iosr-JCE   Volume-9 ~ Issue-6

Abstract: In this paper, Adaptive Modulation and Coding technique for OFDM is proposed. In this technique it is possible to switch the modulation order and coding rate in order to better match the channel conditions. The use of adaptive modulation allows higher throughputs and covering long distances. The aim of this paper is to increase the transmission data rate which the high order modulation scheme with low coding redundancy is used. Numerical results are presented showing that the better performance both in terms of error probability and data throughput.

Index terms: OFDMA, adaptive modulation and coding, IEEE 802.16, broadband wireless access, WiMAX.

[1] Motorola and Nokia, "Proposal for standardization of very high rate mixed voice-data traffic capabilities, based on extending and
enhancing 1X systems," 3GPP2, S00-200003210-020,March, 2000
[2] Motorola and Nokia, "1XTREME," 3GGP2, S00-20000321-019, March, 2000
[3] Motorola, Nokia, Philips, TI and Altera, "Joint 1XTREME Proposal for 1XEV-DV," 3GPP2, C50-20010611-008a, June, 2001
[4] Motorola, Nokia, Texas Instruments, Altera, and Philips Semiconductors, "1XTREME Physical Specification for Integrated Data
and Voice Services in cdma2000 Spread Spectrum Systems," 3GPP2, C50-200010611-013R1, June, 2001.
[5] L. Hanzo, C. H. Wong, M. Yee, Adaptive Wireless Transceivers: Turbo-Coded, Turbo-Equalized and Space-Time Coded TDMA,
CDMA, and OFDM Systems. (John Wiley, 2002)
[6] T. Keller and L. Hanzo, "Adaptive modulation techniques for duplex OFDM transmission," IEEE Trans. Veh. Technol., vol. 49, no.
5, pp. 1893–1906, Sept. 2000.
[7] A. J. Goldsmith and S.-G. Chua, "Adaptive coded modulation for fading channels," IEEE Trans. Commun., vol. 46, no. 5, pp. 595 –
602, May1998.
[8] W. T. Webb and R. Steele, "Variable rate QAM for mobile radio," IEEE Trans. Commun., vol. 43, pp. 2223 –2230, July 1995.
[9] C. Y. Wong, R. S. Cheng, K. B. Letaief, and R. D. Murch, "Multiuser OFDM with adaptive subcarrier, bit and power allocation,"
IEEE J. Select. Areas Commun., vol. 17, no. 10, pp. 1747–1758, Oct. 1999.
[10] M.-K. Chang and C.-C. J. Kuo, "Power control, adaptive modulation and subchannel allocation for multiuser downlink OFDM," in
Proc. IEEE VTC2004-Fall, Los Angeles, CA, USA, Sept. 2004.

Abstract: We describe a Model RSM2 (A Reliable and Scalable Multicast Model). The approach we adopt uses Proactive-Routing, Minimum-Cost Path Algorithm, Combo-casting, Active Server Based Recovery, NACK-Based acknowledgement, Buffer Management, Optimized Flooding Algorithm. The main characteristic of RSM2 model is, to provide complete multicasting, i.e. at the same time more than one node can act as sender. This model provides one-to-many communications as well as many-to-many communications. Through this model, we tried to create an improvement over RMTP. To describe the generality of this Model, we have designed an algorithm MCPA(Minimum Cost Path Algorithm).

Keywords - Combo-Casting, Optimized Flooding Algorithm, Proactive Routing, Reliability, Scalability

Journal Papers:
[1] Sanjoy Paul, Member, IEEE, Krishna K. Sabnani, Fellow, IEEE, John C.-H. Lin and Supratik Bhattacharyya ―Reliable Multicast Transport Protocol (RMTP)‖. IEEE journal on Selected Areas in Communications, Vol. 15, No. 3, April 1997.
Proceedings Papers:
[2] Danyang Zhang, Sibabrata Ray, Rajgopal Kannan, S. Sitharama Iyengar ―A Recovery Algorithm for Reliable Multicasting in reliable networks.‖ Proceedings of the 2003 International Conference on Parallel Processing (ICPP'03).
Books:
[3] K.K.Singh, Akansha Singh,‖Mobile Computing‖, Umesh Publications.
Thesis:
[4] Ruchi Gupta, A Reliable and Scalable Multicast Model (RSM2) ,Mahamaya Technical University, Noida, M.Tech, CSE, 2012.
Journal Papers:
[5] Carolos Livadas, Idit Keidar, Nancy A. Lynch ―Designing a Caching-Based Reliable Multicast Protocol‖
[6] Ruchi Gupta, Pramod Kumar Sethy ―A Reliable & Scalable Multicast Model―(RSM2), in International Journal of Recent Technology and Engineering (IJRTE) ISSN: 2277-3878, Volume-1, Issue-2.

