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

The abundant availability of food is extremely essential for human existence on this planet, thus making agriculture a mandatory practice throughout the world. Within two decades, a severe complication of food will arise. Hence, the advancement and progress of agriculture is essential. With the help of trending technologies like IoT, the environmental factors that affect the crops are easily monitored, and decisions are taken based on them so that crop monitoring is done remotely, which is a magnificent IoT application. Today, agriculture in the world is partially automated, and farmers mostly rely on traditional methods because of which they suffer from scarcity of rainfall and dearth of water. A plethora of techniques exist that provide automation of agricultural activities and hence increase their efficiency so that better crop output is obtained. The automation of agriculture enables reduction in human involvement. The main purpose of this review paper is to present an overview of various techniques adopted in automated agriculture systems which save the farmers' time, money and power. This paper also extracts key features of existing automated agriculture systems based on their advantages and disadvantages. This paper will assist in the development of a system which will overcome the drawbacks of existing automated agriculture systems. © 2019 IEEE.

School of Computer Engineering & Technology

Engineering and Technology

World University root node

2019 IEEE Pune Section International Conference, PuneCon 2019

Automated Systems for Smart Agriculture

The medical information sharing involves information collection, information storage, and sharing of this information. Protection to medical information against malicious attacks is an important concern due to its storage on remote cloud. In current online question answering system for health-related issues, extraction of medical knowledge from the clamorous question- answers pair is a challenge. To overcome these challenges, medical knowledge extraction scheme for cloudlet based healthcare system is proposed. The proposed and developed medical knowledge extraction (MKE) scheme finds valid remedial Triples from clamorous question-answer (Q-A) pairs and evaluate the reliability along with doctor's proficiency using truth discovery method the modified number theory research unit algorithm (NTRU) and collaborative intrusion detection system (CIDS) is used to avoid and detect malicious attacks. The response time of the proposed system is 6 to 8 seconds which results in a substantial reduction in time and cost for the end-user. © 2019 Inderscience Enterprises Ltd.

International Journal of Cloud Computing

Medical knowledge extraction scheme for cloudlet-based healthcare system to avoid malicious attacks

There is a large number of credit card payments take place that is targeted by fraudulent activities. Companies which are responsible for the processing of electronic transactions need to efficiently detect the fraudulent activity to maintain customers’ trust and the continuity of their own business. In this paper, the developed algorithm detects credit card fraud. Prediction of any algorithm is based on certain attribute like customer’s buying behavior, a network of merchants that customer usually deals with, the location of the transaction, amount of transaction, etc. But these attribute changes over time. So, the algorithmic model needs to be updated periodically to reduce this kind of errors. Proposed System provides two solutions for handling concept drift. One is an Active solution and another one is Passive. Active solution refers to triggering mechanisms by explicitly detecting a change in statistics. Passive solution suggests updating the model continuously in order to consider newly added records. The proposed and developed system filters 80% fraudulent transactions and acts as a support system for the society at a large. © 2018, Springer Nature Singapore Pte Ltd.

Advances in Intelligent Systems and Computing

Implementation of credit card fraud detection system with concept drifts adaptation

AVAYA Interaction Center is developed for communication between customer and the company. The Interaction Center provides business-class control of contact center communications across several channels like voice, email, web chat. Chat is a progressively popular communication channel due to growth in the era of Internet. Existing chat generator tool supports only IE browser. So, there is a need that the tool should be browser independent. The paper proposes the tool based on REST API. In the proposed system, the REST API of Chat media of CSPortal is captured through SOAPUI tool. The request–response of REST API is captured for different resources like/csportal/cometd/of CSPortal Chat Media. The result shows the proposed approach is more efficient than existing tool and chat is live for more than 2 min. © 2018, Springer Nature Singapore Pte Ltd.

Implementation of REST API automation for interaction center

Preface

Agriculture growth is the key component in socioeconomic growth of our country due to liberalization and globalization. Gradually with significant increase in technology, advanced telecommunication services assist plant disease treatment at remote locations. Earlier systems were designed for either monocot or dicot plant family disease detection. The paper proposes an integrated approach for monocot and dicot plant disease detection and treatment along with precautionary measurement through smartphone and image processing techniques. The paper mainly focuses on plant disease detection technique based on integrated approach of K-means segmentation algorithm and SVM Classifier. The proposed and developed approach gives 83 % accuracy for plant diseases recognition. © Springer Science+Business Media Singapore 2017.

