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Item Virtual Motion Detector to Detect Crime In Real Time and Alert Authorized Person(2018-06-19T11:40:48Z) DEVENDAR KUMAR K, CHOUDARY; S, PREETHI; SAGAR, K; SHRAVANTHI, SThe Computer Vision Intruder Detection Security System aims at providing an understanding vision to the user’s computer. This proposed software would revolutionize the technology and it will replace the existing technology by providing strong means of security which was lacked in the previous security system by implementation of the concepts like Computer Vision, Object recognition, video tracking and advanced image processing with object detection systems. The proposed system is highly user friendly and portable it can convert any normal pre-existing security cam or the web cam into Artificial intelligence camera which would add the quality of recognizing objects in them which would set a bench mark in security systems and in the fields of computer vision and artificial intelligence. The software has two different zones the red and the green zones. When the cameras are set to the green zone it behaves like a normal CCTV camera and records footage., When its set to the red mode the normal CCTV cameras turn into an artificial intelligence camera which would activate the artificial intelligent brain for the CCTV cameras to detect any intrusions. The proposed software also lets the user to set both the green and red zones simultaneously.Item Detection and Prevention of Dos Attack On Websites(2018-06-19T11:37:37Z) SUCHITHRA, A B; RASHMI, D S; KRUTHIKA, PThe web is a complicated graph, with millions of websites interlinked together. In this project, we propose to use this website graph structure to mitigate flooding attacks on a website, using a new web referral architecture for privileged service. This proposed scheme allows a legitimate client to obtain a privilege URL through a click on a referral hyperlink, from a website trusted by the target website. Using that URL, the client can get privileged access to the target website in a manner that is far less vulnerable to a DDoS flooding attack. The proposed solution does not require changes to web client software and is extremely lightweight for referrer websites, which eases its deployment. The massive scale of the web site graph could deter attempts to isolate a website through blocking all referrers.Item Eye State Detection of Driver(2018-06-19T11:34:48Z) BLESSINA D, JUTIKE; CHAITANYA, K; JYOTHI, MEye state detection of a driver system is an effective tool to reduce the number of road accidents. This project proposes a non-intrusive approach for detecting drowsiness in drivers, using Computer Vision. The algorithm is coded on OpenCV platform in Windows environment. The parameters considered to detect drowsiness are eye detection, blinking, eye closure and gaze. The input is captured from the camera and live fed the algorithm is Haar Classifier trained to detect the face and the eye from the incoming frame. Once the eye is detected,to track the eye and automatically set a dynamic threshold value. Depending on the values obtained from each of the incoming frames and deviations from the threshold values, eyelid closure/blink/gaze is detected. Warning system is designed to alert the driver. This system renders an efficient solution to road accidents and the cost of developing it into a real time system is also feasible when compared to the cost involved in the manufacture of car.Item Effective Method for Removing Intrusive and Incurs overhead by Map Reduce Program(2018-06-19T11:27:16Z) RAHUL, Y; SABIN, PANDEY; CHETHAN V, MUTTAGI; SUNIL, SINGHApache Hive is a widely used data warehousing and analysis tool. Developers write SQL like HIVE queries, which are converted into Map Reduce programs to run on a cluster. Despite its popularity, there is little research on performance comparison and diagnosis. Part of the reason is that instrumentation techniques used to monitor execution cannot be applied to intermediate Map Reduce code generated from Hive query. Because the generated Map Reduce code is hidden from developers, run time logs are the only places a developer can get a glimpse of the actual execution. Having an automatic tool to extract information and to generate report from logs is essential to understand the query execution behavior. We designed a tool to build the execution profile of individual Hive queries by extracting information from HIVE and Hadoop logs. The profile consists of detailed information about Map Reduce jobs, tasks and attempts belonging to a query. It is stored as a JSON document in Mongo DB and can be retrieved to generate reports in charts or tables. We have run several experiments on AWS with TPC-H data sets and queries to demonstrate that our profiling tool is able to assist developers in comparing HIVE queries written in different formats, running on different data sets and