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There are many biometric authentication methods such as face, finger print, iris, hand, veins, keystroke, signature, voice based authentication .Among that face recognition based research has been chosen under cost and time consuming factors.The main objective of the face recognition research is to recognize a sample face from a set of given authenticated student faces in order to provide more security. In this project principle component analysis (Eigen face approach) is applied to recognize a student face that is a face under different lightening and emotional condition. For comparison and experimental analysis simple approach such as user name and password based authentication and finger print based authentication are used. The final result is analysed and the face recognition method produces best result. The present invention of face recognition based authentication involves two phases such as, face detection which is the primary process and face recognition which is an authenticating phase. Face detection involves four main concepts. Firstly, face localization which separates parameter space and object space using Hough method and skin color information method[4]. The Second step is face normalization which extracts only the face by discarding all the surroundings. Third step is to locate facial characteristics using neural network .Finally the student face is extracted using Eigen face approach. After extracting the features of the face, all these features will be basically stored as a template that will be used for recognition. In recognition phase, the student face is captured and checked for authentication. Only if the face matches with the store template the student will be allowed for the examination. Like single face recognition multi face recognition system uses principle component analysis (PCA) technique[1]. To perform PCA five steps to be undertaken. The first step is subtracting the Mean of the data from each variable. The second step is calculating and forms a covariance Matrix. The third step is calculating Eigenvectors and Eigen values from the covariance Matrix. The fourth step is to choose a Feature Vector. Final step is multiply the transposed Feature Vectors by the transposed adjusted data.

Hough Method, Face Color Information Method, Adaboosting method, Normalization, Normalization, Neural Network, Eigen Face Approach

[1] A. Gunjan Dashore, B. Dr. V.Cyril Raj, 2012 , An Efficient Method For Face Recognition Using Principal Component Analysis (Pca), Volume 2, Issue 2, (IJATER) pp:23-28.
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K.Kanimozhi and M.Sakthivel , "Biometric Authentication for Online Examination," International Journal of Computer Sciences and Engineering, Vol.3, Issue.9, pp.162-164, 2015.

By finding the most important medical symptoms and laboratory data helps in building an expert system to predict the dengue fever in early stages. We developed in this project a new expert system to predict the dengue fever in early stages. This methodology consists of three important steps: a) manual missing value imputation method is applied that makes the data consistent. b) An expert doctors opinion is taken for selecting most influential attributes for dengue fever also we done internet survey . c) A neural network model is used for accurate prediction of dengue fever. The expert system is developed using MATLAB 2013. This methodology is seems to be giving good predictive results compared to other techniques.

Dengue Fever, Expert system, Neural Network, Prediction

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[3] Thitiprayoonwongse, Prapat Suriaphol and Nuanwan Soonthornphisaj Data Mining of Dengue Infection Using Decision Tree Daranee Latest Advances in Information Science and Applications, ISBN: 978-1-61804-092-3
[4] Revathi N. Prof.S.J.K.Jagadeesh Kumar Genetic lgorithm Optimization And Neural Network For The Diagnosis of Disease. International Journal of Computer Applications & Information Technology Vol. II, Issue I,. January 2013 (ISSN: 2278-7720)
[5] L. Tanner, M. Schreiber, J.G. Low, A. Ong, T. Tolfvenstam, Y.L. Lai, L.C. Ng, Y.S. Leo, L. Thi uong, S.G. Vasudevan, C.P. Simmons, M.L. Hibberd and E.E. Ooi, Decision Tree Algorithms Predict the Diagnosis and Outcome of Dengue Fever in the Early Phase of Illness,PLoS Neglected Tropical Disease, Vol.2, 2008.
[6] T. Faisal, F. Ibrahim and M.N. Taib, A noninvasive intelligent approach for predicting the risk in dengue patients, Expert Systems with Application,Vol.37, No.3, 2010, pp. 2175- 2181.
[7] F. Ibrahim, M. N Taib, W. A. B. Wan Abas, C. G. Chan and S. Sulaiman, A novel dengue fever (DF) and denguehaemorrhagic fever (DHF) analysis using artificial neural network (ANN), Computer Methods and Programs in Biomedicine, No.79, 2005, pp. 273-281.
[8] Md. Nazmul Karim, Saif Ullah Munshi*, Nazneen Anwar & Md. Shah Alam**. “Climatic factors influencing dengue Cases in Dhaka city: a model for dengue prediction”. Indian J Med Res 136, July 2012, pp 32-39.
[9] Anna L Buczak*, Phillip T Koshute, Steven M Babin, Brian H Feighner and Sheryl H Lewis Buczak et al “A data- Driven epidemiological prediction method for dengue outbreaks using local and remote sensing data.” BMC Medical Informatics and Decision Making 2012, 12:124
[10] Vadrevu Sree Hari Rao, Senior Member,IEEE, and Mallenahalli Naresh Kumar “A New Intelligence- Based Approach for Computer-Aided Diagnosis of Dengue Fever”.IEEE Transactions on information Technology in biomedicine. Vol. 16, no. 1, January- 2012.
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M.V.Jagannatha Reddy and B.Kavitha, "Expert System to Predict the Type of Fever Using Data Mining Techniques on Medical Databases," International Journal of Computer Sciences and Engineering, Vol.3, Issue.9, pp.165-171, 2015.

