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Lakhani, Jyoti
- Blind XPath Injection Attack: A Case Study
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1 Maharaja Ganga Singh University, Bikaner, Rajasthan, IN
1 Maharaja Ganga Singh University, Bikaner, Rajasthan, IN
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International Journal of System & Software Engineering, Vol 1, No 1 (2013), Pagination: 30-34Abstract
Extensible Mark-up Language (XML) is adopted by different organizations as a data exchange format for web services and internet applications. The XML is much prone to hackers' attack. The common hacking technique for XML is XPath injection. The attacker can exploit the XPath to manipulate the database. XPath Injection attack can even bypass the system security and results can be disastrous. In this communication Blind XPath code injection problem is being reviewed using a case study. This article discusses the extent of the problem and few principals for managing and solving XML deployment.Keywords
XML, XPath Injection, Blind XPath Injection
References
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- Clustering Trend Predictions Using Evolutionary K-means Algorithm for Automated Clustering
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Authors
Affiliations
1 Maharaja Ganga Singh University, Bikaner, Rajasthan, IN
1 Maharaja Ganga Singh University, Bikaner, Rajasthan, IN
Source
International Journal of Knowledge Based Computer System, Vol 1, No 2 (2013), Pagination: 29-32Abstract
The paper proposed a method of hybridization of k-means algorithm and evolutionary programming. The blend of the two generates k number of clusters C = (c1, ..., ck) in the data space D = {x1, ..., xn}. These clusters will evolve in such a way that prediction of the upcoming trends of clusters in the application is possible. The proposed hybrid is named as evolutionary k-means clustering algorithm which is useful in generating and predicting clustering trends in an automated system.Keywords
Clustering, Data Mining, Evolutionary Programming, K-means- Clustering Techniques for Biological Sequence Analysis: a Review
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Authors
Affiliations
1 Deaprtment of Computer Science, Maharaja Ganga Singh University, Bikaner, Rajasthan, IN
1 Deaprtment of Computer Science, Maharaja Ganga Singh University, Bikaner, Rajasthan, IN
Source
Journal of Applied Information Science, Vol 3, No 1 (2015), Pagination: 14-32Abstract
In the present scenario there are a variety of technical tools for supporting and validating wet-lab experiments in the field of science and biotechnology. In order to analyze biological sequences it is necessary to group similar genes. Grouping of genes can be done by using various techniques like pattern matching, classification, clustering etc. In the present study clustering is used as a tool for analyzing biological data. Clustering of Biological sequences is a very interesting and fascinating area as various researchers are working on it. But simple clustering algorithms are not much suitable for sequence analysis problems. Most of the biological sequence analysis problems are NP-hard and some strong optimization algorithm are required for these types of problems.The manuscript presented here is a survey of various clustering techniques useful for analysis of biological sequences. The 3+ stage review process is adopted for the review of literature. To prepare this report 98 papers have been reviewed from year 1997 to 2014 according to the year of publish. The papers reviewed have discussed various issues related to the analysis of biological sequences. The major issues discovered in the reviewed papers were prediction, sequence alignment, motif discovery, cluster boundary prediction etc. Various solution approaches used by researchers for the biological sequence analysis are evolutionary clustering, neural networks, hierarchical clustering, k-means, Go technologies, feature selection, incremental approach, bio-inspired methods, particle swarm optimization, fuzzy techniques, rough set theory and bi-clustering etc. Researchers have applied these solution approaches on various types of datasets. In this communication we have also discussed about these datasets and the parameters used with results mentioned in papers.
Keywords
Biological Sequences, Sequence Analysis, Clustering, Sequence Clustering.References
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- A Complete Inter-Class Sharing During the Inheritance to Enhance Reusability of Public Data and their Access Control Using Dominance
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Authors
Affiliations
1 Department of Computer Science, Maharaja Ganga Singh University, Bikaner, Rajasthan, IN
2 Department of Microbiology, Maharaja Ganga Singh University, Bikaner, Rajasthan, IN
1 Department of Computer Science, Maharaja Ganga Singh University, Bikaner, Rajasthan, IN
2 Department of Microbiology, Maharaja Ganga Singh University, Bikaner, Rajasthan, IN
Source
International Journal of System & Software Engineering, Vol 3, No 2 (2015), Pagination: 14-18Abstract
Inheritance is used for reusability in an object oriented programming language. The complete reusability is not possible with the simple inheritance process. On inheriting parent class, the child does not get a complete access to the inherited data. Only an instance of the values of inherited data has been accessible by the child class and it is true even for the public data. The present communication is a concept paper in which a special inheritance method has been conceptualised. This proposed method is called backward accessibility inheritance. Once inherited, the public data item of the parent class can be shared by the child class in all sense. This way the inherited data item can be truly reused by child class in terms of memory space, name and value. To control the accessibility of the data during the backward accessibility inheritance, concept of dominance has also been introduced.Keywords
Inheritance, Object Oriented Programming, Backward Accessibility, Dominance.References
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- Cluster Validation of Evolutionary Clustering Algorithm for Multivariate Datasets
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