|VOLUME 14, ISSUE 1, 1 October, 2018 To 31 December, 2020|
|VOLUME 14, ISSUE 1, 1 November, 2018 To 31 December, 2020|
|VOLUME 13, ISSUE 1, 1 April, 2017 To 30 June, 2017|
|VOLUME 12, ISSUE 1, 1 January, 2017 To 31 March, 2017|
|VOLUME 11, ISSUE 1, 16 October, 2016 To 31 December, 2016|
|VOLUME 9, ISSUE 1, 15 April, 2016 To 14 June, 2016|
|VOLUME 8, ISSUE 1, 15 January, 2016 To 14 April, 2016|
|VOLUME 7, ISSUE 1, 15 October, 2015 To 14 January, 2016|
|VOLUME 6, ISSUE 1, 15 July, 2015 To 14 October, 2015|
|VOLUME 5, ISSUE 1, 16 April, 2015 To 15 July, 2015|
|VOLUME 4, ISSUE 1, 16 January, 2015 To 15 April, 2015|
|VOLUME 2, ISSUE 1, 16 August, 2014 To 15 November, 2014|
|VOLUME 1, ISSUE 1, 15 June, 2014 To 15 August, 2014|
Research on security of MANETs remains active, in spite of years of exploration, in both education sector and industry. Despite the fact that no mature solution is widely accepted and the growing availability of small and personalized mobile devices with peer to peer communication capability through wireless channels research in the area is continuing to improve security in MANET. The characteristics of MANET such as node mobility, dynamic infrastructure, unreliable multi-hop communication channel, resource limitation and physical vulnerability and to secure MANET has made more challenging. Using MRA (Malicious Report Authentication) and digital signature to provide the details of false alerts generated by malicious nodes and key authentication before communication have suggested in the previous work. This work uses CTS and RTS signals to exchange the key and symmetric cipher algorithm to encrypt and decrypt the data. Implementation shall be tested with DSDV routing protocol.
Parsers have wide range of applications in system programming, reverse engineering and user oriented applications. They are applied singly or in combinations with natural language processing. For processing text documents, with the advancement in programming a wide range of parsers have been developed starting from normal parsers to combinatorial parsers. Such parsing frameworks are not only useful in parsing of text document but also for analyzing design and its requirements. The proposed parser as stated in this research work is useful in designing a parser for the computer languages which reduces the time complexity of parsing. Hence generating an object file small time will results in low power consumption and complexity. The implementation of proposed parser [An Efficient Parser for Native Compiler] has been conducted and is shown with an example of programs on java language. The analysis of the proposed work has been done with the native algorithm and is observed that the proposed algorithm outperforms with respect to time and power utilization. Proposed parser is based on the top-down approach. The implementation of the proposed parser is done using JDK and Net Beans IDE. The complexity analysis of proposed work shows that our approach is better than other existing works. Other, the experimental results show the better performance of proposed parser as compared to previous parsers.
Cloud computing is spreading around the world and causing the researchers to focus on security of the data over it. These are first, making it possible to communicate between two or more clouds and second, security of communication. The techniques which can be used in hybrid cloud securities are to share the challenge text between the clouds before actual communication should start for authentication. The various works done in this area till now are oriented on other techniques of security between the two or more clouds in a hybrid cloud.
In Data Mining, confidentiality of huge data where users of the system requires getting collaborative access then the complete system is termed as Collaborative Privacy Preserving. The application of privacy preserving of data in collaborative environment faces the problem of low performance and accuracy along with the high security needs. It also requires for providing ease of access for the destined users. This paper proposes a high performance and accuracy based system for collaborative privacy preserving data mining and based on characteristics of the data for faster access as well for the users of the system.
Web mining includes three different domains of data analysis. These domains of data analysis is depends upon the data available for analysis such as for analysing the contents of web pages the content mining, for structure of web pages structure mining and for web usage mining the web usage mining is performed.In this presented workweb usage data is analysed for frequent pattern extraction from data. For extraction of frequent pattern form web accessed data the Apriori algorithm is employed. But due to observations and literature survey of Apriori algorithm some deficiencies are addressed. The key issue in traditional Apriori algorithm is time and spacecomplexity.In addition of that the algorithm sometimes processes the unusual datadue to this additional time and space overhead is added. Therefore in this work the traditional k-mean algorithm is used with the traditional Apriori algorithm with a slight modification. First the K-mean algorithm is applied over data this process split data in small segments. These segments are grouped according to the user IP address and this data processed using Apriori algorithm. That generates the unusual transections using the web access data. Some amount of data can also reduce here using elimination of similar data which introduces ambiguity in dataset. This is also reduced using the similarity computation. The implementation of the proposed technique is performed in JAVA development environment. Additionally the performance of the system is computed in terms of accuracy, error rate, memory consumed and time consumption. According to the obtained results the performance of proposed pattern extraction algorithm is adoptive due to increasing accuracy and reducing error rate and the search time of the mining is also adoptable. On the other hand the memory consumption of the system is slightly high as compared with the traditional algorithm in near future the work is extendable with the memory constrain.