configured with different parameters. It is also able to compare tasks/attempts within the same job to diagnose performance issues.Item Big Data for Personalized Healthcare in Defence(2018-06-19T11:24:04Z) NAIMA, HUSSAIN; SRUTHI S, NAIREffective patient queue management to minimize patient wait delays and patient overcrowding is one of the major challenges faced by hospitals. Unnecessary and annoying waits for long periods result in substantial human resource and time wastage and increase the frustration endured by patients. For each patient in the queue, the total treatment time of all the patients before him is the time that he must wait. It would be convenient and preferable if the patients could receive the most efficient treatment plan and know the predicted waiting time through a mobile application that updates in real time. Therefore, we propose a Patient Treatment Time Prediction (PTTP) algorithm to predict the waiting time for each treatment for a patient. We use realistic patient data from various hospitals to obtain a patient treatment time model for each task. Based on this large-scale, realistic dataset, the treatment time for each patient in the current queue of each task is predicted. Based on the predicted waiting time, a Hospital Queuing-Recommendation (HQR) system is developed. HQR calculates and predicts an efficiency and convenient treatment plan recommended for the patient. Because of the large-scale, realistic dataset and the requirement for real-time response, the PTTP algorithm and HQR system mandate efficiency and low-latency response. We use an Apache Spark-based cloud implementation at the National Supercomputing Center in Changsha to achieve the aforementioned goals. Extensive experimentation and simulation results demonstrate the effectiveness and applicability of our proposed model to recommend an effective treatment plan for patients to minimize their wait times in hospitals.Item Secured Data Transfer Using Map Reduce Frame Work(2018-06-19T11:21:53Z) CHAITRA, N R; KAMYA, G; THILAK KUMAR, M; SHARADHA, B LInformation is developing at a huge rate in the present world. One of the finest and most famous advances accessible for taking care of and handling that gigantic measure of information is the Hadoop biological system. Undertakings are progressively depending on Hadoop for putting away their profitable information and handling it. In any case, Hadoop is as yet developing. There is much helplessness found in Hadoop, which can scrutinize the security of the touchy data that ventures are putting away on it. In this paper, security issues related with the system have been distinguished. We have additionally attempted to give a concise review of the at present accessible arrangements and what are their impediments. Toward the end a novel technique is presented, which can be utilized to kill the discovered vulnerabilities in the structure. In the cutting edge time, data security has turned into a basic need for every last person. Notwithstanding, not every person can manage the cost of the specific appropriations gave by various sellers to their Hadoop group. This paper shows a financially savvy method that anybody can use with their Hadoop group to give it 3-D security.Item Cryptography Assisted Key Distribution Using Cloud Computing(2018-06-19T10:48:34Z) ASHA, YADAV; DEBANJANA, DEY; SABNAM, PANDIT; KRITI, ARYALCloud computing it is the way to stores the data. It provides the data Storage at the high cost and at the faster rate as data is generated. It is costly among the persons who are using it as alone as the Hardware is costly.It help in building up a system that ensures promising environment providing security by implementing the techniques of cryptography and cloud computing. Applying the key distribution approaches during communication and at the same time protecting both security and efficiency is sometimes difficult.Protecting personal privacy and maintaining anonymity is also a major concern in the project.The cloud helps us to reduce the maintaining cost of the storage of data. Cloud storage moves large set of data from the users and the remotely located users.As we know cloud provides the security then it has to face the challenges imposed by the security and resolve them in the better manner. We provide a scheme which gives a proof of data integrity in the cloud which the customer can employ to check the correctness of his data in the cloud. This proof can be agreed upon by both the cloud and the customer and can be incorporated in the Service level agreement (SLA). We apply the methodology of Identity-Based Encapsulation Mechanism to establish communication using anonymous key distribution.