Towards DNA based data security in the cloud computing environment

Namasudra, Suyel; Devi, Debashree; Kadry, Seifedine; Sundarasekar, Revathi; Shanthini, A.

doi:10.1016/j.comcom.2019.12.041

Cited by 136 publications

(65 citation statements)

References 24 publications

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“…The service provided using proprietary or software resources must be tracked. Plans are essential to monitoring the use of these services based on the mean plot [19] as shown in Figure 7b—their SLAs, performance, robustness, and business dependency. Society is most likely facing the future, with a majority of schools in a cloud, and institutions with expensive hardware, power bills, salaries, and computer resources no longer have their own data centers.…”

Section: Resultsmentioning

confidence: 99%

Research on the design of analytical communication and information model for teaching resources with cloud‐sharing platform

Zheng

Muthu²,

Kadry

2021

Comp Applic In Engineering

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The recent growth in the adoption by several organizations of cloud computing services has created the challenge to determine their performance of information model. The ability of cloud computing systems to provide the required services in line with the quality of service and service level agreement constraints is a major problem for cloud service providers and consumers. To that end, it is possible to develop the means of ensuring that the desired levels of success are achieved in simulated environments. In the eventual stage of commissioning and running cloud computing, this will reduce the disrupted service and performance degradation problems using analytical communication and information model of cloud technology. However, several modelers and simulators for simulating cloud computing systems are available in conventional research. This paper, therefore, provides a critical assessment with state of the art cloud computing modeling and simulation frameworks. It compares the prominent frameworks of simulation regarding application programming interface features, programming flexibility, operating system requirements, services supported, and licensing needs with 95% reliability. It offers recommendations to the researchers, administrators, and managers of cloud computing systems regarding the choice of the most appropriate framework.

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Section: Resultsmentioning

confidence: 99%

Research on the design of analytical communication and information model for teaching resources with cloud‐sharing platform

Zheng

Muthu²,

Kadry

2021

Comp Applic In Engineering

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“…However, even though the behavioral study of both marine and terrestrial animals has been in literature for many other applications. In the presented comparison, ensemble classification has provided insights about cattle monitoring [72] and conservation area identification in dolphins [97] cattle.…”

Section: E Sequenced Methods With Existing Ensemblesmentioning

confidence: 99%

“…However, in practice, there may be uncertainties, unpredicted dynamics, and other unknown phenomena that cannot be mathematically modeled. The main contribution of the fuzzy modeling theory is its ability to handle many practical problems that cannot be adequately represented by conventional methods [97][98][99][100][101][102].…”

Section:  Frbcs For Animal Behavioral Classificationmentioning

confidence: 99%

Did They Sense it Coming? A Pipelined Approach for Tsunami Prediction Based on Aquatic Behavior Using Ensemble Clustering and Fuzzy Rule-Based Classification

et al. 2020

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Tsunami is one of the real feelings of dread among humanity. Designing an early and effective Tsunami Warning System (TWS) is an immediate goal, for which the scientific community is working. Underwater seismic responses sensed by different numerical expository techniques have resulted in various cautionary frameworks proving successful in predicting tsunamis. However, multiple instances in the past where these warning systems have failed to generate alerts in time, has raised concerns to design even more efficient, diverse, and multidisciplinary warning methods or systems. However, there have been many instances in the past where these warning systems have failed to generate alerts in time, raising concerns about designing/implementing more efficient, diverse, and multidisciplinary warning methods or systems. Therefore, we propose a sequenced (EC G F C) approach for designing a TWS, based on Ensemble Clustering (EC G) and Classification for categorizing anomalous behavior in response to seismic perturbations, taking three aquatic animal behavioral datasets: Turtle, Earthworm, and Fish, as the input(s). EC G uses an existing state-of-the-art method bagged with Gaussian mixture model to label the dynamically changing behavioral data. The paper compares the results of the clustering ensemble used with baseline clustering methods on three behavior datasets as well as four benchmark datasets. The proposed sequenced (EC G F C) method is finally compared on three classification error metrics: MSE, MAE, and SMAPE on behavioral and existing ensemble frameworks in the state-of-the-art.

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“…The outcome illustrated augmented efficiency along with reduced search time. The system elucidated the disadvantages of the L-EncDB lightweight encryption in support of the database along with MSSK (most significant single keyword) that made use of the radix sort to investigate the data, along with that the system trounced the augmented storage space centred upon SEDFS [25]. The main shortcoming of SEDFS was that it encompassed more time when searching a keyword.…”

Section: Literature Surveymentioning

confidence: 99%

Three factor authentication system with modified ECC based secured data transfer: untrusted cloud environment

Vengala

Kavitha

Kumar

2021

Complex Intell. Syst.

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Cloud computing (CC) is a technology that delivers its service by means of the internet. In the modern scenario, cloud storage services have gained attention. The cloud environment confronts data breaches expansively in cloud storage, which might bring about the disclosure of personal in addition to corporate data. Thus, the requirement arises for the creation of a more foremost authentication system. Customary authentication schemes depend on techniques, like Password Authentications Protocol (PAP), Challenge Handshakes Authentication Protocols (CHAP), as well as One-Time Pads (OTP), which are often susceptible to malevolent attacks as well as security threats. To shun such issues, this paper proposed a Modified ECC centred secure data transfer and a ‘3’-factor authentication scheme in the untrusted cloud environment. The proposed work comprises ‘3’ steps: authentication, data compression, and safe data transfer. In the authentication phase, the SHA-512 algorithm along with CCP is utilized. After that, the user-uploaded data is compressed utilizing CHA on the server-side. Next, MECC encrypts the compressed data, and then, safely uploaded it to the cloud server (CS). In the investigational appraisal, the proposed work is contrasted with the prevailing methods. The outcomes proved that the proposed work renders better security than the prevailing methods.

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Towards DNA based data security in the cloud computing environment

Cited by 136 publications

References 24 publications

Research on the design of analytical communication and information model for teaching resources with cloud‐sharing platform

Research on the design of analytical communication and information model for teaching resources with cloud‐sharing platform

Did They Sense it Coming? A Pipelined Approach for Tsunami Prediction Based on Aquatic Behavior Using Ensemble Clustering and Fuzzy Rule-Based Classification

Three factor authentication system with modified ECC based secured data transfer: untrusted cloud environment

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