By reducing errors, this ideal training will guarantee an improvement in detection results. The suggested hybrid optimization combines the two techniques, TDO and DMO. The accuracy of the methods FS‐WOA‐DNN, RBF‐PSO, SMA, BRO, SLO, and NMRA was 86.73%, 85.69%, 84.58%, 87.43%, 88.91%, and 89.78%, respectively, while the accuracy of the TUDMA was 95.34% in the 80th learning percentage. Finally, for many measurements, the suggested efficiency is superior to the traditional methods.

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Detection of Suspicious Activities at Hypervisor in Cloud Computing: A Brief Study

Anumukonda,

Yadav,

2024

Intelligent Systems Design and Applications

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A service governance and isolation based approach to mitigate internal collateral damages in cloud caused by DDoS attack

Cited by 8 publications

References 35 publications

Uncovering collateral damages and advanced defense strategies in cloud environments against DDoS attacks: A comprehensive review

Uncovering collateral damages and advanced defense strategies in cloud environments against DDoS attacks: A comprehensive review

DDoS attack detection in cloud using ensemble model tuned with optimal hyperparameter

Detection of Suspicious Activities at Hypervisor in Cloud Computing: A Brief Study

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