FacialRecognitionSystemFormatPPT.pptx slide for introduction

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FacialRecognitionSystemFormatPPT for biometric authentication system


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NAME OF THE INSTITUTE, PARUL UNIVERSITY 1 “Facial Recognition System For Security” Title” Parul Institute of Engineering and Technology, PARUL UNIVERSITY

Broad Outline NAME OF THE INSTITUTE, PARUL UNIVERSITY Parul Institute of Engineering and Technology, PARUL UNIVERSITY 2 , Abstract Problem Statement Goal & Objective What is Facial Recognition?? What is Big Data?? What is Hadoop Architecture?? How is H adoop used in Big Data?? Why H adoop is being called as Big Data Technology?? What is Kerberos?? Workflow of Big Data Possible attacks on B ig D ata Literature Survey Conclusion References

A facial recognition system is a technology capable of matching a human face from a digital image or a video frame against a database of faces, typically employed to authenticate users through ID verification services , works by pinpointing and measuring facial features from a given image. NAME OF THE INSTITUTE, PARUL UNIVERSITY Parul Institute of Engineering and Technology, PARUL UNIVERSITY 3 Abstract

Abstract Big data is a field that treats ways to analyze, systematically extract information from, or otherwise deal with data sets that are too large or complex to be dealt with by traditional data-processing application software . Data with many fields (columns) offer greater statistical power , while data with higher complexity (more attributes or columns) may lead to a higher false discovery rate . Big data security is the collective term for all the measures and tools used to guard both the data and analytics processes from attacks, theft, or other malicious activities that could harm or negatively affect them. By adding facial recognition to the authentication process we are adding extra layer of security to access big data to legitimate users.

NAME OF THE INSTITUTE, PARUL UNIVERSITY Parul Institute of Engineering and Technology, PARUL UNIVERSITY 5 Problem Statement Attacks on big data systems – information theft, DDoS attacks, ransomware, or other malicious activities – can originate either from offline or online spheres and can crash a system. The consequences of information theft can be even worse when organizations store sensitive or confidential information like credit card numbers or customer information. Distributed Data Non-Relational Databases Endpoint Vulnerabilities Data Mining Solutions Access Controls

NAME OF THE INSTITUTE, PARUL UNIVERSITY Parul Institute of Engineering and Technology, PARUL UNIVERSITY 6 Goal & Objective Addressing Big Data Security Threats Security tools for big data are not new. They simply have more scalability and the ability to secure many data types. The list below explains common security techniques for big data. Encryption User Access Control Intrusion Detection and Prevention Centralized Key Management In a military context, its purpose is to identify, classify, verify, and if needed, neutralize any perceived threat. In the interest of security, this may seem a reasonable application.

NAME OF THE INSTITUTE, PARUL UNIVERSITY Parul Institute of Engineering and Technology, PARUL UNIVERSITY 7 What i s Facial Recognition ? Facial recognition is a way of identifying or confirming an individual’s identity using their face. Facial recognition systems can be used to identify people in photos, videos, or in real-time. Facial recognition is a category of biometric security . Other forms of biometric software include voice recognition, fingerprint recognition, and eye retina or iris recognition. The technology is mostly used for security and law enforcement, though there is increasing interest in other areas of use.

NAME OF THE INSTITUTE, PARUL UNIVERSITY Parul Institute of Engineering and Technology, PARUL UNIVERSITY 8 What is Big Data ? Big Data Technology can be defined as a Software-Utility that is designed to Analyze, Process and Extract the information from an extremely complex and large data sets which the Traditional Data Processing Software could never deal with. Big data is a field that treats ways to analyze, systematically extract information from, or otherwise deal with data sets that are too large or complex to be dealt with by traditional data-processing application software.

NAME OF THE INSTITUTE, PARUL UNIVERSITY Parul Institute of Engineering and Technology, PARUL UNIVERSITY 9 What is Hadoop Architecture ? The Hadoop architecture is a package of the file system, MapReduce engine and the HDFS (Hadoop Distributed File System). The MapReduce engine can be MapReduce/MR1 or YARN/MR2. A Hadoop cluster consists of a single master and multiple slave nodes.

NAME OF THE INSTITUTE, PARUL UNIVERSITY Parul Institute of Engineering and Technology, PARUL UNIVERSITY 10 How is Hadoop used in Big Data? Hadoop is an open-source software framework for storing data and running applications on clusters of commodity hardware. It provides massive storage for any kind of data, enormous processing power and the ability to handle virtually limitless concurrent tasks or jobs.

