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Haq, Shamsul
- Application of Simple Random Sampling in Agriculture using R-software
Abstract Views :250 |
PDF Views:0
Authors
M. Iqbal Jeelani
1,
Nageena Nazir
1,
S. A. Mir
1,
Fehim Jeelani
1,
N. A. Dar
2,
Shamsul Haq
3,
Syed Maqbool
3,
Shahid Wani
3
Affiliations
1 Division of Agricultural Statistics, SKUAST-K, IN
2 Division of Plant Pathology, SKUAST-K,, IN
3 Division of Environmental Science, SKUAST-K, IN
1 Division of Agricultural Statistics, SKUAST-K, IN
2 Division of Plant Pathology, SKUAST-K,, IN
3 Division of Environmental Science, SKUAST-K, IN
Source
Indian Journal of Science and Technology, Vol 7, No 5 (2014), Pagination: 705–708Abstract
In this paper one of the basic techniques of sampling namely simple random sampling has been used utilizing R software keeping in view the importance of this technique in agricultural surveys. Apple data taken from district Ganderbal of Kashmir valley is taken. Function SRSWOR(Y,N) using R software is developed; also different graphics are presented.Keywords
R Software, Boxplot, Simple Random SamplingFull Text
- On Botnet Detection in Networks, based on Traffic Monitoring
Abstract Views :154 |
PDF Views:0
Authors
Affiliations
1 Department of Computer Science and Information Technology, Central University of Jammu, Jammu and Kashmir, 181143, IN
1 Department of Computer Science and Information Technology, Central University of Jammu, Jammu and Kashmir, 181143, IN
Source
Research Cell: An International Journal of Engineering Sciences, Vol 27, No 1 (2018), Pagination: 61-68Abstract
One of the serious and widespread attacks in cyber security is Botnet. Using command and control infrastructure or peer-to-peer communication between bots, botmasters can perform a variety of attacks on internet system-users. To mitigate this, multiple techniques have been developed for botnet detection over the past two decades. In this paper we have discussed various botnet structures and the different techniques of botnet detection proposed in literature. We evaluated these techniques based on their distinctive features and presented their detailed comparative analysis. We also proposed a method for botnet detection using network traffic monitoring. Our approach is based on combining signature and anomaly detection systems that complement each other. Our proposed hybrid detection system may decrease false positive rate in anomaly detection by finding the well-known bots using signature detection and thereby may increase overall detection efficiency.Keywords
Botnet, Malicious Activities, P2P, Anomaly Detection.Full Text
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