The Future Internet: A World of Secret Shares

Buchanan, William J.; Lanc, David; Ukwandu, Elochukwu; Lü, Fan; Russell, Gordon; Lo, Owen

doi:10.3390/fi7040445

Cited by 12 publications

(11 citation statements)

References 13 publications

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“…The secret sharing scheme used is modified Social Secret sharing scheme. The issue of confidentiality and integrity in the use of secret sharing scheme has been validated by many works in secret sharing schemes such as Abdallah and Salleh [13], Buchanan et al [14]. Since RESCUE is concentrated on Data Availability at Zero Downtime [15], the essence of the experiment is to understand all performance overheads that will impact negatively on the objective of the system so as to eliminate them or validating already known facts.…”

Section: Results and Evaluationsmentioning

confidence: 99%

Performance evaluation of a fragmented secret share system

Ukwandu

Buchanan

Russell

2017

2017 International Conference on Cyber Situational Awareness, Data Analytics and Assessment (Cyber SA)

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There are many risks in moving data into public storage environments, along with an increasing threat around large-scale data leakage. Secret sharing scheme has been proposed as a keyless and resilient mechanism to mitigate this, but scaling through large scale data infrastructure has remained the bane of using secret sharing scheme in big data storage and retrievals. This work applies secret sharing methods as used in cryptography to create robust and secure data storage and retrievals in conjunction with data fragmentation. It outlines two different methods of distributing data equally to storage locations as well as recovering them in such a manner that ensures consistent data availability irrespective of file size and type. Our experiments consist of two different methodsdata and key shares. Using our experimental results, we were able to validate previous works on the effects of threshold on file recovery. Results obtained also revealed the varying effects of share writing to and retrieval from storage locations other than computer memory. The implication is that increase in fragment size at varying file and threshold sizes rather than add overheads to file recovery, do so on creation instead, underscoring the importance of choosing a varying fragment size as file size increases.

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Section: Results and Evaluationsmentioning

confidence: 99%

Performance evaluation of a fragmented secret share system

Ukwandu

Buchanan

Russell

2017

2017 International Conference on Cyber Situational Awareness, Data Analytics and Assessment (Cyber SA)

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“…To compare the different schemes, several metrics have to be considered, according to [32], and these include the storage factor, the key management scheme, the data de-duplication option, the revoking authority, the provided security options, the computational overhead, and performance optimization. In table I, we present the comparison of the different secret sharing schemes.…”

Section: B Rabin Information Dispersal Algorithm Ida [20]mentioning

confidence: 99%

Preserving data security in distributed fog computing

et al. 2019

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In this paper, a novel cryptographic solution is proposed to secure data in fog computing. The solution combines the AES-GMAC operation mode with information dispersal over GF(2 w) to provide data confidentiality, integrity, and availability along with source authentication. The value of w is flexible (8, 16, 32 or 64) and it could be configured according to the fog device features. Moreover, the proposed cryptographic solution is based on the dynamic key-dependent approach, which allows for a good compromise between the security level and computational complexity. In the proposed solution, the collected data at one fog node is encrypted, authenticated and dispersed in a pseudorandom manner to its n neighbor fog nodes. For data recovery, any k of the n fragments along with the corresponding dynamic key are required to retrieve the original data. This complicates the attacker's task who needs to compromise at least k fog nodes to disclose the encrypted data. Additionally, attackers should seek the dynamic key, which is different for each input data. On the other hand, redundant fragments protect the stored data against up to (n − k) fog nodes' failure or unavailability. The security and performance analysis tests show that the proposed security scheme exhibits a high level of efficiency and robustness.

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“…Fragmenting and dispersing data over multiple independent storage sites reinforces its confidentiality, integrity, and availability [1]. During the past decades, multiple fragmentation methods were defined and used in various settings [2]. These methods include but are not limited to information-theoretic secret sharing schemes [13], information dispersal algorithms [10], as well as schemes combining symmetric encryption with data fragmentation [8,12].…”

Section: Introductionmentioning

confidence: 99%

PE-AONT: Partial Encryption combined with an All-or-Nothing Transform

Kapusta¹,

Memmi²

2018

Preprint

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In this paper, we introduce PE-AONT: a novel algorithm for fast and secure data fragmentation. Initial data are fragmented and only a selected subset of the fragments is encrypted. Further, fragments are transformed using a variation of an all-or-nothing transform that blends encrypted and non-encrypted fragments. By encrypting data only partially, we achieve better performance than relevant techniques including data encryption and straightforward fragmentation. Moreover, when the ratio between the number of encrypted and non-encrypted fragments is wisely chosen, data inside fragments are protected against exposure of the encryption key unless all fragments are gathered by an attacker.

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The Future Internet: A World of Secret Shares

Cited by 12 publications

References 13 publications

Performance evaluation of a fragmented secret share system

Performance evaluation of a fragmented secret share system

Preserving data security in distributed fog computing

PE-AONT: Partial Encryption combined with an All-or-Nothing Transform

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