Abstract: Automatic Train Control (ATC) is the term for a general class of train protection systems for railways that involves some sort of speed control mechanism in response to external inputs. ATC systems continuously monitor all movements of the trains on lines and at stations and provide safe signaling. A large number of automatic functions support the high speeds possible and enabling the line and network resources to be utilized to maximum capacity. ATC use to schedule multiple trains between two stations with small meter gap between adjutant trains. So the railway department can run more train by using the same track without accident problem. Population explosion has resulted in a series of problems, such as traffic jam, environment pollution, and energy crisis. This project focus on channel estimation errors and the tradeoff between MIMO multiplexing gain and diversity gain in making handoff decisions. The handoff problem is formulated as a partially observable Markov decision process (POMDP), and the optimal handoff policy can be derived to minimize the handoff latency.

Keywords- Green computing, railway communication, wireless local area network (LAN), train scheduling

[1] M. Khan and X. Zhou, "Stochastic optimization model and solution algorithm for robust double-track train-timetabling problem," IEEE Trans. Intell Transp. Syst., vol. 11, no. 1, pp. 81–89, Mar. 2010.

[2] L. Li, H. Zhang, X. Wang, W. Lu, and Z. Mu, "Urban transit coordination using an artificial transportation system," IEEE Trans. Intell. Transp Syst.,vol. 12, no. 2, pp. 374–383, Jun. 2011.

[3] H. Dong, B. Ning, B. Cai, and Z. Hou, "Automatic train control system development and simulation for high-speed railways," IEEE Circuits Syst. Mag., vol. 10, no. 2, pp. 6–18, Jun.2010.

[4] M. Aguado, O. Onandi, P. Agustin, M. Higuero, and E. Jacob Taquet, "WiMax on rails," IEEE Veh. Technol. Mag., vol. 3, no. 3, pp. 47–56, Sep. 2008.

[5] A. Santos, A. Soares, F. de Almeida Redondo, and N. Carvalho, "Tracking trains via radio frequency systems," IEEE Trans. Intell. Transp. Syst., vol. 6, no. 2, pp. 244–258, Jun. 2005.

[6] A. Amanna, M. Gadhiok, M. Price, J. Reed, W. Siriwongpairat, and T. Himsoon, "Railway cognitive radio," IEEE Veh. Technol. Mag., vol. 5, no. 3, pp. 82–89, Sep. 2010.

[7] M. Aquado, E. Jacob, P. Saiz, J. J. Unzilla, M. V. Hiquero, and J. Matias,"Railway signaling systems and new trends in wireless data communication, "in Proc. IEEE VTC, Dallas, TX, Sep. 2005, pp. 1333–1336.

[8] I. Ramani and I. Ramani, "Syncscan: Practical fast handoff for 802.11infrastructure networks," in Proc. IEEE INFOCOM, Seoul, Korea, Mar. 2005, pp. 675–684.

[9] L. Zheng and D. N. C. Tse, "Diversity and multiplexing: A fundamental tradeoff in multiple-antenna channels," IEEE Trans. Inf. Theory, vol. 49, pp. 1073–1096, May 2003.

[10] M. Park, S. Choi, and S. M. Nettles, "Cross-layer MAC design for wireless networks using MIMO," in Proc. IEEE GLOBECOM, Nov. 2005, p. 2874.

Abstract: Due to the rapid development of wireless sensor devices in terms of low power and inexpensive data‐relaying has been partially achieved because of the rapid progress in integrated circuits and radio transceiver designs and device technology. Because of this, the wireless sensor devices are able to gather information, process them if required and send them to the next sensor device. The resource constrained ad hoc wireless sensor network is versatile yet vulnerable to attacks. The communication infrastructure with less sensor networks may interact with the sensitive data in the hostile environment where the nodes may fail and new nodes may join the network, which may leads to the susceptibility to many kinds of security attacks. An adversary can eavesdrop on all the messages within the emission area, by operating in promiscuous mode. So, it is imperative that the protection of the network routing from the adversaries for the wireless ad hoc sensor network must be adopted for critical missions. A particularly devastating attack, predominant in today's world is the wormhole attack. In this paper, the wormhole attack made by the malicious attacker in sensor networks has been implemented and also the number of Guard nodes required has been decided and implemented. Functions of the guard nodes like local inter-node collaborative data fusion and decision fusion to detect, isolate and prevent any further attacks is to be implemented. Simulations have been performed under different scenarios and from the results of simulation we have observed that our scheme is capable of improving the security in resource constrained wireless sensor networks.

