Accountable MapReduce in cloud computing

Xiao, Zhifeng; Xiao, Yang

doi:10.1109/infcomw.2011.5928788

Cited by 35 publications

(19 citation statements)

References 78 publications

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“…Accountability in operating system was proposed and studied in [2,55]. Accountability for cloud computing was proposed and studied in [39,40,70,80]. Accountability for smart grids was proposed and studied in [71,72,73,74].…”

Section: Secure and Accountable Internetmentioning

confidence: 99%

“…The papers [33,34] use Emulab to study 4D future Internet. The papers [39][40] use Emulab to study MapReduce for cloud computing. The papers [41,42] use Emulab to study building global view with log files.…”

Section: Introductionmentioning

confidence: 99%

“…The papers [41,42] use Emulab to study building global view with log files. The papers [33][34][35][36][37][38][39][40][41][42][43][44][45] study security and attacks for ProtoGENI. The paper [46] provides a survey of authentication and access control for ProtoGENI.…”

Section: Introductionmentioning

confidence: 99%

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Security Issues in ProtoGENI

Shalini¹,

Xiao²,

Sun³

2016

EAI Endorsed Transactions on Industrial Networks and Intelligen

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Network security consists of primary concerns in future Internet development due to the ever increasing threats to current Internet. ProtoGENI is a federated testbed facility supporting slice-based experiments to manage, utilize, and monitor the resources for innovative network research. Security research in ProtoGENI is crucial because experiments conducted in manipulated or corruptted test environment can mislead about security mechanism's capabilities in a system. In this paper, existing ProtoGENI security mechanisms and functions are tested and analyzed through different experiments to find out the exploitable attacking loopholes. Experiments elaborate the existing functioning and security issues that can cause nonfunctional, semi non-functional or malfunctioned systems. Results indicate threats to ProtoGENI resources and run-time interactions. Cross-experiment communication in Emulab wireless nodes have the capability of assisting in verifying isolation between ProtoGENI slices. Host security is one of the security components, which can be enhanced by modifying default security settings including SSH port number and root login rights. Documentation of experiment environment, experiment design, results, and analysis including many observations is helpful to understand the basic functioning and security issues to improve the overall functioning and security of ProtoGENI.

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Section: Secure and Accountable Internetmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Security Issues in ProtoGENI

Shalini¹,

Xiao²,

Sun³

2016

EAI Endorsed Transactions on Industrial Networks and Intelligen

Self Cite

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“…Yongzhi Wang and his colleagues introduced the verifier role in the MapReduce computing model [10], which samples and re-computes the results passed the replication verification, to defend collusion attack. Z. Xiao et al used a set of trusted auditing nodes to record the results generated by various phases of MapReduce [20]. The cheating nodes can be located by re-computing the results.…”

Section: Related Workmentioning

confidence: 99%

VAWS: Constructing Trusted Open Computing System of MapReduce with Verified Participants

Ding

Wang

Wei

et al. 2014

IEICE Trans. Inf. & Syst.

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SUMMARYMapReduce is commonly used as a parallel massive data processing model. When deploying it as a service over the open systems, the computational integrity of the participants is becoming an important issue due to the untrustworthy workers. Current duplication-based solutions can effectively solve non-collusive attacks, yet most of them require a centralized worker to re-compute additional sampled tasks to defend collusive attacks, which makes the worker a bottleneck. In this paper, we try to explore a trusted worker scheduling framework, named VAWS, to detect collusive attackers and assure the integrity of data processing without extra re-computation. Based on the historical results of verification, we construct an Integrity Attestation Graph (IAG) in VAWS to identify malicious mappers and remove them from the framework. To further improve the efficiency of identification, a verification-couple selection method with the IAG guidance is introduced to detect the potential accomplices of the confirmed malicious worker. We have proven the effectiveness of our proposed method on the improvement of system performance in theoretical analysis. Intensive experiments show the accuracy of VAWS is over 97% and the overhead of computation is closed to the ideal value of 2 with the increasing of the number of map tasks in our scheme. key words: result verification, computational integrity, MapReduce, open system, integrity attestation graph

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“…Xiao et al [4] presented an accountable MapReduce platform which checks all working machines and detects malicious nodes in real time. By replaying the tasks executed by workers and matching output with the original results, auditors are able to generate verifiable evidence once inconsistency occurs.…”

Section: Related Workmentioning

confidence: 99%

Towards Trusted Services: Result Verification Schemes for MapReduce

Huang

Zhu

2012

2012 12th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (Ccgrid 2012)

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Abstract-Recent development in Internet-scale data applications and services, combined with the proliferation of cloud computing, has created a new computing model for data intensive computing best characterized by the MapReduce paradigm. The MapReduce computing paradigm, pioneered by Google in its Internet search application, is an architectural and programming model for efficiently processing massive amount of raw unstructured data. With the availability of the open source Hadoop tools, applications built based on the MapReduce computing model are rapidly growing.In this work, we focus on a unique security concern on the MapReduce architecture. Given the potential security risks from lazy or malicious servers involved in a MapReduce task, we design efficient and innovative mechanisms for detecting cheating services under the MapReduce environment based on watermark injection and random sampling methods. The new detection schemes are expected to significantly reduce the cost of verification overhead. Finally, extensive analytical and experimental evaluation confirms the effectiveness of our schemes in MapReduce result verification.

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Accountable MapReduce in cloud computing

Cited by 35 publications

References 78 publications

Security Issues in ProtoGENI

Security Issues in ProtoGENI

VAWS: Constructing Trusted Open Computing System of MapReduce with Verified Participants

Towards Trusted Services: Result Verification Schemes for MapReduce

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