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Item Recognizing and Handling the Malware Propagation in Large Scale Networks(2017-08-18T12:12:52Z) Shishir, Umesh; Recognizing and Handling the Malware Propagation in Large Scale, Networks; Shobhita, G HMalware is pervasive in networks, and poses a critical threat to network security. However, many people have very limited understanding of malware behavior in networks to date. The aim is to investigate how malware propagates in networks from a global perspective. The problem is formulated, and a rigorous two layer epidemic model for malware propagation from network to network is established. Based on the proposed model, the analysis indicates that the distribution of a given malware follows exponential distribution, power law distribution with a short exponential tail, and power law distribution at its early, late and final stages, respectively. Extensive experiments have been performed through two real-world global scale malware data sets, and the results confirm theoretical findings.Item A Project Report on Medication Provider Workspace(2017-08-18T12:09:26Z) Sivaranjani, JMedication provider workspace project is carried at “Cerner Healthcare Services Private Limited” Bengaluru. This system allows the clinicians to enter, order medical and non-medical services electronically. The primary objective of this application is to reduce the rate of medical errors that occurs in the manual process of transcription sharing across the clinical departments. Also this system replaces the traditional patient record management with Electronic Medical Records (EMR), which eliminates manual way of taking notes. Healthcare professionals must use a computerized medication provider tool to record and dispense the prescribed medicines to fulfil the meaningful use requirements. If it is done manually it results in time consumption and errors. Developing an efficient application will ensure a leading edge of care by submitting prior authorizations electronically. This reduces the administrative burden and help the patients to quickly get the medications that they need. It provides a shared access to critical medications and services. This ensures high availability and security while medication errors can be prevented. Thus ensuring “Right medication to the right patient”. Agile software development methodology is being used in this project which makes the process very flexible and evolving. [1]Item Deceloping a Web Automation Framework Using Selenium to Generate and Validate Business Objects Reports(2017-08-18T12:03:52Z) Samyuktha, PrabhuEDW/EXP is a Cerner’s proprietary solution which deals with ETL, Data Warehousing and Analytical Reporting. The Certification unit of the Solution is responsible for conducting package installation, functional and regression tests. A regression suite is designed to be executed as the last phase before signing and packaging of every release to the client. The current process, being manual, requires several hours/days of time and resource to automate report validation in SAP Business Objects 4.0 (Web). An automation framework to execute all the validation steps involved in the reporting will achieve more resource availability and cut down on several hours of effort.Success of test automation project is determined, among other factors, by its overall economy. Compared to manual test, creation of automated test is more expensive, but its execution is significantly less costly. Thus, when automated test is repeated certain number of times, it becomes less costly than manual test. This saved resource/time will be an opportunity to engage in further developing an enhanced methodology to finish the cycle, thereby, resulting in improved product delivery to the clients.Item Enterprise Vault and Remote connect(2017-08-18T11:58:55Z) Nirosh, PThis project entitled “Enterprise Vault and Remote Connect” is a web based tool that allows the users to easily manage passwords and connect to remote servers. It is primarily a password vault that allows the associates to store passwords of multiple remote servers. It functions as a search and connect tool that allows the associates to connect to the remote servers with just one click. The tool stores the password in a database in an encrypted format. Browser based password managers are convenient to use. However, if the passwords are stored in an unencrypted fashion, it is still possible to obtain those passwords maliciously thereby giving local access to servers. Hence encryption of the passwords is of high importance. Gaining remote access allows us to run the target machine completely by using our own machine, allowing for the transfer of files between the target and the host and such other functions.Item Electronics Medical Record Access: Enhancement of Power Chart Tool(2017-08-18T11:56:24Z) Chaitra, RaoCerner Corporation has a software called Millennium which consists of 78 applications. PowerChart, ExplorerMenu, Discern Visual Developer, Discern Layout Builder and Discern Prompt Builder are a few applications part of Millennium, among others. PowerChart is handled by doctors or nurses to access any medical record of a patient. The PowerChart application is currently being used to go through limited details of patients. The change requests will allow the physicians and nurses to access the entire Electronic Medical Record (EMR) of any patient in a more refined yet detailed level. It also allows the users to