Combined Effect of Soft Computing Methods in Classification

Kompalli, Vijaya Sri; Kuruba, Usha Rani

doi:10.1007/978-981-10-2471-9_49

Cited by 7 publications

(3 citation statements)

References 2 publications

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“…Connecting these developments to breast cancer research 38 , presents a genetically optimized neural network (GONN) specifically for BC classification, employing a genetic algorithm (GA) to refine the neural network's architecture, achieving a noteworthy accuracy rate of 97.73 percent. In 39 , a genetic algorithm is utilized for feature selection, leading to an accuracy of 95.8 percent when supplying optimized features to a support vector machine (SVM) classifier. These instances underscore the significant impact of integrating metaheuristic algorithms with ML techniques on the accuracy and efficiency of cancer diagnosis.…”

Section: Related Workmentioning

confidence: 99%

Breast cancer diagnosis using support vector machine optimized by improved quantum inspired grey wolf optimization

Bilal,

Imran,

Baig

et al. 2024

Sci Rep

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A prompt diagnosis of breast cancer in its earliest phases is necessary for effective treatment. While Computer-Aided Diagnosis systems play a crucial role in automated mammography image processing, interpretation, grading, and early detection of breast cancer, existing approaches face limitations in achieving optimal accuracy. This study addresses these limitations by hybridizing the improved quantum-inspired binary Grey Wolf Optimizer with the Support Vector Machines Radial Basis Function Kernel. This hybrid approach aims to enhance the accuracy of breast cancer classification by determining the optimal Support Vector Machine parameters. The motivation for this hybridization lies in the need for improved classification performance compared to existing optimizers such as Particle Swarm Optimization and Genetic Algorithm. Evaluate the efficacy of the proposed IQI-BGWO-SVM approach on the MIAS dataset, considering various metric parameters, including accuracy, sensitivity, and specificity. Furthermore, the application of IQI-BGWO-SVM for feature selection will be explored, and the results will be compared. Experimental findings demonstrate that the suggested IQI-BGWO-SVM technique outperforms state-of-the-art classification methods on the MIAS dataset, with a resulting mean accuracy, sensitivity, and specificity of 99.25%, 98.96%, and 100%, respectively, using a tenfold cross-validation datasets partition.

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Section: Related Workmentioning

confidence: 99%

Breast cancer diagnosis using support vector machine optimized by improved quantum inspired grey wolf optimization

Bilal,

Imran,

Baig

et al. 2024

Sci Rep

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“…Forensics now-a-days are enforcing its impact and need in many diverse areas like software affected during natural disasters [14], cloud applications where the third party storage kind of works related [16], medicine [17] [19] and other diverse application areas [15] [18][19] [20].…”

Section: Introductionmentioning

confidence: 99%

Automated Collection of Artifacts from a Live Windows System using e-Triage Tool

Kota¹

2020

IJATCSE

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The evolution of computers and technology is outpacing the effectiveness of forensic techniques. In traditional computer forensic methodology, when an organization is effected by a cyber-attack, the systems were plugged off at the scene which results in loss of acquiring volatile memory and further seized media are analyzed at forensic laboratories to get report. In the current work, a novel e-Triage tool is developed which extracts artifacts present within a defined live windows system. It yields on-site identification and interpretation of digital evidences in a short period of time. The e-Triage tool follows live forensic methodology and facilitates to extract and collect artifacts related to system information, registry, events and network information, Random Access Memory, browsing history, shell bag, page file, hibernation file, swap file and also records the changes done by tool on registry whose novelty improves the forensic report. The current proposed e-Triage tool carries out prioritizing and collecting artifacts in preliminary investigation until a potential source is being identified and from then it accelerates further investigation.

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“…Some existed security mechanisms and frameworks of various applications we studied in [11]- [14]. The sentiment analysis, data management and processing algorithms are discussed by several authors are studied from [18]- [20] papers.…”

Section: Introductionmentioning

confidence: 99%

Shuffled Illusion PIN Framework to Prevent Shoulder – Surfing

Kavitha*,

Haran,

Meenan

et al. 2019

IJRTE

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Shoulder surfing is a kind of technique applied to sneak the personal data like passwords and some confidential data of the user. For this type of attacks there is no need of any kind of technical knowledge but just a keen observation towards the user performance is necessary. However, secret gadgets made these shoulder surfing easy for the attackers like cc cams. To overcome these attacks some authentication schemes are proposed- Illusion pin that works on digital display. It applies the method of hybrid pictures with 2 keypads blended one keypad with another, it is designed by using the human visibility and quotes the least distance at which an attacker is incapable to understand the buttons. We developed an innovative shuffling algorithm for shuffling the keys for every single pin entry. Using this Shuffling algorithm, we create a new pattern of the keypad for every exclusive entry of the pin. Through this technique the attacker is unable to track the pin even if he remembers the spatial arrangement of the digits in a keypad. To provide more security we are adding one-time password generating (OTP) technique.

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Combined Effect of Soft Computing Methods in Classification

Cited by 7 publications

References 2 publications

Breast cancer diagnosis using support vector machine optimized by improved quantum inspired grey wolf optimization

Breast cancer diagnosis using support vector machine optimized by improved quantum inspired grey wolf optimization

Automated Collection of Artifacts from a Live Windows System using e-Triage Tool

Shuffled Illusion PIN Framework to Prevent Shoulder – Surfing

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