Keywords: Wireless Sensor Network, AODV, Wormhole

[1] Junfeng Wu, Honglong Chen, Wei Lou and Zhibo Wang, "Label-Based DV-Hop Localization AgainstWormhole Attacks in Wireless Sensor Networks" in IEEE Transactions, 978-0-7695-4134-1/10,2010
[2] He Ronghui, Ma Guoqing, Wang Chunlei, and Fang Lan "Detecting and Locating Wormhole Attacks in Wireless Sensor Networks Using Beacon Nodes" in World Academy of Science, Engineering and Technology 55 2009
[3] Y.C. Hu, A. Perrig, and D.B. Johnson. Packet leashes, "A defense against wormhole attacks in wireless ad hoc networks," in Proceedings of INFOCOM 2003, April 2003
[4] Issa Khalil, Saurabh Bagchi,Ness B.Shroff, "LITEWORP: A Lightweight Countermeasyre for the Wormhole Attack in Multihop Wireless Networks" on International Conference on Dependable Systems and Networks (DSN'05)
[5] Zaw Tun and Aung Htein Maw,"Wormhole Attack Detection in Wireless Sensor Networks" in World Academy of Science, Engineering and Technology 46 2008
[6] B. Dahill, B. N. Levine, E. Royer, and C. Shields, "A secure routing protocol for ad-hoc networks," Electrical Engineering and Computer Science, University of Michigan,Tech. Rep. UM-CS-2001-037, August 2001.
[7] P. Papadimitratos and Z. Haas, "Secure routing for mobile ad hoc networks," in SCS Communication Networks and Distributed Systems Modeling and Simulation Conference (CNDS), 2002.
[8] Y. C. Hu, A. Perrig, and D.B. Johnson, "Packet leashes: a defense against wormhole attacks in wireless networks," in Proceedings of the 22nd INFOCOM, pp. 1976-1986, 2003.
[9] C. E. Perkins and P. Bhagwat, "Highly dynamic destinationsequenced distance-vector routing (DSDV) for mobile computers," In ACM SIGCOMM on Communications Architectures, Protocols and Applications, 1994.
[10] D. Johnson, D. Maltz, and J. Broch, "The Dynamic Source Routing Protocol for Multihop Wireless Ad Hoc Networks," in Ad Hoc Networking, Addison-Wesley, 2001.

Abstract: People nowadays rely heavily on the Internet since conventional activities or collaborations can be achieved with network services (e.g., web service). Widely deployed web services facilitate and enrich several applications, e.g., online banking, e-commerce, social networks, and cloud computing. user authentication is only handled by text passwords for most websites. Applying text passwords has several critical disadvantages. Safety is a major focus of awareness for operators and users of the website and its many applications, among the difficult problems still inefficiently addressed is identity authentication for purposes of associating a particular user with particular services and authorizations. A request is a way to classify users such that forging recommendation is difficult for adversaries, while providing strong authentication of their chosen identifiers remains easy and convenient for users. The objective of the proposed system is to make online transaction more efficient to the user who uses the website and shops online. This will have a positive impact on user profitability. To make on-line shopping even simpler and safer, a secure processing system is being introduced. Index Terms— authentication, online shopping, text password, web services

[1]. Hung-Min Sun, Yao-Hsin Chen, and Yue-Hsun Lin, " oPass: A User Authentication Protocol Resistant to Password Stealing and Password Reuse Attacks",in IEEE transactions on information forensics and security, vol. 7, no. 2, april 2012.
[2]. S. Chiasson, A. Forget, E. Stobert, P. C. van Oorschot, and R. Biddle, "Multiple password interference in text passwords and click-based graphical passwords," in CCS '09: Proc. 16th ACM Conf. Computer Communications Security, New York, 2009, pp. 500–511, ACM.
[3]. S. Gawand E. W. Felten, "Password management strategies for online accounts, in SOUPS '06: Proc. 2nd Symp. Usable Privacy Security, New York, 2006,p 44– 55, ACM.
[4]. K.-P. Yee and K. Sitaker, "Passpet: Convenient password management andphishing protection," in SOUPS '06: Proc. 2nd Symp. Usable Privacy Security, New York, 2006, pp. 32–43, ACM.
[5]. M.Wu, S. Garfinkel, and R. Miller, "Secure web authentication with mobile phones," in DIMACS Workshop Usable Privacy Security Software,Citeseer, 2004.
[6]. A. Perrig and D. Song, "Hash visualization: A new technique to improve real-world security," in Proc. Int.Workshop Cryptographic Techniques E-Commerce, Citeseer, 1999, pp. 13.
[7]. Florencio and Cormac Herley, "One-Time Password Access to Any Server without Changing the Server" in Microsoft Research, One Microsoft Way, Redmond, WA.
[8]. Joseph D. Touch, "Performance Analysis of MD5" in USC / Information Sciences Institute

Abstract: As MANETs haven't any mounted infrastructure, all messages have to be routed through the nodes within the network. several clustering and routing algorithms are developed for MANETs. Moreover, most of the prevailing routing algorithms don't utilize the potency that may be obtained by clustering a network. clustering method involves in grouping network nodes and facilitates in reducing the overhead messages that help in establishing routes. Moreover, there's a trade-off between providing security and preserving the ability of a node. In current approaches, clustering and routing algorithms are designed specifically for either providing security or protective power. It's terribly tough to boost each security and minimize power consumption, as usually one is achieved at the expense of the opposite. In this paper we survey about different weight based clustering algorithms designed so far.

