Towards an Intelligent Framework for Cloud Service Discovery

Ali, Abdullah Marish; Shamsuddin, Siti Mariyam; Eassa, Fathy; Saeed, Faisal; Alassafi, Madini O.; Al-Hadhrami, Tawfik; Elmisery, Ahmed M.

doi:10.4018/ijcac.2021070103

Cited by 5 publications

(2 citation statements)

References 25 publications

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“…This phase involves preprocessing the data set for training the model, that is, converting the data from raw form into a usable form or understandable form. 29,30 Data preprocessing involves three phases, that is, data cleaning, data transformation, and data reduction. Data transformation involves normalization and attribute selection.…”

Section: Data Preprocessingmentioning

confidence: 99%

A content and URL analysis‐based efficient approach to detect smishing SMS in intelligent systems

Jain

Gupta

Kaur

et al. 2022

Int J of Intelligent Sys

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Smishing is a combined form of short message service (SMS) and phishing in which a malicious text message or SMS is sent to mobile users. This form of attack has come to be a severe cyber‐security difficulty and has triggered incredible monetary losses to the victims. Many antismishing solutions for mobile devices have been proposed till date but still, there is a lack of a full‐fledged solution. Therefore, this paper proposes an efficient approach that analyzes text content and uniform resource locator (URL) presented in the SMS. We have integrated the URL phishing classifier with the text classifier to improve accuracy as some of the SMS contain the URL with no text or much less text. To find out rare words in a report, depending upon the frequency of term (TF) and the reciprocal of document frequency TF‐inverse document frequency (IDF), a weighting framework TF‐IDF is used. We have used two data sets for both text as well as for URL phishing classifier and used a synthetic minority oversampling technique to balance the training data. The voting classifier simply merges the findings of each classifier passed into it and predicts the output on the basis of voting. In proposed approach integrating KNN, RF, and ETC can detect smishing messages with a 99.03% accuracy and 98.94% precision rate which is relatively efficient compared with existing ones like SmiDCA model which has the given accuracy of 96.40% using Random Forest classifier in BFSA, Feature‐Based it has an accuracy of 98.74% and 94.20% true positive rate and Smishing Detector it shows an overall accuracy of 96.29%.

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Section: Data Preprocessingmentioning

confidence: 99%

A content and URL analysis‐based efficient approach to detect smishing SMS in intelligent systems

Jain

Gupta

Kaur

et al. 2022

Int J of Intelligent Sys

View full text Add to dashboard Cite

show abstract

“…In an Intelligent System, 1 intelligence is integrated into machine applications, like, transport systems, [2][3][4][5][6] Internet of Things, 7,8 cloud computing, 9,10 data extraction, [11][12][13][14][15] computer networks, 16,17 sustainable technology, 18,19 and numerous others. In this, the environment is perceived by the machine and the system responds accordingly.…”

Section: Introductionmentioning

confidence: 99%

An efficient hardware supported and parallelization architecture for intelligent systems to overcome speculative overheads

Kumar

Singh

Aggarwal³

et al. 2022

Int J of Intelligent Sys

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In the last few decades, technology advancements have paved the way for the creation of intelligent and autonomous systems that utilize complex calculations which are both time‐consuming and central processing unit intensive. As a consequence, parallel processing systems are gaining popularity to enhance overall computer performance. Programmers should be able to efficiently utilize available hardware resources with parallelization in an ideal world. Through the automatic parallelization of sequential code, multithreading can be executed without extra supervision. However, a wide range of software dependencies prevents this from being feasible. An architectural framework for speculative parallelization along with an efficient memory analysis and computational algorithms for the code generation are proposed that can provide optimal performance. Furthermore, a suitable support of hardware design as a runtime library to the proposed architectural framework is presented which can be used to recover misspeculated results during execution to minimize speculative parallelism overhead. The implementation makes use of the Low‐Level Virtual Machine compiler infrastructure and is tested on numerous benchmarks, thus making it highly scalable in terms of programming languages and architectures. According to our experimental results, there is significant potential for speedup increase. In comparison to the overall function speedup, that is, geomean speedup of 5.2× approximately when using the proposed architecture without hardware support, the proposed architectural framework and algorithm with hardware support give an average geomean speedup of 7.0× approximately on the given benchmark which is written in C/C++.

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A Node-Level Model for Service Grid

Wang

Jifei

2022

Mobile Information Systems

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This papers studies a high-performance node-level service grid model, which aims to solve the problem that the current pod-level service grid model affects the service operation and consumes many computing resources. The main method of the node-level service grid model is to improve pod-accompanied service grid sidecar with the node-accompanied service grid sidecar sharing of multiple pods, combined with the cut-through of user mode protocol stack and scaling of node-level service grid sidecar. By the performance comparison of pod-level service grid model and node-level service grid, we can conclude that node-level service grid model can isolate pod services without affecting service operation, significantly reduce memory consumption without multiplying with the number of pods, and largely reduce end-to-end network delay about 30% but the overall CPU consumption as the same as that of the pod service grid model. It indicates that the node service grid model can obtain better business benefits than the pod service grid model in container cloud, cloud service providers can provide grid services for more tenants with less memory resources and network latency, and adding grid services has no impact on the operation of user applications.

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Towards an Intelligent Framework for Cloud Service Discovery

Cited by 5 publications

References 25 publications

A content and URL analysis‐based efficient approach to detect smishing SMS in intelligent systems

A content and URL analysis‐based efficient approach to detect smishing SMS in intelligent systems

An efficient hardware supported and parallelization architecture for intelligent systems to overcome speculative overheads

A Node-Level Model for Service Grid

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