NAME OF THE INSTITUTE, PARUL UNIVERSITY Parul Institute of Engineering and Technology, PARUL UNIVERSITY 11 Why Hadoop is called a Big Data technology?? Hadoop is the Big Data operating system. Optimized for parallel processing using structured and unstructured data, using low hardware costs. Hadoop processing is in batch, not in real time, replicating the data through network, and maintaining fault tolerance.

NAME OF THE INSTITUTE, PARUL UNIVERSITY Parul Institute Of Engineering & Technology, PARUL UNIVERSITY 12

NAME OF THE INSTITUTE, PARUL UNIVERSITY Parul Institute Of Engineering & Technology, PARUL UNIVERSITY 13 What is Kerberos?? Kerberos is an authentication protocol which uses “tickets” to allow nodes to identify themselves. ... Hadoop can use the Kerberos protocol to ensure that when someone makes a request, they really are who they say they are. This mechanism is used throughout the cluster.

NAME OF THE INSTITUTE, PARUL UNIVERSITY PARUL INSTITUTE OF ENGINEERING AND TECHNOLOGY, PARUL UNIVERSITY 14

NAME OF THE INSTITUTE, PARUL UNIVERSITY PARUL INSTITUTE OF ENGINEERING AND TECHNOLOGY, PARUL UNIVERSITY 15

NAME OF THE INSTITUTE, PARUL UNIVERSITY PARUL INSTITUTE OF ENGINEERING AND TECHNOLOGY, PARUL UNIVERSITY 16 Fig: Work Flow Of Big Data

NAME OF THE INSTITUTE, PARUL UNIVERSITY Parul Institute of Engineering and Technology, PARUL UNIVERSITY 17 Possible attacks on Big Data : Zero-day exploit. DNS Tunneling.

NAME OF THE INSTITUTE, PARUL UNIVERSITY Parul Institute of Engineering and Technology, PARUL UNIVERSITY 18 Literature Survey Table I Literature Survey Approach Method Name Summary Limitations Future Work [14] PCA The PCA method has been extensively applied for the task of face recognition. Approximate reconstruction of faces in the ensemble was performed using a weighted combination of eigenvectors (Eigen pictures), obtained from that ensemble. Furthermore, if w decreases with non-negligible ratio as z does, then PCA fails to reproduce the original behavior of w. ... Also, time varying w can be confused with the incorrect value of constant one when the decreasing (or increasing) ratio of w is small but not negligible [14] LDA Linear Discriminant is a “classical” technique in pattern recognition [6], where it is used to find a linear combination of features which characterize or separate two or more classes of objects or events Fixed K (the number of topics is fixed and must be known ahead of time)Uncorrelated topics (Dirichlet topic distribution cannot capture correlations)Non-hierarchical (in data-limited regimes hierarchical models allow sharing of data)Static (no evolution of topics over time)  -

NAME OF THE INSTITUTE, PARUL UNIVERSITY Parul Institute of Engineering and Technology, PARUL UNIVERSITY 19 Cont.… [17] Hadoop Hadoop includes a fault‐tolerant storage system called the Hadoop Distributed File System, or HDFS. HDFS is able to store huge amounts of information, scale up incrementally and survive the failure of significant parts of the storage infrastructure without losing data. Hadoop creates clusters of machines and coordinates work among them Clusters can be built with inexpensive computers. If one fails, Hadoop continues to operate the cluster without losing data or interrupting work, by shifting work to the remaining machines in the cluster. Issue with Small Files. Hadoop does not suit for small data. ... Slow Processing Speed. ... Support for Batch Processing only. ... No Real-time Data Processing. Apache Spark Apache Flink Apache Pig [15] [16] MapReduce Map Reduce is a model for processing largescale data records in clusters. The Map Reduce programming model is based on two functions which are map() function and reduce() function Real-time processing.It's not always very easy to implement each and everything as a MR program. When your intermediate processes need to talk to each other(jobs run in isolation). Core parallel processing

NAME OF THE INSTITUTE, PARUL UNIVERSITY Parul Institute of Engineering and Technology, PARUL UNIVERSITY 20 [12] Kerberos  To integrate pluggable authentication providers, enhance desirable single sign on for end users, and enforce centralized access control on the platform, Hadoop community has widely discussed and concluded that token based authentication is the appropriate approach [18]. In this paper we discuss an innovation solution about how to implement the token authentication based on the Kerberos pre-authentication framework The Kerberos protocol is not as resistant to penetration as it should be. A number of weaknesses are apparent; the most serious is its use of an authenticator to prevent replay attacks. The authenticator relies on use of a timestamp to guard against reuse. Kerberos will provide ability to use strong encryption algorithms to protect passwords and authentication tickets. [19] Biometric approach to secure Big Data Biometrics is the science of establishing the identity of an individual based on the physical, chemical or behavioral attributes of the person. The relevance of biometrics in modern society has been reinforced by the need for large-scale identity management systems whose functionality relies on the accurate determination of an individual's identity in the context of several different applications  - Cont.…