Keywords- Clustering, MANET, Mobility, Security

[1] Agarwal, R., & Mahesh, M. (2009). Survey of Clustering Algorithms for MANET. International Journal on Computer Science and Engineering, Vol.1 (2), 2009, (pp. 98-104).

[2] Ismail Ghazi Shayeb, AbdelRahman Hamza Hussein and Ayman Bassam Nasoura(2011). A Survey of Clustering Schemes for Mobile Ad-Hoc Network (MANET), American Journal of Scientific Research, 20, (pp. 135-151).

[3] Mario Gerla and Jack Tzu-Chieh Tsai, "Multicluster, mobile,multimedia radio network", Wireless Networks, Vol. 1, No. 3, pp. 255-265, March 1995.

[4] Mainak Chatterjee, Sajal K. Das, and Damla Turgut, "WCA: A Weighted Clustering Algorithm for Mobile Ad Hoc Networks", Cluster Computing, Vol. 5, No. 2, pp. 193-204, April 2002.

[5] Geng Chen, Fabian Garcia Nocetti, Julio Solano Gonzalez, and Ivan Stojmenovic, "Connectivity Based k-hop Clustering in Wireless Networks", Proceedings of the 35th Hawaii International onference on System Sciences, pp. 2450-2459, Big Island, Hawaii, January 2002.

[6] Dongkyun Kim, Seokjae Ha, and Yanghee Choi, "K-hop Cluster-basedDynamic Source Routing in Wireless Ad-Hoc Packet Radio Network",Proceedings of the 48th IEEE conference on Vehicular Technology, pp. 224-228,

[7] Suman Banerjee and Samir Khuller, "A Clustering Scheme for Hierarchical Control in Multi-hop Wireless Networks", Proceedings of theTwentieth Annual Joint Conference of the IEEE Computer and Communications Societies Anchorage, Alaska, April 2001.

[8] Khaled M. Alzoubi, Peng-Jun Wan, and Ophir Frieder, "New Distributed Algorithm for Connected Dominating Set in Wireless Ad Hoc Networks", Proceedings of the 35th Hawaii International Conference on SystemSciences, pp. 3849- 3855, Big Island Hawaii, January 2002.

[9] Yuanzhu Peter Chen and Arthur L. Liestman, "Approximating Minimum Size Weakly-Connected Dominating Sets for Clustering Mobile AdHoc Networks", Proceedings of the 3rd ACM international symposium on Mobile ad hoc networking & computing, pp. 165-172, Lausanne, Switzerland, June 2002.

[10] Alan D. Amis, Ravi Prakash, Thai H.P. Vuong, and Dung T. Huynh,"Max-Min D-Cluster Formation in Wireless Ad Hoc Networks", Proceedings of the Nineteenth Annual Joint Conference of the IEEE Computer andCommunication Societies, pp. 32-41, Tel-Aviv, Israel, March 2000.

Abstract: Most of the businesses need strategy for sales and distribution of their products. In order to have massive distribution of product the manufacturers have to first reach out the dealers to promote their products. The selling process comprises multiple business process such as warranty and claim of a material produced from the manufacturer. However, various business processes involved can be customized for all the various products. This investigative study proposes an efficient framework for online dealer management portal using SAP Abap Web-Dynpro.

Keywords – SAP, ERP, Abap Web-Dynpro, Dealer Portal

[1] Ezine Articles. "Ezine Articles" What is SAP? An In-depth Definition of SAP ERP System. 30 Jan. 2013. < http://EzineArticles.com/1314218>.

[2] C1 India. "Dealer Portal" Dealer Portal Is A Very Simple Yet Comprehensive Buyer - Seller B2b Platform.2 Feb. 2013. < http://www.c1india.com/dealer.html>.

[3] Code Project. "Code Project" Simple Example of MVC. 2 Feb. 2013. < http://www.codepro ject.com/Articles/25057/Simple-Example-of-MVC-Model-View-Controller-Design>.

[4] IT Toolbox. "Enterprise Solutions" An Example of Frameworks. 5 Feb. 2013. < http://it.toolbox. com/blogs/enterprise-solutions/an-example-of-frameworks-21190>

Abstract: The sequential pattern mining finds all sequential patterns which occurs frequently for a given sequence database whose frequency is no less than the threshold. The weighted sequential pattern mining aims to find more interesting sequential patterns by considering the different significance of each data element in a sequence database. In the conventional weighted sequential pattern mining, pre-assigned weights of data elements are used to get the priorities which are derived from their quantitative information. Generally in sequential pattern mining, the generation order of data is considered to find sequential patterns. However, generation time and time-intervals between the data are also important in real world application domains. Therefore, time-intervals information of data elements can be helpful in finding more interesting sequential patterns. The proposed system presents a framework for finding time-interval weighted sequential (TiWS) patterns in a sequence database. In addition, the CloSpan algorithm is used for mining TiWS patterns in a sequence database which reduces the multiple database scans and the processing time. This is useful in application fields such as web access pattern analysis, customer purchase pattern analysis, DNA sequence analysis, etc.