“ICC” is an application it provides the security to data in the higher level of data.Item Suggesting an Area to Invest Using Decision Trees with Regression Algorithm in Machine Learning and Retrieving Data for Additional Decision Making by Using Textual Analysis In NLP(2018-06-19T10:45:36Z) SUCHIT, R; NIKILESH RAJ, N; KAUSHIK, JEYARAMANThe prime aim of this project is to suggest stocks to invest by using decision tree and regression algorithm in Machine Learning and enhance the decision making by performing textual analysis using NLP. We aim to develop a program which serves an accurate solution for suggesting stocks according to a predefined time interval and recommend investors to buy/sell to maximize profit. This is implemented by passing a list of companies through a classifier and sort them dynamically into various categories based on which historical data analysis or textual analysis is performed. Weights being assigned to different categories. The result is displayed in the front end and can be seen on the home page in the browser.Item SQL Injection Detection and Prevention Mechanism Coupled with Encryption to Secure Data on E-Commerce Website(2018-06-19T10:39:25Z) G, GAYATHRI; SUSHMITHA, KSQL injection (SQLi) is an application security weakness that allows attackers to control an application’s database – letting them access or delete data, change an application’s data-driven behaviour & other undesirable things. These weaknesses occur when an application uses untrusted data, such as data entered into web form fields, as part of a database query. When an application fails to properly sanitize this untrusted data before adding it to a SQL query, an attacker can include their own SQL commands which the database will execute. In this project we develop a SQLi attack detection and prevention system. The proposed solution is based on SQLi Signature detection and Anomaly detection approaches. The patterns of SQLi attacks are stored in database. When a web form either through POST or GET request is received, it is first sent to SQLi signature detection module to match if the request parameters has any SQL query patterns and if any pattern found, the FORM request is not processed and user is redirected to Failure response page. When there is no SQLi pattern , the user behaviour is collected in terms number of times he requested in a period of time, different source ip address it is requesting web pages and based on any abnormal behaviour threshold, the user is denied access to web page for certain duration. The proposed system of detection and prevention of SQLi is tested against a E-commerce web application. The E-commerce web application will have Forms for searching products, prices etc . SQLi attack is launched by typing SQL queries in these Forms and see the response of the server. The server response with and without proposed SQLi detection and prevention system will be demonstrated in this project. The project will be implemented as Web Framework GlassFish web server. The coding will be done using JAVA. The attack signatures are kept in a file , so new signatures can be added and the system can be improvised. The attack signatures are stored in encrypted way(Using AES) , so that it is not possible for any attacker to modify the attack signatures. This project will be very useful online shopping and e-commerce websites with Forms. Leakage of sensitive information in database due to SQL injection attack is prevented by using the proposed solution.Item Assisting Crop Selection for Farmer(2018-06-19T10:34:41Z) UMASHREE R, KADIWAL; MONISHA, V; SWATHI, M NIn Farming based countries like INDIA, it is required for farmers to predict the yield of crop to be planted well before planting. If yield can be predicted, farmers can calculate their profit margin and decide which crop to plant. The prediction is based on three macro factors rainfall, humidity and temperature. In this project, we propose a Neuro Fuzzy system to predict the yield of crop and a ARIMA model to predict the price of crop.Item Fast and Efficient Data Search in Hadoop(2018-06-19T10:32:01Z) T.POOJITHA, REDDY; MANDARA, B M; NANDITHA, NHadoop is the most popular implementation framework of the MapReduce programming model, and it has a number of performance-critical configuration parameters. However, manually setting these parameters to their optimal values not only needs in-depth knowledge on Hadoop as well as the job itself, but also requires a large amount of time and efforts. Automatic approaches have therefore been proposed. Their usage, however, is still quite limited due to the intolerably long searching time. In this proposed system, we introduce MapreducE Self-Adjusting (MESA), a framework that accelerates the searching process for the optimal configuration of a given Hadoop application. We have devised a novel mechanism by integrating the model trees algorithm with the genetic algorithm. As such, MESA significantly reduces the searching time by removing unnecessary profiling, modelling, and searching steps, which are mandatory for existing approaches. Our experiments using five benchmarks, each with two input data sets (DS1 and 2xDS1) show that