MIT-World Peace University (MIT-WPU) is a top educational institute located in Pune, India. It is recognized within&nbsp;UGC under Government of Maharashtra Act No. XXXV 2017.&nbsp;

It is part of the MIT group of institutions (established in 1983) which covers 10+ campuses across India and has more than 50,000+ students enrolled across various disciplines at a given point of time. The institute houses 15 schools ranging from Engineering &amp; Technology, Design, Pharmacy, Commerce, Governance among others. It offers undergraduate, postgraduate and PhD programs among different disciplines.&nbsp;

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MIT World Peace University

School of Computer Engineering & Technology

X.509 certificates are used to confirm the identity of the parties involved in the communication and to validate the information being transferred. Currently, more and more people and organizations are using X.509 certificates to prove their identities in online transactions, so the reliability and trust level of these certificates come into question. To solve this question in X.509 Certificates trust model many authors proposed their ideas in their research. In this paper we did survey of different research papers which help in giving answer to the question of X.509 certificates trust model and describe these papers in briefly with their advantages and disadvantages. We also describe the terms and concepts comes in understanding of x.509 certificates.

World University root node

Engineering and Technology

International Journal of Software & Hardware Research in Engineering

Survey of X.509 Certificates Trust Evaluation

Imbalanced data set, a problem often found in real world application, can cause seriously negativeeffect on classification performance of machine learning algorithms. There have been many attempts at dealingwith classification of unbalanced data sets. To handle the problem of imbalanced data is to re balance themartificially by oversampling and/or under-sampling.

International Journal of Computer Science and Mobile Computing

A survey on methods to handle imbalance dataset

Smart phone is used by most of the population. Over thousands of applications are used daily and a new application gets launched as per need. In order to do work on phones itself many desktop applications are getting converted to mobile version by developers. And it's real challenge to market are these applications and reach to the maximum users. From developer point of view for application to reach to most of the end users it need to run on max platforms, this needs redevelopment of application, we can solve this problem to some extent by developing cross platform application without additional investment. Several techniques are available which will help to make it happen. Survey of these techniques could help application developers to make a proper choice.

International Journal of Advanced Research in Computer Engineering & Technology (IJARCET)

Survey on Techniques for Cross Platform MobileApplication Development

Crowdsourcing has developed as a significant problem solving and information gathering standard which makes use of the Internet. The crowdsourced data available on different blogs, forums and social media websites in the form of customer feedback and reviews is an important source of information for the companies. A Data analyst aims at finding trends, patterns and meaningful insights from crowdsourced data. Taking help of crowdsourced workers to analyze this redundant and huge amount of data is not only tedious but is also time consuming. A solution for this problem is proposed that increases the potential of gain of meaningful insights to a large extent. Data mining approach is used to analyze reviews of four different ecommerce websites based on different performance parameters. This unstructured crowdsourced data is processed and filtered using J48 classifier. 355 fake reviews were eliminated. Remaining truthful data was analyzed and Multiviewpoint based similarity clustering was used in order to remove redundancy, which gave the accuracy of 98.66%. To make crowdsourced data more representative and usable graphs were plotted based on delivery, return, refund and customer care parameter to help the analyst in decision making

IJSRD - International Journal for Scientific Research & Development|

Data Mining Approach to Analyze Crowd Sourced Data for BusinessAnalytics

Int.J.Computer Technology & Applications

Gesture Recognition For Mood Detection

Internet has become a vital part of any organization. But with the growth of internet, intrusion and attacks have also increased. Thus, there arises a need of robust and powerful intrusion detection systems which can detect the attacks. Recently, many novel methods are experimented to build strong IDSs. In this paper, we implement a new Improved Dynamic FCM algorithm and successfully integrate it in WEKA to expand the system functions of the open-source platform, so that users can directly call the FCM algorithm to do fuzzy clustering analysis. Besides, considering the shortcoming of the classical FCM algorithm in selecting the initial cluster centers, we represent this Improved DFCM algorithm which adopts a new strategy to optimize the selection of original cluster centers. A novel classification via dynamic fuzzy c means clustering algorithm has been proposed to build an efficient anomaly based network intrusion detection model. A subset of KDD Cup 99 intrusion detection benchmark dataset has been used for the experiment. The proposed novel concept will be efficient in terms of detection accuracy, low false positive rate in comparison to the other existing methods.

International Journal of New Technologies in Science and Engineering

Network Intrusion Detection Using Dynamic Fuzzy C Means Clustering

NS3 is an open source Network Simulator used in research and educational feild.NS3 is an open source free software freely and publicly available for research and development. It is licensed under GNU GPLv2 license. The main aim of this NS3 project is to give network researchers the open simulation environment to test their network protocols so that these protocols gives same performance in the real time screnario.Ns3 is developed by Tom Henderson, George, Sally Floyd and Sumit Roy. The team received funding from US National Science Foundation(NSF) for the development of NS3. NS3 is written from the scratch in c++ programming language. Waf build systems and framework for generating Python bindings are contributed by Gustavo Carneiro. Today NS3 is used by many researchers to perform their research in networking filed. Journals like IEEE, ACM, IJCA etc accepts the result simulated using NS3 simulator. New protocol can be written and tested in NS3 by using c++ language with an extension of .cc, after compiling these .cc files NS3 generates .pcap file and .tr files. These .tr files generated by the NS3 can be analyzed to get the throughput, delay, jitter, packet delivery ratio for new protocol developed. Trace file format of NS3 is totally different from that of trace format of NS2. In this paper a new trace file analyzer is developed using Java so that researcher can spend much of his time and efforts in developing a new protocol than analyzing a trace file. This paper also discussed the trace file format of NS3.Similar project called tracemetric is developed but it is not installed correctly on every machine and is not able to read the .tr file takes too long.

Advances in Information Sciences and Service Sciences(AISS)

Trace Analyzer for NS3

A context-aware architecture can be designed tocollect the mobile user’s context information, derive mobileuser’s current context, distribute user context among contextawareapplications, and support the applications like contextawaresearch. The context acquisition is centralized at thecontext server to ensure the reusability of context informationamong mobile devices, while context reasoning remains at theapplication level. Implementation of such a proxy helpscontext aware applications to derive user context profiles. Theintegration of user context with search engines like Google andYahoo proves how context-aware searches can meet userdemands for tailored services and products in and around theuser’s environment.

International Journal of Computer Science and Information Technologies

A Context-Aware Search System for Smart Phones Based on Context-Aware Infrastructure

Probing has evolved as a promising approach for fault diagnosis in a network management. It is based on the principle of actively sending out probes in the network to infer the health of network components. Probes are test transactions whose success or failure depends on the health of the probed network components. Probing technique for fault localization involves placement of probe stations (Probe stations are specially instrumented nodes from where probes can be sent to monitor the network) which affects the diagnosis capability of the probes sent by the probe stations. Small probe sets is desirable in order to minimize the costs imposed by probing, such as additional network load and data management requirements.In this paper we have presented an overview of various probe set selection algorithms for network fault detection and localization. We have evaluated these algorithms on a sample network for better understanding.

Transactions on Networks and Communications

Survey of Probe Set and Probe Station Selection Algorithms for Fault Detection and Localization in Computer Networks

In this article, we propose two methods for selection of meta parameter (C) in support vector regression. The proposed methods are robust because these are based on the robust statistical measures. The performance of the proposed parameter selection methods is evaluated in case of normal and non-normal distributed error variables. It is evaluated in the sense of prediction risk and mean square error of estimates of regression parameters for clean and outlier data.