Agri-guide: An integrated approach for plant disease precaution, detection, and treatment

The development and urbanization occurred in past decades led to the concept of smart cities. These smart cities consist of various high-risk locations, so there is a need of smart authentication technique which is more reliable and secured. We proposed smart security framework with the integration of enhanced existing technologies. This authentication framework provides security for the high-risk location, such as government office buildings, airport, military bases, and space stations. The area consists of various Wi-fi access points creating the geo-fence. As soon as the person enters into the geo-fence with his smartphone, biometric authentication is carried out using smartphone and accordingly the person is allowed to enter inside the geo-fence. At the same time, Wi-fi positioning system locates the path of person in the geo-fence. Biometric authentication uses the local binary pattern matching algorithm having accuracy of 80 %. The location of the person inside the geo-fence is tracked with the help of Trilateration method. The Wi-fi positioning system based on Trilateration method finds the location of the person with an error rate of 5 m, which is relatively very lower than the Global Positioning System. This wireless authentication framework provides the better solution for security of smart cities which in turn will be beneficial for maintaining the peaceful and healthy social relations. © Springer Science+Business Media Singapore 2016.

Advances in Computing Applications

A smart security framework for high-risk locations using wireless authentication by smartphone

There is a substantial emphasis on security design of Text based CAPTCHA by way of providing the security at pre-processing layer, segmentation layer and character recognition layer. The strength to protect the system from security threats defines the robustness of any given system and which in turn depends on number of attempts the malicious program, which does not have direct access, will need to defend it. This paper proposes a systematic approach to measure the qualitative strength of the Text based CAPTCHA depending on type of TBC, Length of TBC, Character recognition rate and its response time. Applying our systematic approach to different CAPTCHA providers and users, we found that approximately 80% CAPTCHAs are weak and susceptible to our attacks. Along with the attacks leading to weakness of text based CAPTCHA, we have provided the distinguishing features of different CAPTCHA Segmenter which play an important role in defending anti-segmentation techniques. © 2015 IEEE.

Proceedings - IEEE International Conference on Information Processing, ICIP 2015

Systematic approach to measure strength of Text based CAPTCHA

In Delay Tolerant Networks (DTNs), the information is transferred from its source to destination without end-to-end connectivity of the network. The Reputation-Based Trust Management Systems for MANETs do not apply to DTNs due to lack of end-to-end connectivity. The existing Iterative Trust Reputation Mechanism (ITRM) is effective in a detection of malicious node, however it faces from latency time, and hence, sometimes results in false detection of node considered as malicious node. The Proposed Modified Iterative algorithm for Detection of the malicious node for Delay-Tolerant Networks is based on clustering of Raters as per their ratings to Service Providers. The Raters are categorized as low priority, middle priority and high priority based on rating given to Service Provider. This has resulted into lowered amount of false positives and improvement in Service Provider reputation accuracy. The Proposed Modified Iterative algorithm for Detection of the malicious node for Delay-Tolerant Networks is compared with the existing ITRM algorithm and found that, the proposed algorithm has less time complexity and better accuracy of detection of malicious nodes. © 2015 IEEE.

IEEE Region 10 Annual International Conference, Proceedings/TENCON

An approach to detect malicious node for Delay Tolerant Networks

CAPTCHAs (Completely Automated Public Turing test to tell Computers and Humans Apart) are widespread security measures on the World Wide Web that prevent automated programs from abusing online services. CAPTCHAs are designed to be easy for humans but hard for machines. Academic research into CAPTCHAs takes the form of a friendly 'arms race', with some researchers acting as 'malicious users' that try to attack and defeat the latest CAPTCHA systems automatically. Defeating a CAPTCHA requires two procedures: segmentation and recognition. Recent research shows that the problem of segmentation is much harder than recognition. The efforts to break the CAPTCHA determine its strength & thus in turn help the researcher to build stronger CAPTCHA. In order to test the strength of a particular CAPTCHA, in this paper, we have developed a universal algorithm that measures one of the parameters to measure strength of CAPTCHA. The proposed algorithm can adapt to various cases for segmenting characters from CAPTCHA image. The said algorithm is inspired from projection value of characters, concept of snake game and typical patterns of touching the characters. Experimental results prove that the proposed algorithm has improved correct segmentation rates giving accuracy of 85%. © 2012 Springer-Verlag.

Communications in Computer and Information Science

A new approach towards segmentation for breaking CAPTCHA

CAPTCHA stands for Completely Automated Public Turing test to distinguish Computers and Humans apart. CAPTCHA is a program which can generate and grade the tests that it itself cannot pass. The security aspect of CAPTCHA should be such that none of the computer program should be able to pass the tests generated by it even if the knowledge of the exact working of the CAPTCHA is known. The effectiveness of CAPTCHA of a given strength is determined by how frequently the guesses of CAPTCHA can be tested by an attacker. This paper proposes a simple and uniform framework for the assessment of security and usability of CAPTCHA that arbitrary compositions of security measures can provide". In this sentence instead of "a simple and uniform framework", use "parameters". This paper proposes parameters for the assessment of security and usability of CAPTCHA that arbitrary compositions of security measures can provide.The pre-processing attack on targeted CAPTCHA is demonstrated having success rate of approximately 97% which in turn helps to build more robust and human friendly CAPTCHA. The universal structure for segmentation attack is framed to analyze security of CAPTCHA. © 2012 Springer-Verlag.