MESA improves the searching efficiency (SE) by factors of 1.37x and 2.18x on average respectively over the state-of-the-art approach.Item Privacy Preserving Spam Detection Using Hadoop(2018-06-19T10:28:22Z) SANDEEP, SK; SAMBUDDHA, BISWAS; SAURABH, RAJNALASpam has become the platform of choice used by cyber-criminals to spread malicious payloads such as viruses and trojans. In this project, we consider the problem of early detection of spam campaigns. Existing collaborative spam detection techniques can deal with a lot of e-mail data contributed by various sources; however, they have a common and major problem of requiring disclosure of e-mail content. These hashes which preserve distance are one of the common solutions used for maintaining the privacy of the content of the e-mail while allowing the messages to get classified for detecting the spam. However, distance-preserving hashes are not scalable, thus making large-scale collaborative solutions difficult to implement. To solve this, in this project, we propose a method using Big Data which uses privacy-preserving collaborative spam detection platform built based on a standard Map Reduce facility. It uses a highly parallel encoding technique that enables the detection of spam campaigns in competitive times. The evaluation of our system’s performance is done using a huge elaborate spam base and show that our technique performs very well against the creation and delivery overhead of the current spam generation tools.Item Securing Folders Using Bluetooth and Rijndael Encryption Algorithm(2018-06-19T10:25:40Z) SANYA, DIKSHIT; SIMRAN, SINGH; RASHMI, RANJANSince the advent of the windows securing of the computer files and folders have been a core issue. Passwords were introduced to solve the issue but they themselves have a lot of disadvantages. In this project, we shall see what all drawbacks the passwords bring and how we can solve them. Also we shall propose a Two Factor Authentication system which uses a combination of Bluetooth and Rijndael Encryption Algorithm. Bluetooth is the most commonly used technology. Almost every phone has this feature and it provides Point to Point short range of communication of devices. Since the range of Bluetooth is less, it can be a good choice as a security mechanism. Rijndael algorithm is an Advanced Encryption standard. It is the most effective encryption and decryption algorithm. It is a symmetric algorithm as it uses same key for encryption and decryption. It has 10 rounds of encryption and variable key size with a minimum of 128 bits. The larger the key the more security it provides. Using a combination of above two will notonly reduce the disadvantages of passwords, but also create a user friendly security system.Item Securing Cloud Data Under Key Exposure(2018-06-19T10:22:59Z) BISHWAS, BELBASE; DHARMENDRA, KUSHWAHA; NITESH KUMAR, YADAV; ROSHAN, JIMIRecent news reveal a powerful attacker which breaks data confidentiality by acquiring cryptographic keys, by means of coercion or backdoors in cryptographic software. Once the encryption key is exposed, the only viable measure to preserve data confidentiality is to limit the attacker’s access to the ciphertext. This may be achieved, for example, by spreading ciphertext blocks across servers in multiple administrative domains—thus assuming that the adversary cannot compromise all of them. Nevertheless, if data is encrypted with existing schemes, an adversary equipped with the encryption key, can still compromise a single server and decrypt the ciphertext blocks stored therein. In this paper, we study data confidentiality against an adversary which knows the encryption key and has access to a large fraction of the ciphertext blocks. To this end, we propose Bastion, a novel and efficient scheme that guarantees data confidentiality even if the encryption key is leaked and the adversary has access to almost all ciphertext blocks.Item Enhanced Cloud Security using Multilevel Mechanism(2018-06-19T10:20:39Z) ATISH, OJHA; NIKI KUMAR SAH, KALWAR; SANGYAL, TSERING; SASWATA, CHANDRACloud computing has made an impact on the IT business by proving itself to be the role model for the next generation IT architecture. In divergence to the conventional solutions, where the IT facilities are under appropriate physical and staff office controls, cloud computing provides the flexibility of migrating the system software and databases to the remote data centres, where the management of the data and services may not be fully trustable. This unparalleled attribute, however, poses a good deal of new security challenges which have not been properly analysed. In this project, we specialize in cloud data storage security measures, which has always been an important factor when it comes to quality of service. To ensure the rightness of user's data in the cloud, we devise an efficient and flexible distributed scheme with two prominent features, opposing the conventional