Networks composed of mobile nodes inherently suffer from intermittent connections and high delays. Performance can be improved by adding supporting infrastructure, including base stations, meshes, and relays, but the cost-performance trade-offs of different designs is poorly understood. To examine these trade-offs, we have deployed a large-scale vehicular network and three infrastructure enhancement alternatives. Mobile ad-hoc networks (MANETs) are ideal for situations where a fixed infrastructure is unavailable or infeasible. Today’s MANETs, however, may suffer from network partitioning. This limitation makes MANETs unsuitable for applications such as crisis management and battlefield communications, in which team members might need to work in groups scattered in the application terrain. In such applications, inter-group communication is crucial to the team collaboration. To address this weakness, we introduce in this paper a new class of ad-hoc network called Autonomous Mobile Mesh Network (AMMNET). We propose a distributed client tracking solution to deal with the dynamic nature of client mobility, and present techniques for dynamic topology adaptation in accordance with the mobility pattern of the clients. Our simulation results indicate that AMMNET is robust against network partitioning and capable of providing high relay throughput for the mobile clients.

Mobile Mesh Networks, Dynamic Topology Deployment, Client Tracking

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[2] L. Nuaymi, WiMAX: Technology for Broadband Wireless Access. John Wiley & Sons, 2007.
[3] K. Fall, “A Delay-Tolerant Network Architecture for Challenged Internets,” Proc. ACM Special Interest Group on Data Comm., 2003.
[4] A. Petkova, K.A. Hua, and S. Koompairojn, “Processing Approximate Rank Queries in a Wireless Mobile Sensor Environment,”Proc. 11th Int’l Conf. Mobile Data Management (MDM), 2010.
[5] “Quadrocopter LLC,” http://quadrocopter.us/, 2013.
[6] R. Roy, Handbook of Mobility Models and Mobile Ad Hoc Networks.Springer, 2010.
[7] Y.-C. Chen, E. Rosensweig, J. Kurose, and D. Towsley, “Group Detection in Mobility Traces,” Proc. Sixth Int’l Wireless Comm. And Mobile Computing Conf. (IWCMC ’10), 2010.
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N Venkata Santhi and D Kumar, "Sovereign Mobile Mesh Networks," International Journal of Computer Sciences and Engineering, Vol.3, Issue.9, pp.172-177, 2015.

This system describe talkable hand glove system which aims at translation of sign language to analyze text and voice. This system consists of a talk able glove that can be worn by a deaf/dumb person to facilitate the communication in real-time with other people. The system translates the hand finger motion to corresponding letters using IR sensors and a Microcontroller. Our main goal is to identify 26 alphabets and display text on the LCD. Once the text is obtained on the LCD then text to speech conversion operation is carried out and finally a voice output is obtained. Further, the text gain can also be viewed on a LCD or any portable hand held device. Our main aim is to set an interface between the Deaf or Dumb and normal people to improve the communication capabilities so that they can communicate handily with others. We mount IR sensor on the talk able hand glove and propose and efficient methodology to convert these sign languages. This system will simplify the communication of deaf or dumb people with people able to normal communications without the need of a human translator