Keywords – CloSpan, Sequential database, Sequential pattern mining, Time-interval weight, TiWS support, TiWS pattern, weighted sequential pattern.

[1] [13] Minghua. Zhang and Ben. Kao. A GSP- based Efficient Algorithm for Mining Frequent Sequences. In HKU CSIS Tech Report TR-2002-05.
[2] [8] R. Srikant and R. Agrawal. Mining sequential patterns: Generalizations and performance improvements. In Proc.5th Int. Conf. Extending Database Technology(EDBT'96), pages 3–17, Avignon, France, Mar. 1996.
[3] [12] Mohammed J. Zaki, SPADE: An Efficient Algorithm for Mining Frequent Sequences, Computer Science Department, Rensselaer Polytechnic Institute, Troy NY 12180-3590
[4] J. Ayres, J. Gehrke, T. Yiu, and J. Flannick, Sequential PAttern Mining using a Bitmap Representation. In SIGKDD'02, Edmonton, Canada, July 2002.
[5] J. Han, J. Pei, B. Mortazavi-Asl, Q. Chen, U. Dayal, M.-C. Hsu, FreeSpan: frequent pattern-projected sequential pattern mining, in: Proceedings of the 2000 ACM SIGKDD International Conference on Knowledge Discovery and Data Mining(KDD '00), 2000, pp. 355–359.
[6] J. Pei, J. Han, B. Mortazavi-Asl, J. Wang, H. Pinto, Q. Chen, U. Dayal, M.-C. Hsu, Mining sequential patterns by pattern-growth: the PrefixSpan approach, IEEE Transactions on Knowledge and Data Engineering 16 (11) (2004) 1424–1440.
[7] U. Yun, An efficient mining of weighted frequent patterns with length decreasing support constraints, Knowledge-Based Systems 21
[8] Joong Hyuk. Chang, Mining weighted sequential patterns in a sequence database with a time-interval weight, In the Knowledge-Based Systems 24 (2011) 1–9.
[9] Yi-Cheng Chen and Ji-Chiang Jiang. An Efficient Algorithm for Mining Time Interval-based Patterns in Large Databases. In CIKM'10, October 26–30, 2010.
[10] X. Ji, J. Bailey, G. Dong, Mining minimal distinguishing subsequence patterns with gap constraints, Knowledge and Information Systems 11 (3) (2007) 259–296.

Abstract: Fingerprint recognition is one of the most popular and successful methods used for person identification, which takes advantage of the fact that the fingerprint has some unique characteristics called minutiae; which are points where a curve track finishes, intersect with other track or branches off. However obtaining a good fingerprint image is not always easy. Fingerprint images are rarely of perfect quality. They may be degraded and corrupted due to variations in skin and impression conditions. Thus, image enhancement techniques are employed prior to minutiae extraction to obtain a more reliable estimation of minutiae locations. In this paper we are doing the study and analysing the performance of various fingerprint enhancement techniques.

Keywords: Fingerprint, Minutiae, Fingerprint enhancement, Binarisation, Thinning, Minutiae Extraction

[1] Lili Liu and Tianjie Cao, "The Research and Design of an Efficient Verification System Based on Biometrics", International Conference on Computer Science and Electrical Engineering, 2012.

[2] Dr. Salah M. and Dr. Feryal I. Haj Hassan, "Fingerprint Minutiae Extraction", Journal of Computing Press., Vol. 2, November 2010. [3] Maltoni D., Maio D., Jain A. K., and Prabhakar S. "Handbook of Fingerprint Recognition". Springer, 2003.

[4] Lavanya B. N., K. B. Raja and Venugopal K. R., "Minutiae Extraction in Fingerprint using Gabor Filter Enhancement", International Conference on Advances in Computing, Control and Telecommunication Technologies, IEEE, 2009.

[5] F. A. Afsar, M. Arif and M. Hussain, "Fingerprint Identification and Verification System using Minutiae Matching", National Conference on Engineering Technologies, 2004.

[6] Feng Zhao and Xiaoou Tang, "Preprocessing and postprocessing for skeleton-based fingerprint minutiae extraction", Pattern Recognition Society, Published by Elsevier Ltd, 2006.

[7] L. Hong, Y. Wan and A. Jain, "Fingerprint Image Enhancement: Algorithm and Performance Evaluation", IEEE Pattern Analysis and Machine Intelligence, vol. 20, No. 8, pp. 777-787, 1998.

[8] Raymond Thai," Fingerprint Image Enhancement and Minutiae Extraction" technical Report, The University of Western Australia, 2003.

[9] Manvjeet Kaur, Mukvinder Singh and Parvinder S. Sindhu, "Fingerprint Verification System using Minutiae Extraction Technique", Proceedings of World Academy of Science, Engineering and Technology, Vol. 36, December 2008.

[10] Lin Hong, Anil Jain, Sharath PanKanti and R. Bolle, "Identity Authentication Using Fingerprints", Proceedings of the IEEE, Vol. 85, September1997.