generate necessary reports. This project aims to enhance PowerChart by adding certain functionalities- to enable the users (Doctors, Nurses, Clinicians etc.) to search a patient using ‘Last Name’, EMR (Electronic Medical Record) number, MRN or FIN. It also adds functionalities allowing to select a tab as per the patient details required, generate the requirements of user in a prompt using the Discern Prompt Builder, lets the users filter the requirements and generate a report based on those requirements selected by the user. It allows the users to navigate different sections of the PowerChart easily, lets the users to filter the requirements and generate a report based on the requirements selected by the user. The report is generated using Discern Layout Builder in Excel format and PostScript format. Discern Visual Developer application is used to write CCL scripts, Discern Layout Builder is used to generate reports and Explorer Menu is used to provide the application to the clients.Item A Time Based Personalized Retail Recommender Strategy Using Data Mining(2017-08-18T11:52:55Z) R, Prasanna; Srinadh, DasakaE-commerce organisations are growing exponentially with time in terms of both Business and data. Recommendation algorithms are best known for their use only on e-commerce Websites where they use input about a customer’s interests to generate a list of recommended items. There is no good recommendation system used by the retail stores. The E-commerce platforms provide recommendations to the user based only on techniques such as clustering models and collaborative filtering which end up being the similar products or similar customers. The idea of collaborative filtering is in finding users in a community that share appreciations. If two users have same or almost same rated items in common, then they have similar tastes. Such users build a group or also called neighbourhood. In clustering model to find customers who are similar to the user, cluster models divide the customer base into many segments and treat the task as a classification problem. The algorithm’s goal is to assign the user to the segment containing the most similar customers. It then uses the purchases and ratings of the customers in the segment to generate recommendations. In all cases, recommendation quality is relatively poor. The recommendations are often either too general (such as best-selling drama DVD titles) or too narrow (such as all books by the same author). Recommendations should help a customer find and discover new, relevant, and interesting items and should recommend on a time basis. Time interval in recommending a product is very important. It helps to recommend a product at proper time. We have applied this technique on the retail store’s dataset. Customer’s historical bill details are analysed and a model is created for each customer. It helps to recommend them correct product at correct time. The recommendation will be more accurate than the traditional recommendation systems. The recommendation can be sent to the customer by email or sms.Item Adaptive Monitoring in Microkernel OS(2017-08-18T11:49:22Z) Priyadarshini, D; Sridevi, S; Sai Bhargavi, POperating Systems (OSs) are perhaps the most complex and critical part of the software stack in modern systems: they are made up of millions of lines of code (LoCs), provide fundamental services to user programs, and are tightly coupled with hardware resources. However, complexity raises concerns about dependability, since it is challenging to detect and fix software faults (bugs) in such a complex system within time-to-market constraints, as demonstrated by several studies on OSs failures occurring after release. Therefore, significant research efforts have been spent on dependable architectures for OSs, in order to mitigate the issue of software faults in the OS. (Microkernel) OS have a modular based architecture that can potentially be used for developing more dependable systems.Item Commercial Drone with Extended Applications(2017-08-18T11:43:48Z) Akarsh, M; Subhash, Reddy; Imad, Ahmed MThe current drone system that is available in the market is pre-programmed and expensive. Casual users have to spend high amounts of money to buy a stable drone which is limited to a few operations that are pre-programmed into its system. Serious users may have trouble buying a drone that will let them program their own functions into it and there lies the limitations in the current drone system. This project aims to provide a programmable drone at a low cost that allows users to type in their own code to program the Arduino Pro Mini into performing their own functions. A base C/C++ program can be easily manipulated into making the drone perform operations according to the user’s requirements. This feature of the low cost drone produced is shown in the project by making it respond to the user’s basic voice commands to control its flight pattern. Results of this project aim to show that a drone can be made at a lost cost which can be programmed in future systems with basic C/C++ commands on the drone’s Arduino Pro Mini. Keywords Programmable drone, Voice commands, flight pattern, Arduino Pro Mini.Item A Novel Method of Detecting and Tracking of Moving objects for Video Surveillance System(2017-08-18T10:20:42Z) Akshatha, K R; Chinmayi, K A; Harshitha MAutomated surveillance systems are of critical importance for the field of security. The task of reliably detecting and tracking moving objects