IR sensor,H12E encoder,H12D decoder,Transmitter,Receiver

[1]. Bhavina Patel, Vandana Shah, Ravindra Kshirsagar: ”Microcontroller Based Gesture Recognition System For The Handicap People”, JERS/Vol. II/ Issue IV/ 113-115/ October-December, 2011
[2]. Kuldeep Singh Rajput ,Shashank Deshpande,Uma Mudenagudi :“Interactive Accelerometric Glove For Hearing Impaired”, AIML Journal, vol. 7, 2013
[3]. Gourab Talukdar,Omkar Gondhalekar: “Hand Gesture Recognition System”, International Journal of Scientific and Research Publications, Volume 4, Issue 2,SSN 2250-3153,Feb 2014
[4]. Gunasekaran Manikandan : “Sign Language To Speech Translation System Using PIC Microcontroller”, International Journal of Engineering and Technology, ISSN : 0975-4024 Vol 5,No 2,Apr-May 2013.
[5]. Priyanka Lokhande , Riya Prajapati: “Data Gloves for Sign Language Recognition System”, International Journal of Computer Applications (0975 – 8887),March 2015
[6]. Gunasekaran. K1, Manikandan. R2: “ Sign Language to Speech Translation”,2014

Bodke Sulakshana, Alai Gayatri, Shinde Dipali, Pawar Sonali, "Glove to Translate Sign Language," International Journal of Computer Sciences and Engineering, Vol.3, Issue.9, pp.178-180, 2015.

Cloud computing is provide a dynamically scalable resources provisioned as a service over the webpage. The third-party, on-demand, self-service, pay-per-use, and seamlessly scalable computing resources and services offered by the cloud environment promise to reduce capital as well as operational expenditures for hardware and software. Various distinct architectures are introduced and discussed according to their security and privacy capabilities and prospects. It provides four distinct models in form of abstracted multi-cloud architectures. These developed multi cloud architectures allow to categorize the available schemes and to analyze them according to their security reimbursement. An assessment of the different methods replication of applications, partition of application system into tiers, partition of application logic into fragments and partition of application data into fragments is given in particular. In addition, enabling public audit ability for cloud storage is of critical importance so that users can resort to an Integrity third party auditor (ITPA) to check the integrity of outsourced data and be worry-free. This paper proposes a secure cloud storage system supporting Isolation-preserving public auditing. It further extends the result to enable the ITPA to perform audits for multiple cloud users simultaneously and efficiently.

Cloud Computing, Multi-cloud, Integrity, Isolation Preserving Auditing, ITPA

[1] S. Bugiel, S. Nurnberger, T. Poppelmann, A.-R. Sadeghi, and T.Schneider, ―AmazonIA: When Elasticity Snaps Back,‖ Proc. 18th ACM Conf. Computer and Comm. Security (CCS ’11), pp. 389-400, 2011.
[2] Amazon Elastic Compute Cloud (Amazon EC2).http://aws.amazon.com/ec2/.
[3] D. Catteddu (Ed.): Security & Resilience in Governmental Clouds – Making an informed decision. ENISA Report, January 2011.
[4] J. Somorovsky, M. Heiderich, M. Jensen, J. Schwenk, N. Gruschka, and L. Lo Iacono, ―All Your Clouds Are Belong to Us: Security Analysis of Cloud Management Interfaces,‖ Proc. Third ACM Workshop Cloud Computing Security Workshop (CCSW ’11), pp. 3-14, 2011.
[5] P. Mell and T. Grance: The NIST Definition of Cloud Computing (Draft). Recommendations of the National Institute of Standards and Technology (NIST), Special Publication 800—145 (Draft), available at http://csrc.nist.gov/publications/drafts/800-145/Draft-SP-800-145_cloud-definition.pdf, January 2011.
[6] G. Danezis and B. Livshits, ―Towards Ensuring Client-Side Computational Integrity (Position Paper),‖ Proc. ACM Cloud Computing Security Workshop (CCSW ’11), pp. 125-130, 2011.

S.Sujitha and S. J. Mohana, "Secure Data Storage and Retrieval Using Adaptive Integrity Protocol Model in Cloud Environment," International Journal of Computer Sciences and Engineering, Vol.3, Issue.9, pp.181-184, 2015.

