FedORAM: A Federated Oblivious RAM Scheme

Pujol, Alexandre; Murphy, Liam; Thorpe, Christina

doi:10.1109/access.2020.3027516

Cited by 2 publications

(5 citation statements)

References 33 publications

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“…The proposed approach has evaluated with number of users and number of servers for communication cost, based on both results our system is efficient than [29] in both experiments.…”

Section: Security Analysismentioning

confidence: 98%

“…Pujol et al [29] presented FEDORAM. Weak and strong FEDORAM tried to tradeoff between security and performance in the instance messaging.…”

Section: Related Workmentioning

confidence: 99%

“…On the other hand, the shuffling procedure must be done often, and the whole storage must wait for such shuffled to finish before proceeding to another ORAM process. It adds extra waiting time to the process resulting in delayed output [29]…”

Section: Related Workmentioning

confidence: 99%

“…According to FEDORAM, it describes one-to-one communication between all servers, which may produce high communication costs [29]. The proposed module generates a parallel connection between to all available sets of servers S. Fig.…”

Section: Security Analysismentioning

confidence: 99%

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HORAM: Hybrid Oblivious Random Access Memory Scheme for Secure Path Hiding in Distributed Environment

Funde¹,

Swain²

2021

IJACSA

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Now-a-days in most of the sectors digitization has taken place to store data and process it easily with enhanced techniques. Online transactions produce very huge data daily in various sectors like health care, military, government office. To store huge data many firms, take the help of third-party organizations and store data on machines provided by them which creates new security issues. While performing operations on the data or accessing data metadata leakage may happen due to untrustworthy systems. This paper proposed hybrid oblivious random-access memory (HORAM) offers users to access their data from untrusted storage devices without sharing any information about their access patterns or techniques. Here random data block shuffling approach is used which helps in hiding storage policies about the user data blocks placement and preserving privacy of data. HORAM techniques perform pullpush operations on data in a parallel manner which in turn minimizes network overhead and reduces the execution time of operation. An extensive experimental analysis of the proposed system produces better results than weak and strong Federated oblivious random access memory (FEDORAM) respectively. The method is faster than weak FEDORAM and strong FEDORAM as it takes 0.96 seconds for communication with 5 servers whereas weak and strong FEDORAM takes 1.5 and 2 seconds respectively for reading and writing data.

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“…The proposed approach has evaluated with number of users and number of servers for communication cost, based on both results our system is efficient than [29] in both experiments.…”

Section: Security Analysismentioning

confidence: 98%

“…Pujol et al [29] presented FEDORAM. Weak and strong FEDORAM tried to tradeoff between security and performance in the instance messaging.…”

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Security Analysismentioning

confidence: 99%

See 2 more Smart Citations

HORAM: Hybrid Oblivious Random Access Memory Scheme for Secure Path Hiding in Distributed Environment

Funde¹,

Swain²

2021

IJACSA

View full text Add to dashboard Cite

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“…Additionally, parameter 𝑤 affects the randomization of blocks. This section provides definitions key terms used in the article as well as an overview of Federated Oblivious RAM (FedORAM) [48] system architecture and threat model.…”

Section: Cycle Orammentioning

confidence: 99%

Big Data Privacy and Security Using Abundant Data Recovery Techniques and Data Obliviousness Methodologies

Funde

Swain

2022

IEEE Access

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The concept of big data security is introduced in this article along with many features. It illustrates the need for security in healthcare systems as the volume of data increases continuously over the period of time. The necessity of big data security as well as several big data analytics phases highlighted. It covers many big data privacy-preserving strategies. Many digital storage solutions being used in today's world are designed to work only with fixed format of the data. This paper introduces some methods for maintaining metadata obliviousness. The oblivious RAM technology mentioned in the research article address security concerns and it can be handled with the daily increase in data in several industries. Security needs are introduced at many phases of big data creation, such as information extraction, storage systems, and analytics of the information. Additionally, it presents several data recovery methods for recovering original data in the event of a data crash. This paper covers several data categorization methods for sorting data into normal and sensitive categories as well as methods for anomaly detection. It discusses the advantages and disadvantages of various security measures.INDEX TERMS Security, privacy, obliviousness, data recovery. I. INTRODUCTIONThe core concepts and phases of big data are introduced in this section. At several stages of big data production, such as data generation, data storage, and data analytics, security requirements are introduced. The importance of security in big data, cloud, and Internet of Things (IoT) infrastructure is discussed in this section. It discusses about several security measures that must be defended against various kinds of attacks. It discusses on the security of healthcare systems. It gives a general overview of the medical industry and discusses how patient data must be safeguarded if it is stored in a dispersed setting. A. BIG DATABig data is data that has large volume, heterogeneity, speed, and volatility all at the same time. The term "high volume" denotes to the significant quantity of data that is produced on a daily basis by a variety of companies and organizations. The rapid proliferation of new data types, many of which are going to be incorporated in current datasets that have been acquired from a variety of companies and devices, is referred to as heterogeneity. The term "high speed" refers to the rapid rate at which data is collected or captured from a variety of social networking sites into a database [1]. Huge amounts of data present additional difficulties to the security systems that are already in place due to the variety, volume, and unpredictability of the data. Most data storage models used today are designed to work with data that has been properly arranged. The currently available encryption methods are inefficient for use with massive data as once data has been encrypted, producing keys, encrypting it, and then decrypting it takes a significant amount of time. For instance, the data collected from patients, various sensors, soc...

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FedORAM: A Federated Oblivious RAM Scheme

Cited by 2 publications

References 33 publications

HORAM: Hybrid Oblivious Random Access Memory Scheme for Secure Path Hiding in Distributed Environment

HORAM: Hybrid Oblivious Random Access Memory Scheme for Secure Path Hiding in Distributed Environment

Big Data Privacy and Security Using Abundant Data Recovery Techniques and Data Obliviousness Methodologies

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