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Pauline, A.
- HTTP Botnet Defense Mechanism using System Dynamics based Genetic Algorithm
Abstract Views :174 |
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Authors
Affiliations
1 Department of Computer Science and Engineering, MVJ College of Engineering, Near ITPB, Whitefield, Bangalore-560 067, Karnataka, IN
1 Department of Computer Science and Engineering, MVJ College of Engineering, Near ITPB, Whitefield, Bangalore-560 067, Karnataka, IN
Source
Indian Journal of Science and Technology, Vol 9, No 45 (2016), Pagination:Abstract
Objectives: The system which is under the control of Bot master is called Bot. Botnet refers to the network of bots. Hypertext Transfer Protocol (HTTP) Botnet use HTTP protocol for communication. Findings: HTTP Botnet is difficult to detect since their features are somewhat similar to normal HTTP traffic1. Genetic algorithm Based detection method results in better analysis of botnet attacks. However, it sets the initialization pool by picking the values randomly and can assure only less false positive rate. Novelty: This paper proposes System Dynamics (SD) based Genetic Algorithm for improving the efficiency of Genetic algorithm and hence the botnet detection.Keywords
Genetic Algorithm, HTTP Botnet, Layered Detection, System Dynamics.- An Improvement in Defect Detection Efficiency -A Review
Abstract Views :143 |
PDF Views:0
Authors
Affiliations
1 Department of Computer Science, MVJ College of Engineering, Near ITPB, Whitefield, Bangalore-560 067, Karnataka, IN
1 Department of Computer Science, MVJ College of Engineering, Near ITPB, Whitefield, Bangalore-560 067, Karnataka, IN
Source
Indian Journal of Science and Technology, Vol 9, No 45 (2016), Pagination:Abstract
Objectives: The defect detection efficiency has to be improved by comparing different software development lifecycles and finding the best of defect detection methodology, along with the accurate defect rate analysis and classification and to achieve 100% efficiency in defect detection and attain 100% customer satisfaction. Methods and Statistical Analysis:- Agile methodology, with In-memory analytics is employed to improve the effectiveness of defect detection efficiency. Along with Agile methodology, defect comparison and classification of defects based on defect rate with respect to the standard threshold values, at each stage of the design process can be employed. In memory analytics can be employed for Defect classification. This method provides effectiveness of defect classification and rates defect as low, high and medium. This method easier the tasks of designer to detect the severity of defect and rectify, to avoid the defect being added to subsequent phases. Findings: It is found that, In Waterfall model, the product is tested only after the product has been completely manufactured. The defect detection effectiveness considering an average of 15-20 percentages of defects originating at each phase is 50 percent. In Six Sigma approach, the defect detection effectiveness which is improved to 99.9997 percent with the same percentage of defect originating at each phase. While 100 percent defect detection effectiveness is not practically possible. Hence the greatest challenge is how the testing engineers can meet 100 percent testing standard. The testing engineers need to adapt a unique technique to remove the defects before they get added to the system. Such technique will not only helps to detect defects faster but also reduces the high cost of poor quality products.Keywords
Defect Detection Methodology with Accurate Data Analytics, Defect Detection and Classification, Defect Analysis, Defect Characterization, In-Memory Analytics.- Configuring Linux System for Internet Protocol based Multimedia Communication Network
Abstract Views :174 |
PDF Views:0
Authors
C. Sivaprakash
1,
A. Pauline
2
Affiliations
1 Sri Sairam College of Engineering, Bengaluru - 562106, Karnataka, IN
2 Department of CSE, SEA College of Engineering, Bengaluru - 560049, Karnataka, IN
1 Sri Sairam College of Engineering, Bengaluru - 562106, Karnataka, IN
2 Department of CSE, SEA College of Engineering, Bengaluru - 560049, Karnataka, IN