Most of us use android phones these days and also uses the multiple applications and facilities frequently. Play store provides great number of application but unfortunately few of those applications are fraud. Such applications dose damage to phone and also possibly data thefts. Hence such applications must be marked, so that they will be recognizable for play store users. So we are proposing a web application which will process the information, comments and the reviews of the application on cloud server. As we are handling the big data here so the process is done on cloud server and malware is detected. So it will be easier to decide which application is fraud or not. Multiple applications can be processed at a time with the web application.

Android, Permissions, Security, Instrumentation, Privacy, Risk assessment

[1] W. Enck, M. Ongtang, and P. McDaniel, “On lightweight mobile phone application certification,” in Proc. 16th ACM Conf. Comput. Commun. Security, 2009, pp. 235–245.
[2] B. P. Sarma, N. Li, C. Gates, R. Potharaju, C. Nita-Rotaru, and I. Molloy, “Android permissions: A perspective combining risks and benefits,” in Proc. 17th ACM Symp. Access Control Models Technol., 2012, pp. 13–22.
[3] H. Peng, C. Gates, B. Sarma, N. Li, Y. Qi, R. Potharaju, C. Nita- Rotaru, and I. Molloy, “Using probabilistic generative models for ranking risks of Android apps,” in Proc. ACM Conf. Comput. Commun. Security, 2012, pp. 241–252.
[4] Ali K, Lhot_ak O. Application-only call graph construction. In:Proceedings of the 26th European onference onObject-Oriented Programming. Springer-Verlag; 2012.p. 688e712. “A tool for reverse engineering android apk files.”
[5] A.-D. Schmidt, R. Bye, H.-G. Schmidt, J. Clausen, O. Kiraz, K. A. Yuksel, S. A. Camtepe, and S. Albayrak, “Static analysis of executables for collaborative malware detection on Android,” in Proc. IEEE Int. Conf. Commun., 2009, pp. 1–5.
[6] I. Burguera, U. Zurutuza, and S. Nadjm-Tehrani, “Crowdroid: Behavior-based malware detection system for Android,” in Proc. 1st ACM Workshop Security Privacy Smartphones Mobile Devices, 2011, pp. 15–26.

Sangita Mahajan, Suvarna Sangle and Gayatri Khairnar, "To develop an application in android for smart phones tasks processing to the cloud to detect malware in application and generate reports," International Journal of Computer Sciences and Engineering, Vol.3, Issue.9, pp.185-188, 2015.

Secure File Storage System is application to provide security to user for protect his file and also share file bin categorize we will implement some module like data storage module, data encryption module and data retrieval module and facilitate main storage and secondary storage. Now the massive quantity of expanding industrial atmosphere each and everything depends on the other sources to broadcast the data strongly and maintain the data as well in the frequent medium. Convenient nodes in military surroundings, for example, a frontage line or a hostile area are prone to experience irregular system network and common partition. Disruption-tolerant network (DTN) improvement are getting to be productive results that allow remote device get across by officers to tell with other and access the private data consistently by exploitation external capacity nodes or storage nodes. The new approach is to offer effective communication beside to another also access the different information supply through various key establishments like commander or other superiors. This system offer competent scenario for approval strategy and the strategy renew for protected data salvage in most demanding situation. The most assure cryptographic result is commenced to manage the access RSA algorithm.

Secure storage, RSA algorithm, disruption-tolerant network (DTN), multiauthority, data retrieval, data encryption, data decryption