in surveillance video, which forms a basis for higher level intelligence applications. Computer Vision is the part of “Artificial Intelligence” concerned with the theory behind artificial systems that extract information from images. Within which, Video Surveillance is a term given to monitor the behavior of any kind through videos. It requires person to monitor the CCTV and huge volume of memory to record it. One of the major challenges involved is the huge volume of video storage and retrieval of the same on demand. In order to avoid the depletion of human resources and to detect the suspicious behaviors that threaten safety and security, Intelligent Video Surveillance system (IVS) is required. The proposed work is focused on bringing effective and efficient video surveillance system with added intelligence to avoid human intervention in identifying security threats. The detection of moving object is one of the major steps in computer vision. We proposed a system with Gaussian Mixture Model (GMM) which is established on Background Subtraction and Morphological Filtering to enhance the image. Kalman Filter algorithm is used to track the moving objects. So, the proposed work is suitable for real time surveillance in detecting and tracking of moving objects.Item E-Mail Encryption Using AES and RSA Algorithm(2017-08-18T10:15:48Z) Aishwarya, B; Farheen, SultanaNow a day’s civilization is hugely dependent upon electronic and communication system. In this electronic world, increasing need of data protection in computer networks is necessary for the development of several cryptographic algorithms and to send data securely over a transmission link from one person to another .The Advanced Encryption Standard, or AES, is a symmetric block cipher to protect classified information and is implemented in software and hardware throughout the world to encrypt sensitive data. RSA is an asymmetric encryption system, it works with two different keys: A public and a private key and both work complementary to each other, which means that a message encrypted with one of them can only be decrypted by its counterpart. In this project we have used AES to encrypt the text data and then encrypted the AES key using RSA to achieve the combination of symmetric with asymmetric encryption thereby producing a hybrid encryption system that would overcome the drawbacks of algorithm simultaneously which when used individually would have its own disadvantages hence providing secure system without compromising speed.Item Inclusive Analysis of Incomplete Datasets Using 1Knn Search(2017-08-18T10:08:30Z) Sonia, Singh; Sujithra, K S; Supriya, PAnalyzing and processing any dataset is very important for any organization as it helps in making key business decisions of a organization and also increases the profit of any business organization. But these data sets also include incomplete data sets which are often eliminated in the preprocessing techniques. Here, incompleteness refers to the case where data has error or certain information is missing. In this project we focus only on missing data. Missing data exists due to failure of data transmission devices, accidental loss of data or improper storage. Although we can simply perform all the analysis tasks based on complete data sets by removing all the incomplete data, the analysis in incomplete and output is inaccurate. Given a dataset of multi-dimensional objects and a query object, finding k closest objects to the query from the dataset without discarding the incomplete data records (IkNN query) is a fundamental problem in data mining. This concept has its significant role in real time applications like image recognition, location based services, etc. Our objective of this project is to develop and present efficient indexes, pruning techniques and algorithms to support the execution of IkNN queries efficiently. We develop a front end for the data analyst to query the data set using java swing. The java code acts as a client to Rserve which is the backend server in our project. The Rserve accepts the query and executes the search algorithm and provides the k nearest neighbor object of the query to the data analyst. The algorithm uses LαB index, α-pruning and Distance pruning techniques to perform the search efficiently.Item Traffic Management Using Big Data Analytical Tool(2017-08-18T10:02:36Z) Prachi, Sahu; Roja, M H; Saranya, KrishnaTraffic congestion and accidents are one of the major concerns in almost every cities throughout the world. Almost 90 people on average lose their lives every day and more than 250 are injured every hour. Road safety could be enhanced by decreasing the traffic crashes. Traffic crashes cause traffic congestion as well, which has become unbearable, especially in mega-cities. In addition, direct and indirect loss from traffic congestion only is over $124 billion. The existence of the Big Data of traffic crashes, as well as the availability of Big Data analytics tools can help us gain useful insights to enhance road safety and decrease traffic crashes.Item Association Rule Based Product Recommendation Using Big Data(2017-08-18T09:56:17Z) Pavithra, K; Sumanth, Reddy MRecommender systems are integral part of any ecommerce store in order to sustain and compete with other growing businesses. There are various recommendation techniques which are used to appropriately recommend a product to the active user. The recommendation techniques like content-based recommendation