Abstract: Accurate classification of traffic is basic to other numerous network activities. Traffic classification is important and it is needful in many areas like network model, network administration and safety measures of traffic. IP traffic classification comes to a part to find out the unauthorized traffic in a large network and the most essential is to grant diverse Quality of Service to the traffic from different application is a chosen feature for many IP network operators, especially for enterprise networks. So the encouraging methodology that has developed recently is traffic classification using machine learning techniques. This paper shows the overview of interactive IP traffic, analysis and classification using Machine Learning techniques.

Keywords - NetMate , Skype, Tcpdump, Weka

[1] Patrick Schneider. TCP/IP Traffic Classification Based on Port Numbers. Division Of Applied Sciences, Cambridge, MA 02138.

[2] Patrick Haffner, Subhabrata sen, Oliver Spatcheck, Dongmei Wang. 2005. ACAS: Automated Construction of Application Signatures in Proc. ACM SIGCOMM MineNet.

[3] Nigel Williams, Sebastian Zander, Grenville Armitage. 2006. A Preliminary Performance Comparison of Five Machine Learning Algorithms for Practical IP traffic Flow Classification in proc ACM SIGCOMM

[4] Erman, J., Mahanti, A and Arlitt, M. 2006. Internet Traffic Identification Using Machine Learning in proc. IEEE GLOBECOM.

[5] Li, W and Moore, A.W. 2007. A Machine Learning Approach for Efficient Traffic Classification in proc Comput.Telecommun.Syst. [6] Kohavi, R., Quinlan, J.R., Klosgen, W and Zytkow, J. 2002. Decision Tree Discovery, Handbook Data Mining Knowledge.

[7] Kohavi, R. 1996. Scaling Up the Accuracy of Naïve-Bayes Classifiers: a Decision –Tree Hybrid in proceedings of 2nd International Conference on Knowledge Discovery and Data Mining.

[8] Moore, A and Zuev, D. 2005. Internet Traffic Classification Using Bayesian Analysis Techniques in SIGMETRICS'05, Banff, Canada.

[9] Bouckaert, R. 2005. Bayesian Network Classifiers in Weka. Technical Report, Department of Computer Science, Waikato University.

[10] Carlos Bacquet, Kubra Gumus,Dogukan Tizer. 2010. A Comparison of Unsupervised Learning Techniques for Encrypted Traffic Identification in Journal of Information Assurance and Security.

Abstract: Iris Recognition is considered as one of the best biometric method used for human identification and verification, because of its unique feature that differ from one person to another, and its importance in the security field. This paper introduced the two soft computing techniques of neural network which are used for pattern matching in iris recognition. This paper represents iris recognition based Competitive neural network Learning Vector Quantization (LVQ) and Adaptive Resonance Associative Map (ARAM) with essential redefinition of pattern similarity and also introduces the mixture model ARAM for the measurements of patterns.

Keywords - ARAM, Biometric, Iris Recognition, LVQ, and Mixture model ARAM, Neural Network.

[1] R. Plemmonsa, M. Horvatha, E. Leonhardta, P. Paucaa, S. Prasad, ―Computational Imaging Systems for Iris Recognition‖, Processing of Spiel 2004.

[2] C. L. Tisse, L. Martin, L. Torres, M. Robert, "Person identification technique using human iris recognition", ST Journal of System Research Current Issue 2003.

[3] L. Ma, U. Wang, T. Tan, "Iris Recognition Based on Multichannel Gabor Filtering", The 5th Asian Conference on Computer Vision, pp.23—25, Melbourne, Australia, January 2002.

[4] R. Narayanswamy, P. E. X. Silveir, "Extended Depth-of-Field Iris Recognition System for a Workstation Environment", Proceedings of the Spied Biometric Technology for Human Identification II,Vol. 5779, pp. 41-50, Orlando, FL, 2005.

[5] Z. Wei, T. Tan and Z. Sun, "Synthesis of Large Realistic Iris Databases Using Patch-based Sampling‖, IEEE, 2008.

[6] A. Czajka, A. Pacut, "Replay Attack Prevention for Iris Biometrics", IEEE, ICCST 2008.

[7] C. Teo and H. Ewe, "An Efficient One-Dimensional Fractal Analysis for Iris Recognition", Proceedings of the 13-thWSCGInternational Conference in Central Europe on Computer Graphics, Visualization and Computer Vision, pp. 157-160, Plzen-Bory, Czech Republic, January 31 – February 4, 2005.

[8] Daugman J G., ―High confidence visual recognition of persons by a test of statistical independence‖, IEEE Trans. Pattern Anal. Machine Intel. 1993, vol.15, no.11, pp.1148-1161.

[9] Wildes R P., ―Iris Recognition: An Emerging Biometric Technology‖, In Proceeding of the IEEE, Piscataway, NJ, vol. 85, pp.1348-1363, 1997.

[10] Daugman J G., ―Recognition persons by their pattern‖, Information Security Technical report, vol.13, no.1, pp. 33-39, 1998.