[1] Ieee Transactions On Networking Vol:22 NO:1 YEAR 2014 Secure Data Retrieval for Decentralized Disruption-Tolerant Military Networks Junbeom Hur and Kyungtae Kang, Member, IEEE, ACM.
[2] M. Chuah and P. Yang, “Node density-based adaptive routing scheme for disruption tolerant networks,” in Proc. IEEE MILCOM, 2006, pp.1–6.
[3] M. M. B. Tariq, M. Ammar, and E. Zequra, “Mesage ferry route design for sparse ad hoc networks with mobile nodes,” in Proc. ACM MobiHoc, 2006, pp. 37–48.
[4] S. Roy andM. Chuah, “Secure data retrieval based on ciphertext policy attribute-based encryption (CP-ABE) system for the DTNs,” Lehigh CSE Tech. Rep., 2009.
[5] M. Chuah and P. Yang, “Performance evaluation of content-based information retrieval schemes for DTNs,” in Proc. IEEE MILCOM, 2007, pp. 1–7.
[6] M. Kallahalla, E. Riedel, R. Swaminathan, Q. Wang, and K. Fu, “Plutus: Scalable secure file sharing on untrusted storage,” in Proc.Conf. File Storage Technol., 2003, pp. 29–42.
[7] L. Ibraimi, M. Petkovic, S. Nikova, P. Hartel, and W. Jonker, “Mediated ciphertext-policy attribute-based encryption and its application,” in Proc. WISA, 2009, LNCS 5932, pp. 309–323
[8] N. Chen, M. Gerla, D. Huang, and X. Hong, “Secure, selective group broadcast in vehicular networks using dynamic attribute based encryption,” in Proc. Ad Hoc Netw. Workshop, 2010, pp. 1–8.
[9] D. Huang and M. Verma, “ASPE: Attribute-based secure policy enforcement in vehicular ad hoc networks,” Ad Hoc Netw., vol. 7, no. 8, pp. 1526–1535, 2009.
[10] A. Lewko and B. Waters, “Decentralizing attribute-based encryption,”CryptologyePrint Archive: Rep. 2010/351, 2010.
[11] A. Sahai and B. Waters, “Fuzzy identity-based encryption,” in Proc.Eurocrypt, 2005, pp. 457–473.
[12] V. Goyal, O. Pandey, A. Sahai, and B. Waters, “Attribute-based encryption for fine-grained access control of encrypted data,” in Proc.ACM Conf. Comput. Commun. Security, 2006, pp. 89–98.
[13] J. Bethencourt, A. Sahai, and B. Waters, “Ciphertext-policy attribute based encryption,” in Proc. IEEE Symp. Security Privacy, 2007, pp.321–334.
[14] M. Chase and S. S. M. Chow, “Improving privacy and security in multi authority attribute-based encryption,” in Proc. ACM Conf. Comput. Commun. Security, 2009, pp. 121–130.
[15] L. Cheung and C. Newport, “Provably secure ciphertext policy ABE,” in Proc. ACM Conf. Comput. Commun. Security, 2007, pp. 456– 465.
[16] S. Yu, C. Wang, K. Ren, and W. Lou, “Attribute based data sharing with,” in Proc. ASIACCS, 2010, pp. 261–270.
[17] M. Pirretti, P. Traynor, P. McDaniel, and B. Waters, “Secure attribute based systems,” in Proc. ACMConf. Comput. Commun. Security, 2006, pp. 99–112.

Pawar Amol, Sonawane Ajay, Nandan Pravin and Ingole Shubham, "Secure File Storage System for Disruption-Tolerant Military Environment," International Journal of Computer Sciences and Engineering, Vol.3, Issue.9, pp.189-192, 2015.

In this study, we present a brief overview of Named Entity Recognition (NER) system, various approaches followed for NER systems and finally NER systems for Kashmiri language. Kashmiri language raises several challenges to Natural Language Processing (NLP) largely due to its rich morphology. Named entity recognition (NER) (also known as entity identification and entity extraction) is one of the important subtask of information extraction that seeks to locate and classify atomic text into predefined categories such as the names of persons, organizations, locations, monetary values, percentages, expressions of times, etc. This paper describes the problems of NER in the context of Kashmiri Language and provides relevant solutions by using noun identification algorithm and named entity recognition identification algorithm Building a named entity recognition system for Kashmiri languages that can understand Kashmiri language has been one of the long-standing goals of (NER) system.

Named Entity Recognition, Natural Language Processing, Noun Identification, NER Identification, Kashmir language