system, collaborative recommendation system, context aware recommendation system, knowledge based recommendation have their own limitations which could be overcome by using hybrid systems. Also, these existing systems alone are enough to recommend products by analysing huge amount of data in the databases of the respective large retailer stores. The recommendation system has to analyse large amount of data to provide better recommendation and such important issue can be addressed using Hadoop ecosystem. In this paper, a recommendation system for product based on Hadoop framework is proposed. The proposed system recommend products to the user depending on the products present in the user cart. First, it uses framework to import the product transactions. Furthermore, the Apriori for finding frequent itemsets and Association rules are implemented in Hadoop and processing the data using MapReduce.Item Sentiment Analysis of Top Colleges in India Using Twitter Data(2017-08-18T09:50:01Z) Pallavi, S; Rachana, C; Ramya, K VIn today’s world, opinions and reviews accessible to us are one of the most critical factors in formulating our views and influencing the success of a brand, product or service. With the advent and growth of social media in the world, stakeholders often take to expressing their opinions on popular social media, namely twitter. While Twitter data is extremely informative, it presents a challenge for analysis because of its humongous and disorganized nature. This paper is a thorough effort to dive into the novel domain of performing sentiment analysis of people’s opinions regarding top colleges in India. Sentiment analysis deals with identifying and classifying opinions or sentiments expressed in source text. Social media is generating a vast amount of sentiment rich data in the form of tweets, status updates, blog posts etc. Sentiment analysis of this user generated data is very useful in knowing the opinion of the crowd. Twitter sentiment analysis is difficult compared to general sentiment analysis due to the presence of slang words and misspellings. Besides taking additional pre-processing measures like the expansion of net lingo and removal of duplicate tweets. Keyword: Sentiment analysis, machine learning, neural network, opinion mining, natural language processing, twitter.Item Map Reduce Based FiDoop(2017-08-18T09:39:36Z) Gagana, Vijayavarshini; Krithika, RaoExisting parallel mining algorithms for frequent itemsets lack a mechanism that enables automatic parallelization, load balancing, data distribution, and fault tolerance on large clusters. As a solution to this problem, we design a parallel frequent itemsets mining algorithm called FiDoop using the MapReduce programming model. To achieve compressed storage and avoid building conditional pattern bases, FiDoop incorporates the frequent items ultrametric tree, rather than conventional FP trees. In FiDoop, three MapReduce jobs are implemented to complete the mining task. In the crucial third MapReduce job, the mappers independently decompose itemsets, the reducers perform combination operations by constructing small ultrametric trees, and the actual mining of these trees separately.Item Clustering of Large Database in Hadoop(2017-08-18T09:35:43Z) Aditya, Srivastava; MD Faisal, Alam; Subikasha, NWith The growing trend of large volume of data generated everyday,storing and processing the data is a great challenge.The existing solutions like SAS,R,Excel and MapReduce prove to be inefficient.Mapreduce is a part of Apache Hadoop that allows distributive processing of unstructured data, where each distributive node has its own storage. Java serialization is not enough to convert the original message to binary format for a large volume of data,hence,hadoop uses its own serialization technique.Most of the algorithms are iterative in nature.But Mapreduce is a bane as it involves undesirable amount of read and writes to process such iterative algorithms.As an advancement,in this paper,we use the SPARK to implement algorithms like kmeans,linear regression etc on realtime data.Spark is an unified engine that can run Hadoop,Mesos,cloud or standalone.It stores the intermediate result in RAM,thus avoiding read/write from/to disk.Like the Mapreduce,Spark is used for batch processing.In adddition,Spark can be used to handle streaming data,queries and machine learning . It provides various libraries like SaprkSql (mixes the SQL queries with Spark programs) , MLlib (contains algorithms for classification,clustering,regression and so on) and Sparkstreaming (to feed stream data to sprak rograms).In this paper,we prefer to use the cloud services to access the large datasets because cloud is flexible,scalable and ivolves less hardware cost than using our own infrastructure which requires many softwares (hadoop,ubuntu,java etc) to be installed.Once the data is obtained,we then run and evaluate the K-means algorithm on Spark using EMR (Elastic MapReduce) and compare the performance against executing the same algorithm using Mapreduce.Item Intelligent Agriculture Greenhouse Environment Monitoring Based on IoT Technology(2017-08-18T09:31:07Z) Sandeep, K R; Thomas, Joseph; Sree Darshan, DAgriculture is the backbone of the Indian economy. Monitoring and control of greenhouse environment play an significant role in greenhouse environment. The introduction of automated greenhouse monitoring system can bring a green revolution in agriculture. In recent years greenhouse technology