Security analysis of CAPTCHA

CAPTCHA (Completely Automated Public Turing test to tell Computers and Humans Apart) is a computer-generated test that humans can pass but current computer systems cannot. CAPTCHA provide a method for automatically distinguishing a human from a computer program, and therefore can protect Web services from abuse by so-called bots. Most CAPTCHA consist of distorted images, usually text, for which a user must provide some description. Unfortunately, visual CAPTCHA limit access to the millions of visually impaired people using the Web. The Audio/Voice based CAPTCHA was created to solve this accessibility issue; however, the security of Audio based CAPTCHA was never formally tested. Some Visual CAPTCHA have been broken using machine learning techniques, and we propose using similar ideas to test the security of Audio based CAPTCHA. Audio-based CAPTCHA is generally composed of a set of words to be identified, layered on top of noise. To analyze the security of CAPTCHA it is essential to break it. This breaking of Audio based CAPTCHA has two steps first remove noise and then convert it to text. This paper addresses algorithm for adaptive noise reduction from Audio based CAPTCHA and thus in turn help to determine strength of CAPTCHA. The result shows accuracy up to 80% for Audio based CAPTCHA taken from popular Web sites. Such accuracy is enough to consider these CAPTCHA can be broken after converting to Text form. © 2011 IEEE.

International Conference on Emerging Trends in Engineering and Technology, ICETET

An improved adaptive noise reduction for secured CAPTCHA

CAPTCHA stands for Completely Automated Public Turing Tests to Tell Computers and Humans Apart.A CAPTCHA is a program that protects websites against bots -automated scripts by generating and grading tests that humans can pass but current computer programs cannot. For example, humans can read distorted text but current computer programs can't. The threats from bots is growing rapidly and also increasing in technical sophistication causing various types of attacks. These attacks are affecting social aspects of human beings. Human being or legitimate users are cheated by false requests disturbing their social life. This paper aims to provide secured authentification by verifying strength of CAPTCHA. The strength of CAPTCHA can be verified by solving it. The CAPTCHA solving has mainly three steps such as preprocessing, segmentation and character recognition. The input distorted image of CAPTCHA is passed through preprocessing module which removes noise and gives raw image which is then segmented. These segmented characters are recognized using pattern-matching technique achieving 88% accuracy. The result shows that this algorithm provides secured social relevance to avail free Internet services and in turn improve usability of well-claimed CAPTCHA. © 2010 IEEE.

Proceedings - 3rd International Conference on Emerging Trends in Engineering and Technology, ICETET 2010

Algorithm for secured online authentication using CAPTCHA

Completely Automated Public Turing Tests to Tell Computers and Humans Apart (CAPTCHAs) are the automatic filters that are widely used these days to disallow any automated script that can perform the work of a human. CAPTCHAs are built in such a way that it is very difficult for any automated script to break them. In this paper, an approach to break text based CAPTCHAs has been proposed that first preprocesses the given CAPTCHA, segments its characters, and then recognizes the characters depending on it's features. The breaking of CAPTCHA gives strength of CAPTCHA which in turn helps to develop more robust CAPTCHA The testing results shows that the algorithm successfully breaks the CAPCHA. This algorithm will be also helpful to screen reader program. The results show that it is not a trivial task to design a CAPTCHA scheme that is both usable and robust. © 2009 IEEE.

2009 2nd International Conference on Emerging Trends in Engineering and Technology, ICETET 2009

Algorithm to break visual CAPTCHA

Digital voice systems have been in use for many applications including secure military voice communications, hands-free or cellular mobile telephone systems. In such applications, the speech signal is corrupted by environmental ambient noise. This acoustically added background noise degrades the performance of digital voice processors used for various functions like speech compressors, encoders etc. Further, due to dramatic variance in characteristics of noise in different environments, a single algorithm cannot prove equally beneficial in all circumstances. Finally, the complexity is a major barrier when dealing with systems involving runtime signal processing for mobile phones, as issues such as time complexity and MIPS as involved. Hence, some kind of noise reduction technique has to be employed in order to maintain the performance level of the system at par with that in case of a noise-free environment, regardless of the actual environment in which it is employed. To overcome these problems this paper propose to design a pre-processor system for noise suppression which should adapt to the environmental ambient noise and consequently apply a suitable algorithm. ©2007 IEEE.