NAME OF THE INSTITUTE, PARUL UNIVERSITY Parul Institute of Engineering and Technology, PARUL UNIVERSITY 21 Conclusion B iometric plays an important role in security and privacy of database in big data. There are various applications and results of biometrics tools used in safety measures systems. It has several benefits which can progress our lives such as improved protection and helpfulness, decreased fraud and password administrator rates, ease of use and create live more relaxed. Even though the biometrics security system motionless has various concern such as information confidentiality and physical privacy but users cannot deny the fact that this new tools will modify our lives for the enhanced. For a secure mechanism, face recognition, iris scan, palm recognition and fingerprint technology is more popular technologies are adopted by many companies to maintain and secure the user data.

NAME OF THE INSTITUTE, PARUL UNIVERSITY Parul Institute of Engineering and Technology, PARUL UNIVERSITY 22 References [1] K. Bakshi , "Considerations for Big Data: Architecture and Approach", Aerospace Conference IEEE, Big Sky Montana, March 2012. [2] C. Eaton, D. Deroos , T. Deutsch, G. Lapis and P.C. Zikopoulos , Understanding Big Data: Analytics for Enterprise Class Hadoop and Streaming Data, McGraw-Hill Companies, 978-0-07-179053-6, 2012. [3]http://blog.m2sys.com/biometrichardware/advanta gesbiometric - identification-management-system. [4] http://en.wikipedia.org/wiki/Biometrics. [5]http://www.webopedia.com/TERM/B/biometrics.h tm [6]http://searchsecurity.techtarget.com/definition/bio metrics. [7] V. Borkar, M.J. Carey and C. Li, "Inside ʊBig Data Management ۅ: Ogres, Onions, or Parfaits?” EDBT/ICDT 2012 Joint Conference Berlin Germany, 2012. [8] B.Gerhardt , K. Griffin and R. Klemann , "Unlocking Value in the Fragmented World of Big Data Analytics", Cisco Internet Business Solutions Group, June 2012, http://www.cisco.com/web/about/ac79/docs/sp/Infor mation-Infomediaries.pdf.

NAME OF THE INSTITUTE, PARUL UNIVERSITY Parul Institute of Engineering and Technology, PARUL UNIVERSITY 23 References [9] Vailaya , "What’s All the Buzz Around-Big Data", IEEE Women in Engineering Magazine, December 2012, pp. 24-31. [10] Bughin , J., Chui, M., Manyika , J.Clouds , Big Data, and Smart Assets: Ten Tech-Enabled Business Trends to Watch, McKinsey Quarterly, 2010, 56. [11] Bughin , J., Chui, M., Manyika , J.Clouds , Big Data, and Smart Assets Ten Tech-Enabled Business Trends to Watch, McKinsey Quarterly 2010, 56. [12] C. Tankard, "Big Data Security", Network Security Newsletter, Elsevier, ISSN 1353-4858, July 2012. [13] R. Weiss and L.J. Zgorski , "Obama Administration UnveilsʊBig Data Initiative: Announces $200 Million in new R&D Investments", Office of Science and Technology Policy Executive Office of the President, March 2012. [14]https://www.ijert.org/research/comparison-of-pca-and-lda-for-face-recognition-IJERTV2IS70818.pdf [15] https://www.researchgate.net/publication/304571542_A_Survey_Paper_on_Big_Data_Analytics_using_Map_Reduce_and_Hive_on_Hadoop_Framework_A_Survey_Paper_on_Big_Data_Analytics_using_Map_Reduce_and_Hive_on_Hadoop_Framework

NAME OF THE INSTITUTE, PARUL UNIVERSITY Parul Institute of Engineering and Technology, PARUL UNIVERSITY 24 References [16] https://www.researchgate.net/publication/281403776_Big_Data_And_Hadoop_A_Review_Paper [17] http://www.ijsrp.org/research-paper-1014/ijsrp-p34125.pdf [18] https://ieeexplore.ieee.org/abstract/document/7058096 [19] https://ieeexplore.ieee.org/document/7542296

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