Abstract: Inter organizational workflow management systems play a very important role in executing business processes among business partners in a dynamic and timely manner. An inter organizational workflow management engine is used to model and control the execution of business processes involving a combination of manual an automated activities between organizations. Before delivering their product and services to their customers each of them have to authenticate using workflow signature scheme. A workflow consists of number of tasks in the organizations. For providing more security, signing keys can be used to grant permission to perform the task and these keys are issued on the fly. Cryptographically secure scheme is not suitable because the workflow graph is arbitrary. Cryptographic scheme such as RSA provide only data authenticity and integrity. In addition to authenticity and integrity, workflow signature provides the logical relationships such as AND-join and AND-split of a workflow. In workflow signature scheme multi key hierarchical encryption scheme is used. This survey paper mainly examines the workflows and various encryption techniques are explained along the way of discussion.

Keywords- Workflows, Inter organization, Multikey hierarchy

[1] G. Fox and D. Gannon, "Workflow in grid systems," Concurrency and Computation: Practice anExperience, pp. 1009–1019, 2006. [2] V. Atluri, S. Chun, and P. Mazzoleni, "Chinese Wall Security for Decentralized Workflow Management Systems," J. ComputerSecurity, vol. 12, no. 6, pp. 799-840, Dec. 2004.

[3] Karl R.P.H. Leung Lucas C.K. Hui, "Handling Signature Purposes inWorkflow Systems".

[4] Hoon Wei Lim · Kenneth G. Paterson, "Identity-based cryptography for grid security".

[5] A. Shamir, "Identity-Based Cryptosystems and Signature Schemes," CRYPTO: Proc. Advances in Cryptology, G. Blakley and D. Chaum, eds., pp. 47-53, Aug. 1985.

[6] J.C. Cha and J.H. Cheon, "An Identity-Based Signature from Gap Diffie-Hellman Groups," Proc. Sixth Int'l Workshop Theory and Practice in Public Key Cryptography (PKC '03), Y.G. Desmedt, ed.,pp. 18-30, Aug. 2001.

[7] D. Boneh and M. Franklin, "Identity-Based Encryption from the Weil Pairing," CRYPTO: Proc. Advances in Cryptology, J. Kilian, ed., pp. 213-229, Aug. 2001.

[8] C. Gentry and A. Silverberg, "Hierarchical ID-Based Cryptography," ASIACRYPT: Proc. Advances in Cryptology, Y. Zheng, ed., pp. 548-566, Dec. 2002.

[9] H.W. Lim and K. Paterson, "Multi-Key Hierarchical Identity- Based Signatures," Proc. 11th IMA Int'l Conf. Cryptography and Coding (IMA '07), S. Galbraith, ed., pp. 384-402, Dec. 2007..

Abstract: Web contains data that are assorted and are present in abundance. Various kinds of data can be easily extracted from the web, although not all of the data are relevant to the users. Maximum number of the web pages are in unstructured HTML format due to which problems arise in querying data sources making web data extraction process extremely time consuming and expensive. Therefore there arises a necessity to convert the unstructured HTML format into a new structured format such as XML or XHTML. To address this issue, we propose an approach for implementing web data extraction by extracting targeted data from various data sources and make Mashup by generating Extractor system. The Extractor system collaborates and integrates various stages of building a Mashup. Algorithms are used so that the Extractor system can specifically analyze the HTML tags and extract the data into a new format; however the core algorithm used, extracts data using recursive technique while rendering the DOM tree model automatically. Furthermore, the Mashup being created will help in the decision making process, which is the primary requirement for success in corporate world.

Keywords - DOM tree, Extractor, HTML, Mashup, Web Data Extraction, XML.

[1] Robert Baumgartner , Wolfgang Gatterbauer, "Web Data Extraction", 2010.

[2] Rudy AG. Gultom, Riri Fitri Sari, "Implementing Web Data Extraction and Making Mashup with Xtractorz", 978-1-4244-4791- 6/10/$25.00_c 2010 IEEE.

[3] Jer Lang Hong, Fariza Fauzi, "Tree Wrap-data Extraction Using Tree Matching Algorithm", February 2010.

[4] Majlesi Journal of Electrical Engineering Vol. 4, No. 2, June 2010- 43,"Tree Wrap-data Extraction Using Tree Matching Algorithm.

Abstract: Due to the rapid growth of digital communication and multimedia application, security becomes an important issue of communication and storage of images. Encryption is one of the ways to ensure high security images are used in many fields such as medical science, military.Modern cryptography provides essential techniques for securing information and protecting multimedia data. In recent years, encryption technology has been developed quickly and many image encryption methods have been used to protect confidential image data from unauthorized access .In this paper survey of different image encryption techniques have been discussed from which researchers can get an idea for efficient techniques to be used.

Keywords: Cryptography, Decryption, Encryption, Image Encryption , Key Space

[1]. S.H. Kamali, R. Shakerian "A New Modified Version of Advanced Encryption Standard Based Algorithm for Image Encryption" 2010 International Conference on Electronics and Information Engineering (ICEIE 2010).