is to automate, information technology direction in the IOT (Internet Of Things) technology rapid development and wide application. Introducing this system can help in increasing the cultivation in a controlled environment. Greenhouse environment, used to grow crops, plants under controlled climatic condtions for efficient production, forms an important part of the agriculture sectors. Appropiate environmental conditions are necessary for optimum plant growth, improved crop yields, and efficient use of water and other resources. Automating the data acquisition process of the soil conditions and various climatic parameters that govern plant growth allows information to be collected with less labor requirements. The integration of traditional methodology with latest technologies like Internet of Things can lead to agricultural modernization. Keeping this scenario in our mind we have designed, tested and analyzed an ’Internet of Things’ based device which is capable of analyzing the sensed information and then transmitting it to the user. This device can be controlled and monitored from remote location and it can be implemented in agricultural fields, grain stores and cold stores.Item Dynamic Smart Parking System Using IoT(2017-08-18T09:26:45Z) Abhishek, A; Goutham, GThe number of vehicles are increasing day by day and it is very hard for the driver to find a parking space among few. Finding a vacant parking space is time and fuel consuming. This problem may cause drivers to get frustrated and eventually improper parking will appear. This will cause traffic jam in the parking spaces and accident might occur. Hence, we propose a smart parking system that provides the information of available parking spaces to the drivers according to their profile and the details provided. Smart parking system helps drivers to find and park their vehicle in cost effective manner. This solves the problem stated above as users get to choose the parking space and this will feed the information of vacant spaces available to users so to prevent users to wander around at the parking lot. As a result, this will help reduce traffic jams and improper parking in the parking spaces in the futureItem Malware Detection in Cloud Computing infrastructures(2017-08-18T09:23:21Z) Nimith, Shetty M; Kishan V, Reddy; Kaushik C, ReddyCloud datacenters are beginning to be used for a range of always-on services across private, public and commercial domains. These need to be secure and resilient in the face of challenges that include cyber-attacks as well as component failures and mis-configurations. However, clouds have characteristics and intrinsic internal operational structures that impair the use of traditional detection systems. In particular, the range of beneficial properties offered by the cloud, such as service transparency and elasticity, introduce a number of vulnerabilities which are the outcome of its underlying virtualized nature. Moreover, an indirect problem lies with the cloud’s external dependency on IP networks, where their resilience and security has been extensively studied, but nevertheless remains an issue. The approach taken here relies on the principles and guidelines provided by an existing resilience framework. The underlying assumption is that in the near future, cloud infrastructures will be increasingly subjected to novel attacks and other anomalies, for which conventional signature based detection systems will be insufficiently equipped and therefore ineffective. Moreover, the majority of current signature-based schemes employ resource intensive deep packet inspection (DPI) that relies heavily on payload information where in many cases this payload can be encrypted, thus extra decryption cost is incurred. Our proposed scheme goes beyond these limitations since its operation does not depend on a-priori attack signatures and it does not consider payload information, but rather depends on per-flow meta-statistics as derived from packet header and volumetric information (i.e. counts of packets, bytes, etc.). Nonetheless, we argue that our scheme can synergistically operate with signature-based approaches on an online basis in scenarios were decryption is feasible and cost-effective. Overall, it is our goal to develop detection techniques that are specifically targeted at the cloud and integrate with the infrastructure itself in order to, not only detect, but also provide resilience through remediation. At the infrastructure level we consider: the elements that make up a cloud datacenter, i.e. cloud nodes, which are hardware servers that run a hypervisor in order to host a number of Virtual Machines (VMs); and network infrastructure elements that provide the connectivity within the cloud and connectivity to external service users.Item Cost Effective Index Poisoning Scheme for P2P File Sharing System(2017-08-17T12:28:17Z) Kretthika, P; Siraj Ul, Muneera S; Vinutha, Yadav DLiterature survey is mainly carried out in order to analyze the background of the current project which helps to find out flaws in the existing system & guides on which unsolved problems we can work out. So, the following topics not only illustrate the background of the project but also uncover the problems and flaws which motivated to propose solutions and work on this project. A variety of research has been done on power aware scheduling. Following section explores different references that discuss about several topics related to power aware scheduling.