DDoS Attacks in Cloud Computing: Issues, Taxonomy, and Future Directions (1512.08187v2)

Abstract: Security issues related to the cloud computing are relevant to various stakeholders for an informed cloud adoption decision. Apart from data breaches, the cyber security research community is revisiting the attack space for cloud-specific solutions as these issues affect budget, resource management, and service quality. Distributed Denial of Service (DDoS) attack is one such serious attack in the cloud space. In this paper, we present developments related to DDoS attack mitigation solutions in the cloud. In particular, we present a comprehensive survey with a detailed insight into the characterization, prevention, detection, and mitigation mechanisms of these attacks. Additionally, we present a comprehensive solution taxonomy to classify DDoS attack solutions. We also provide a comprehensive discussion on important metrics to evaluate various solutions. This survey concludes that there is a strong requirement of solutions, which are designed keeping utility computing models in mind. Accurate auto-scaling decisions, multi-layer mitigation, and defense using profound resources in the cloud, are some of the key requirements of the desired solutions. In the end, we provide a definite guideline on effective solution building and detailed solution requirements to help the cyber security research community in designing defense mechanisms. To the best of our knowledge, this work is a novel attempt to identify the need of DDoS mitigation solutions involving multi-level information flow and effective resource management during the attack.

• The paper introduces a robust taxonomy classifying prevention, detection, and mitigation mechanisms for cloud-based DDoS attacks.
• It demonstrates the significant financial impact of DDoS attacks and stresses the need for cloud-native defenses like auto-scaling and SDN.
• Future directions include integrating machine learning for real-time detection and developing cost-effective, multi-layered defense strategies.

Overview of DDoS Attacks in Cloud Computing: Issues, Taxonomy, and Future Directions

The paper "DDoS Attacks in Cloud Computing: Issues, Taxonomy, and Future Directions" meticulously examines the nuances of Distributed Denial of Service (DDoS) attacks within the domain of cloud computing. The discussion is anchored in the critical need to bolster cloud infrastructures against the unique challenges posed by such attacks. Notably, the exploration of DDoS in this context is essential due to the intimate connections between cloud paradigms and economic models, thus interlinking service quality with financial sustainability.

Key Contributions

The paper offers a robust taxonomy that classifies DDoS mitigation solutions specific to cloud environments. The taxonomy is divided into three major domains: prevention, detection, and mitigation/recovery mechanisms. Through an extensive literature review, the authors outline the requirement for enhanced solutions that incorporate cloud-native features such as auto-scaling and virtualization into their defense mechanisms. This systematic categorization allows for a granular understanding of the state-of-the-art solutions and identifies existing gaps that necessitate further research.

Technical Insights

1. Security Paradigms: The paper foregrounds the challenges associated with traditional DDoS attacks and articulates new paradigms specifically for cloud environments. The focus is placed on the economic impact, introducing concepts like Economic Denial of Sustainability (EDoS) that are peculiar to the "pay-as-you-go" cloud models.
2. Taxonomy of Solutions:
   • Prevention Measures: Techniques emphasized include challenge-response protocols such as CAPTCHAs and crypto-puzzles, strategies for hidden servers/ports, restrictive access protocols, and resource caps to curtail economic losses.

• Detection Approaches: Solutions are driven by anomaly detection, source and spoof traceback, count-based filtering, and botcloud detection, all of which leverage traffic pattern analysis and machine learning.
• Mitigation Strategies: Highlighting the importance of resource scaling, victim migration, and software-defined networking (SDN), the paper proposes methodologies for minimizing downtime and ensuring service continuity during an attack.

Empirical Analysis

The paper is substantiated with empirical data, citing that over 20% of enterprises encounter DDoS attacks, with substantial financial implications averaging fees as steep as 66K USD/hour due to service disruptions and infrastructural scaling invoked to counter these attacks. These numeric estimates reinforce the critical need for collaborative solutions encompassing multiple infrastructure layers from application through to ISP levels.

Theoretical and Practical Implications

The work shapes a comprehensive lens for examining future directions in cyber-defense within cloud infrastructures. It postulates that solutions must transcend beyond traditional IT defenses by embedding cloud-specific resiliency attributes. The ongoing evolution of cloud infrastructures propels researchers to design automation that can preemptively scale resources or migrate services under threat. Moreover, utilizing SDNs can provide dynamic control over network traffic, offering granular monitoring capabilities for DDoS mitigation.

Future Outlook

The discourse on DDoS in cloud computing opens doors for prospective enhancements in solution design focusing on the integration of machine learning algorithms, real-time anomaly detection, and multi-layered defense architecture. Further investigative work is encouraged in optimizing performance while maintaining minimal false positives in detection mechanisms. Additionally, cost-efficient defensive strategies should be explored to accommodate smaller enterprises that rely heavily on cloud platforms.

Conclusion

In conclusion, the paper delivers a seminal framework, bringing forth analytical clarity on DDoS attacks specific to cloud environments. The taxonomy and subsequent discussions articulate a roadmap for addressing an array of technical and economic challenges intrinsic to cloud-based services. This comprehensive survey serves as both a reflective and prospective guide, aiming to fuel innovative research efforts that secure cloud infrastructures against the evolving landscape of cyber threats.