methods. By employing three levels of security which involves IP triggering, IP binding, and successful redirection, our schema prevents the misuse of users’ data on the cloud. Unlike most prior works, the new scheme further supports secure and efficient dynamic operations on chunks of data which includes: updating the data, deleting as well as append operations on data. Comprehensive security and performance analysis shows that the proposed scheme is highly efficient and provides an additional layer of security by the method of binding a file to the user’s IP address which prevents data modification attacks from unauthorized addresses and successful redirection to a fake file if in case the credentials are compromised.Item Measuring the Distance of an Object using the New DMES Algorithm(2018-06-19T10:17:51Z) VINAY, KHANDE; YASHILA, BASKAR; APARNA, R; SHWETHA, STThe Augmented Reality Virtual Measurement System aims at providing a vision to the user’s computer, this proposed software is being designed to provide a measuring scale system to the user by eliminating the traditional methods of measuring such as physical measuring attributes like the measuring tapes, wires, rulers or any other physical resources and instead replacing it with the advanced AR concept combined with the computer vision and object recognition which would make the process of measuring require little effort and futurist. The software uses the user’s web cam or any additional camera as its eyes to see the objects and the outstanding accessibility feature about the proposed system is that it would get adapted to any cam device that is connected with the system and it doesn't require any proprietary devices specifically designed for the proposed system. A simple laser light is used by the user to point the place up to which the distance from the system to the light pointer has to be measured, the laser light will be automatically detected by the software using the concepts of object tracking, computer vision and the distance will be shown up to the maximum focal length of the cam lens used which will be in the real time and will change in real time based on the movement of the pointer light and this futuristic feature of the proposed system is implemented through the concept of augmented reality. This proposed software would revolutionize the technology and along with that it would set a bench mark in measurement systems and in the fields of computer vision and augmented reality.Item Body Sensing Device with Authentication and Security(2018-06-19T10:14:24Z) SUPRIYA, P; UMESH, NAIK; VENKATESH, R; SANTHOSH PRABHU, PAdvances in information and communication technologies have led to the emergence of Internet of Things (IoT). In the modern health care environment, the usage of IoT technologies brings convenience of physicians and patients, since they are applied to various medical areas (such as real-time monitoring, patient information management, and healthcare management). The body sensor network (BSN) technology is one of the core technologies of IoT developments in healthcare system, where a patient can be monitored using a collection of tiny-powered and lightweight wireless sensor nodes. However, the development of this new technology in healthcare applications without considering security makes patient privacy vulnerable. In this paper, at first, we highlight the major security requirements in BSN-based modern healthcare system. Subsequently, we propose a secure IoT-based healthcare system using BSN, called BSN-Care, which can efficiently accomplish those requirements.Item Malware Testing Analysis using Fisher Linear Algorithm(2018-06-19T10:11:17Z) SANGHEETHA, G; SHIVANI, P; ROHIT, V; SHWETA, BARUAMalware has been recognized as one of the major security threats in the Internet. Previous researches have mainly focused on malware's internal activity in a system. However, it is crucial that the malware analysis extracts a malware's external activity toward the network to correlate with a security incident. We propose a novel way to analyze malware: focus closely on the malware's external (i.e., network) activity. A malware sample is executed on a sandbox that consists of a real machine as victim and a virtual Internet environment. Since this sandbox environment is totally isolated from the real Internet, the execution of the sample causes no further unwanted propagation. The sandbox is configurable so as to extract specific activity of malware, such as scan behaviors. We implement a fully automated malware analysis system with the sandbox, which enables us to carry out the large-scale malware analysis. We present concrete analysis results that are gained by using the proposed system. Malware analysis is a process to perform analysis of malware and how to study the components and behavior of malware. Malware analysis forms a critical component of cyber defense mechanism. In the last decade, lot of