[2]. H. Yu, Z. Zhu "An Efficient Encryption Algorithm Based on Image Reconstruction" 2009 International Workshop on Chaos-Fractals Theories and Applications.

[3]. Z.Yun-peng , Z. Zheng-jun " Digital Image Encryption Algorithm Based on Chaos and Improved DES "Proceedings of the 2009 IEEE International Conference on Systems, Man, and Cybernetics San Antonio, TX, USA - October 2000.

[4]. K.C. Ravishankar, M.G. Venkateshmurthy "Region Based Selective Image Encryption" 1-424-0220-4/06 ©2006 IEEE.

[5]. Paul A.J P. M. K. Paulose Jacob "Matrix based Cryptographic Procedure for Efficient Image Encryption" 978-1-4244-9477-4/11 ©2011 IEEE.

[6]. H.Gao,Y.Zhang, S. Liang, D.Li "A New Chaotic Image Encryption Algorithm "Chaos, Solitons and Fractals 29 (2006) 393–399.

[7]. A.Gautam, M. Panwar, Dr.P.R Gupta "A New Image Encryption Approach Using Block Based Transformation Algorithm" 2011 (IJAEST) Vol No. 8, Issue No. 1, 090 - 096 .

[8]. Q.Hua Lin, Fu-Liang Yin, and Y.R. Zheng" Secure image communication using blind source separation" 2004 IEEE.

[9] . R. Y. H. Zhao "An Efficient Chaos-based Image Encryption Scheme Using Affine Modular Maps" I. J. Computer Network and Information Security, 2012, 7, 41-50

[10] .R. liu, X. tian "New algorithm for color image encryption using chaotic map and spatial bit level permutation "Journal of Theoretical and Applied Information Technology 15 September 2012. Vol. 43 No.1 © 2005 - 2012 JATIT & LLS.

Abstract: Image enhancement is one of the key issues in high quality pictures such as digital cameras. Since image clarity is very easily affected by lighting, weather, or equipment that has been used to capture the image. These conditions lead to image may suffer from loss of information. The main purpose of image enhancement is to bring out detail that is hidden in an image or to increase contrast in a low contrast image. It provides a multitude of choices for improving the visual quality of images. That's why it is used in a huge number of applications with important challenges such as noise reduction, degradations, blurring etc. This paper presents a literature review on some of the image Enhancement techniques for enhancing images like Contrast Stretching, Fuzzy grayscale enhancement, Fusion based approach on MSRCR, A hybrid algorithm for spatial and frequency domain etc. Comparison of all the techniques concludes the better approach for its future research.

Keywords: Digital Image Processing, Fuzzy grayscale enhancement, Image enhancement, MSE, PSNR, Retinex, Spatial And Frequency Domain.

[[1] A. R. Rivera, B. Ryu, and O. Chae, "Content-Aware Dark Image Enhancement Through Channel Division" IEEE Transactions On Image Processing, Vol. 21, No. 9, September 2012.

[2] D. Ghimire and J. Lee ," Nonlinear Transfer Function-Based Local Approach for Color Image Enhancement," IEEE Transactions on Consumer Electronics, Vol. 57, No. 2, May 2011.

[3] S. Parthasarathy, P. Sankaran," Fusion Based Multi Scale RETINEX with Color Restoration for Image Enhancement," 2012 International Conference on Computer Communication and Informatics (ICCCI -2012), Jan. 10 – 12, 2012, Coimbatore, India.

[4] S. Bronte, L. M. Bergasa, P. F. Alcantarilla, "Fog Detection System Based on Computer Vision Techniques".

[5] Z. Chaofu, M. Li-ni, J. Lu-na ," Mixed Frequency domain and spatial of enhancement algorithm for infrared image", 2012 9th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD 2012).

[6] A. Poljicak, L. Mandic, M. Strgar Kurecic ," Improvement of the Watermark Detector Performance Using Image Enhancement

Filters," IWSSIP 2012,11-13 April 2012,Vienna, Austria.

[7] S. W. Jung, J.Y. Jeong, and S.J. K ," Sharpness Enhancement of Stereo Images Using Binocular Just-Noticeable Difference," IEEE Transactions On Image Processing, Vol. 21, No. 3, March 2012. [

8] H. Zhang，Q. Zhao，Lu Li, Y.c. Li，Y.h. You ," Muti-scale Image Enhancement Based on Properties of Human Visual System," 2011 4th International Congress on Image and Signal Processing.

[9] R. K. Jha, R. Chouhan, P. K. Biswas ," Noise-induced Contrast Enhancement of Dark Images using Non-dynamic Stochastic Resonance," 978-1-4673-0816-8/12S ©2012 IEEE.

[10] K. Hasikin, N. A. Mat Isa ," Enhancement of the low contrast image using fuzzy set theory," 2012 14th International Conference on Modelling and Simulation.