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

Internet of Things (IoT) visualizes future, in which the objects of everyday life are equipped with sensor technology for digital communication. IoT supports the concept of smart city, which aims to provide different services for the administration of the city and for the citizens. The important application of IoT is Structural Strength Recognition (SSR). This approach is becoming popular to increase the safety of buildings and human life. Proper maintenance of historical buildings requires continuous monitoring and current conditions of it. Sensor nodes are used to collect data of these historical buildings or large structures. Structural strength recognition covers huge geographical area and it requires continuous monitoring of it. It involves more energy consumption during these activities. Hence, there is need for efficient energy management technique. Clustering is one of the important techniques for energy management in Wireless Sensor Networks (WSN). It helps in reducing the energy consumed in wireless data transmission. In this paper, SSR system is designed with efficient clustering algorithm for wide network and also finds out optimum number of clusters. © 2018, Springer Nature Singapore Pte Ltd.

Engineering and Technology

World University root node

Advances in Intelligent Systems and Computing

Structural strength recognizing system with efficient clustering technique

nventory management and supply chain are areaswhich have strong potential to benefit from Radio FrequencyIdentification technology. In the premises of a wholesale market,location tracking of a product itself becomes challenging for thebuyers. The implemented application will help the buyer to locaterequired product and find the shortest path from his location tothe product’s location. This will help him to locate the product inoptimum time, thus saving his efforts in searching the productmanually. The location tracking is developed with the RFIDtechnology and shortest path is obtained through Digital ImageProcessing

Application of RFID and Path Planning Algorithm forLocating Products in a Wholesale Market

International Journal Of Advancement In Engineering Technology, Management and Applied Science (IJAETMAS)

Computer Aided Learning In Engineering Education

The paper presents a brief overview of Online BankTransaction Processing system which addresses entireprocess of online trading starting from the basicTerminologies to functionality offered by each components &then heading towards actual work flow. As we all know howmuch secured and confidential bank account details are thanwhat actually makes it possible for middleware’s like Flipkart,Paytm, Snapdeal to look into clients account and smoothlycarry out transaction process, by deducting the exact paymentand that too without causing any security issues. The paymentGateway is responsible for offering n number of features suchas customer & merchants account authentication,unforgivable proof by customer to merchant & bank. Mostimportantly personal credentials of user are highly secured. The security architecture of the system isdesigned by using Security Protocols Techniques such asSecured Socket Layer, Secured Electronic Transactionprotocol, Tunneling protocol and Encryption standard whichinclude 56bit DES (Data Encryption System), 168bit TDES(Triple Data Encryption System), and AES (AdvanceEncryption Technique).

International Journal of Scientific & Engineering Research (IJSER), ISSN (Online): 2229-5518

Online Bank Transaction Processing System: An Operational Overview

In domain of data mining and machine learning, multi-label classification is widely studied research problem. The goal of multi-label classification is to predict the absence or presence certain labels of a particular applications those are associated with different classes. In this paper, IML-Forest method is presentedwith goal of improving the performance of multi-label classification over different types of datasets. IML-Forest is based on existing ML-Forest technique. In this paper the construction of set of hierarchical trees and designed the label transfer mechanism in order to identify multiple relevant labels in hierarchical way is proposedto solve the problem of label dependencies in multi label classification. Basically relevant labels at higher levels of trees capture the more discriminable label concepts; next they will be shifted at lower level nodes. From the hierarchy the relevant labels are further aggregated in order to compute the label dependency and make the classification prediction. The problem with ML-Forest method is that noise considerations not yet addressed as collected multi-label dataset may be noisy and imbalanced. This can degrade the performance of learning and accuracy. Noise reduction method is proposed on multi-label dataset to solve the problem of noisy and imbalanced dataset. In this paper the text noises related to low-level data errors are handled.

International Journal on Recent and Innovation Trends in Computing and Communication

Multi-Label Classification Using Noise Reduction Techniqueâ€

International Journal for Scientific Research & Development (IJSRD), ISSN (Online): 2321-0613

An Automated SAN Solutions Overcome by Threshold Cryptography for Security by using Cloud Computing

Fog computing is a distributed computing infrastructure in whichsome application services are provided at the edge of the network in smart devices( IoT devices) and some applications are handled in cloud. Fog computing operates on network ends instead of working entirely from a centralized cloud. It facilitates the operation of storage, compute, analysis and other services between edge devices mostly IoT devices and cloud computing data centres. The main objective of Fog computing is to process the data close to the edge devices .The problem that occurs in Fog is confidentiality and security of data . To overcome this problem, we have proposed the Dual-Encryption to data using Emoticon Technique which is combination of Cryptography and Steganography. In this method, first data is encrypted and then encrypted data is hidden with the cover text like emoticons. So Dual-Encryption enhances data security and reliability. Even if the covered text is accessed by unauthorized person, only encrypted data of original data can be viewed not the actual data.

International Journal on Recent and Innovation Trends in Computing and Communication (IJRITCC)

Secure Fog Computing System using Emoticon Technique

Nowadays companies need to manage user accesses across multiple channels such as mobile, social and cloud. Business is always about delivering value to customers, and Identity and Access Management is very essential part of ensuring that employees are both empowered to deliver that value and prohibited from damaging the security, business reputation. Organization can use Identity and Access data to detect the attacks within the organization. Data Analytics techniques can be used to identify the anomalies in the identity and Access Data, out of that Peer group Analysis is one technique. Peer Group Analysis focuses on the local pattern rather than the global models; anomaly may not be present when compared with whole data but there may be some outliers present when compared with its peer groups. Context anomaly is the data points that considered abnormal when compared with its peer group. In this research we are doing peer group analysis on Identity and Access Data using the various outlier detection algorithms. Various context anomaly detection algorithms are used to identify the abnormal user behaviour which gives the risk insights the organization. We are proposing peer group analysis which can able to locate entitlements that can be exclusive than other users of same group, which gives the risk of the user access.

Fulltext

International Journal of Engineering and Technology

Peer Group Analysis in Identity and Access Management to Identify Anomalies

Now a days, rapidly increasing the use of online social networks (OSNs). Through this services user’s can communicate and transfer any data. The major disadvantage of these Online Social Networking (OSN) services is the lack of privacy for the user’s own private space. We use pattern matching and text classification algorithm for accurate filtering results. We propose a system allowing OSN users to have a direct control on the messages posted on their walls. This is a flexible rulebased system that allows users to customize the filtering process applied to their user’s profiles. A machine learning technique automatically labeling messages in support of content-based filtering. Index Terms: content-based filtering, filtering rule, filtering system, machine learning , online social networks