research has been done, using machine learning methods on both static as well as dynamic analysis. In this paper, we compare various machine-learning techniques used for analyzing malwares.Item Extracting Keywords from Data Set and Assigning Priorities For Popularity Analysis Using Classifier Algorithm(2018-06-19T10:07:22Z) SAHANA P, REDDY; GAGAN REDDY, N; GAGAN VINAY, HEGDESentiment analysis or opinion mining is one of the major tasks of NLP (Natural Language Processing). Sentiment analysis has gained much attention in recent years. Sentiment is an attitude, thought, or judgment prompted by feeling. Sentiment analysis which is also known as opinion mining, studies people’s sentiments towards certain entities. The main aim is to tackle the problem of sentiment polarity categorization, which is one of the fundamental problems of sentiment analysis. Given a piece of written text, the problem is to categorize the text into one specific sentiment polarity, positive or negative. A general process for sentiment polarity categorization is proposed with detailed process descriptions. Data used in this study are college reviews collected from unigo.com. Experiments for both sentence-level categorization and review-level categorization are performed with promising outcomes. However the data have several flaws that potentially hinder the process of sentiment analysis. The first flaw is that, since people can freely post their own content, the quality of their opinions cannot be guaranteed. The second flaw is that, the ground truth of such data is not always available. A ground truth is more like a tag of certain opinion, indicating whether the opinion is positive, negative, or neutral. There are three levels of sentiment polarity categorization, namely the document level, the sentence level, and the entity and aspect level. All the sentences were firstly tokenized into separated English words. The syntactic roles are also known as the parts of speech. In natural language processing, parts-of-speech (POS) taggers have been developed to classify words based on their parts of speech. The second process involves the sentiment score computation for the sentiment tokens. The sentiment score depicts the level of positivity or negativity of a particular sentiment word. Sentiment tokens and sentiment scores are information extracted from the original dataset. Then ratings for the colleges can be made by using those polarities. The efficiency or accuracy that can be achieved using sentiment analysis is about 60-70%Item Automation Script Development for Powerchart(2018-06-19T10:02:28Z) SAI RAMYA, S R; VISHWAS V, AITHAL; SAI SHREE, NAGIREDDYThe Project entitled “Automation Script Development for PowerChart” is automating the manual testing process currently in use. Automation is the use of strategies, tools and artifacts that augment or reduce the need of manual or human involvement or interaction in unskilled, repetitive or redundant tasks. Automation of plans are done using Organization’s tool called Touchstone 9.1. Touchstone 9.1 is an Organization’s internally-developed automation testing tool specifically used for UI and functional testing. Touchstone 9.1 used in creating automated regression tests to supplement or replace manual tests in order to complete testing faster and helps in insuring quality. The application PowerChart is a family of system solutions for a wide assortment of health care providers. As an electronic medical record system, PowerChart supports enterprise-wide viewing of clinical information and provides optimal patient care, it also does Capturing and retrieving discrete patient data, viewing the electronic patient record with the ability to locate discrete results, entering orders, documenting patient care activity, Managing the work day and patient assignments for health care professionals. The Market survey on Powerchart specifies for a particular client on ‘Allergies Documented’ Module on an Average of daily basis around 2560 users are using it. Touchstone 9.1 uses Object Oriented Methodology, where each control on the window is considered as an object. Automated software testing will allow the user to predefine actions, compare the results to the expected behavior and report the success or failure of these manual tests to a test engineer. Once automated tests are created they can easily be repeated and they can be extended to perform tasks impossible with manual testing. Because of this, many companies have found that automated software testing is an essential component of successful development projects. Automated Software Testing saves Time and Money, Improves Accuracy, Increases Test Coverage and Does What Manual Testing Cannot. Example: For an Associate 50 test plans in Manual testing it takes 4 weeks for completing whereas by automating the same it takes only 2 weeks by this there is a huge time line lifts.
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