[01] Vishal Gupta, Gurpreet Singh Lehal, “Named Entity Recognition for Punjabi Language Text Summarization”. International Journal of Computer Applications (0975 – 8887) Volume 33– No.3, November 2011.
[02] NavneetKaurAulakh, Er.YadwinderKaur. “Review Paper on Name Entity Recognition of Machine Translation”.International Journal of Advanced Research in Computer Science and Software Engineering ISSN: 2277 128X Volume 4, April 2014
[03] Kamal deep Kaur, Vishal Gupta. “Name Entity Recognition for Punjabi Language”.International Journal of Computer Science and Information Technology & Security (IJCSITS), ISSN: 2249-9555 Vol. 2, No.3, June 2012.
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[06]YassineBenajiba, Paolo Rosso, and Jos´e Miguel Bened´ıRuiz, 2013.” NER system built exclusively for Arabic texts based-on n-grams and maximum entropy” april2013
[07]SudhaMorwal, and NusratJahan. “Named Entity Recognition Using Hidden Markov Model (HMM): An Experimental Result on Hindi, Urdu and Marathi Languages”. International Journal of Advanced Research in Computer Science and Software Engineering ISSN: 2277 128X Volume 3, Issue 4, April 2013
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[09] Pallavi, Dr. Anitha S Pillai. “Named Entity Recognition for Indian Languages: A Survey”. International Journal of Engineering and Advanced Technology (IJEAT) ISSN: 2277 128X, Volume 3, November 2013
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[12] Pallavi, Dr. Anitha S Pillai. “Named Entity Recognition for Indian Languages: A Survey”. International Journal of Engineering and Advanced Technology (IJEAT) ISSN: 2277 128X, Volume 3, November 2013 Acquisition, pp. 21-39.
[13]https://daim.idi.ntnu.no/masteroppgaver/005/5654/masteroppgave.
14]GitimoniTalukdar, and PranjalProtim Borah. “A Survey of Named Entity Recognition in Assamese and other Indian Languages”.International Journal on Natural Language Computing (IJNLC) Vol. 3, No.3, June 2014
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[16] S Amarappa, Dr. S V Sathyanarayana. “Named Entity Recognition and Classification in Kannada Language”. International Journal of Electronics and Computer Science Engineering, ISSN- 2277-1956 November 2012.

Amir Bashir Malik and Khushboo Bansal, "Named Entity Recognition for Kashmiri Language using Noun Identification and NER Identification Algorithm," International Journal of Computer Sciences and Engineering, Vol.3, Issue.9, pp.193-197, 2015.

Today, net services and applications have become an indivisible part of our daily life. So as to suit during this increase in application and data quality, web services have rapt to a multi-tier design in which, web server runs the application front-end logic and knowledge area unit which are out sourced to information or digital computer. Double-Guard is associate IDS that model the network behavior of user sessions across every front-end net server and additionally the back-end information. By watching both web and consequent database requests, system is able to find out attacks that free-lance IDS wouldn’t be able to determine. This system have tendency to quantify the short comings of any multi-tier IDS in terms of coaching sessions and practically coverage. Double Guard is implemented using an Apache web server with MySQL and light-weight virtualization. Finally, using Double-Guard, system has a tendency to expose a large range of attacks.

Anomaly detection, virtualization, multitier internet application, Attacks, Dedicated Containers

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[12]. Meixing Le, Angelos Stavrou, Member, IEEE, and Brent ByungHoon Kang, Member, IEEE “DoubleGuard: Detecting Intrusionsin Multitier Web Applications”. IEEE transactions on dependable and secure computing, vol. 9, no. 4, march 2014

Tilottama Bachhav, Komal Dhamane, TrutiyaKapadnis, Vaishali Wagh, "Double Guard: Detecting Intrusions in Multitier Internet Applications," International Journal of Computer Sciences and Engineering, Vol.3, Issue.9, pp.198-200, 2015.

In recent years image processing gained the attention of many researches for criminal identification, medical science and Meteorology. This paper discussed about multi biometrics traits such as Face recognition, finger knuckle, RPPVSM, finger print, and vein pattern. Proposed work in this paper RPPVSM fusion with Vein pattern and finger knuckle for criminal identification. RPPVSM are different from birthmarks since birthmarks are congenital but RPPVSM can be congenital or acquired. The two main sections in RPPVSM i.e.) detection, matching. Then vein pattern is impossible for duplicate evidence. finger Knuckle biometrics is one of such promising modalities. Texture pattern produced by the finger knuckle bending is extremely unique and makes the surface a distinctive biometric identifier.

Biometric traits, Vein pattern, Finger Knuckle, RPPVSM

[1] Le Hoang Thai, Ha Nhat Tam “Fingerprint recognition using standardized fingerprint model”, IJCSI International Journal of Computer Science Issues, Vol. 7, Issue 3, No 7, May 2010.
[2] Divyarajsinh N. Parmar, Brijesh B. Mehta, “Face Recognition Methods & Applications”, Int.J.Computer Technology & Applications,Vol 4 (1),84-86
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