iosr-JCE   Volume-9 ~ Issue-5

Abstract: Private Cloud computing provides attractive & cost efficient Server Based Computing (SBC). The implementation of Thin client computing for private cloud computing will reduce the IT Cost and consumes less power. Most cloud services run in browser based environment so we don't need a fat client to use in the private Cloud environment. Implementing Thin Client Technology along with Private Cloud Computing will help to reduce the IT Operational Cost by 90% by saving power, space and maintenance. It requires only minimal power for cooling the Infrastructure. Thin Client with private Cloud Computing can be referred as purest form of green computing & carbon free computing.

Keywords: Thin Clients with Cloud computing; Green computing; Private Cloud Terminal Computing; Carbon Free Computing; Low Powered Computing.

[1] Segal, I.. ""When Is Zero Client Not Zero Client?", SysGen, Inc"
[2] Mell, P. and Grance, T. (2011-09). "The NIST Definition of Cloud Computing. NIST Special Publication 800-145 (September 2011). National Institute of Standards and Technology, U.S. Department of Commerce"
[3] Sherbak, T., Sweere, N., and Belapurkar, V.. "Virtualized Enterprise Storage for Flexible, Scalable Private Clouds. Reprinted from Dell Power Solutions, 2012 Issue 1"
[4] Chou, Timothy. Introduction to Cloud Computing: Business &Technology. http://www.scribd.com/doc/64699897/Introduction-to-Cloud-Computing-Business-and-Technology
[5] Wang, R."Tuesday's Tip: Understanding The Many Flavors ofCloudComputingandSaaS".
[6] Nieh, Jason; Novik, Naomi &., Yang, S. Jae (December, 2005). "A Comparison of Thin-Client Computing Architectures". Technical Report CUCS-022-00 (New York: Network Computing Laboratory, Columbia University
[7] http://www.nomachine.com/documentation/pdf/cucs-022-00.pdf
[8] Madden, B. (May 19, 2012) (2010-05-19). "Wyse hopes to shake up the thin client industry with a new zero client platform. Will it work?"
[9] Greaves, J. (of Carpathia Hosting) and Potti, S. (of Citrix). Uploaded by CarpathiaHosting on Feb 22, 2010. "Flex-Tenancy: Secure Multi-Tenancy Network Environments"
[10] I.S. Jacobs and C.P. Bean, "Fine particles, thin films and exchange anisotropy," in Magnetism, vol. III, G.T. Rado and H. Suhl, Eds. New York: Academic, 1963, pp. 271-350.

Abstract: This paper represents comparative evaluation of different type of algorithms for association rule mining that works on frequent item sets. Association rule mining between different items in large-scale database is an important data mining problem. Now a day there is lots of algorithms available for association rule mining. To perform comparative study of different algorithms various factor considered in this paper like number of transaction, minimum support and execution time. Comparisons of algorithms are generated based on experimental data which gives final conclusion.

Keywords – Apriori, Association Rules, Data Mining, Frequent Pattern

[1] R. Agrawal, R. Srikant. "Fast algorithms for mining association rules in large databases" Proc. of 20th Int'l conf. on VLDB: 487-499, 1994.
[2] J. Han, J. Pei, Y. Yin. "Mining Frequent Patterns without Candidate Generation" Proc. of ACM-SIGMOD, 2000.
[3] D. Cristofor, L. Cristofor, and D. Simovici. Galois connection and data mining. Journal of Universal Computer Science, 6(1):60–73, 2000.
[4] R. Győrödi, C. Győrödi. "Architectures of Data Mining Systems". Proc. Of Oradea EMES'02: 141-146, Oradea, Romania, 2002.
[5] M. H. Dunham. "Data Mining. Introductory and Advanced Topics". Prentice Hall, 2003, ISBN 0-13-088892-3.
[6] J. Han, M. Kamber, "Data Mining Concepts and Techniques", Morgan Kaufmann Publishers, San Francisco, USA, 2001, ISBN 1558604898.
[7] R.J. Bayardo, Jr. "Efficiently mining long patterns from databases". In L.M. Haas and A. Tiwary, editors, Proceedings of the 1998 ACM SIGMOD International Conference on Management of Data, volume 27(2) of SIGMOD Record, pages 85–93. ACM Press, 1998.
[8] R. J. Bayardo. "Efficiently mining long patterns from databases". In SIGMOD'98, pp. 85-93.
[9] G. Dong and J. Li. "Efficient mining of emerging patterns: Discovering trends and differences". In KDD'99, pp. 43-52.
[10] Zaki, M.J. and Hsiao, C.J. "CHARM: An efficient algorithm for closed itemset mining". In Proc. SIAM Int. Conf. Data Mining, Arlington, VA, pp. 457–473, 2002.

Abstract: Anonymizing networks such as Tor allow users to access Internet services privately by using a series of routers to hide the client's IP address from the server. The success of such networks, however, has been limited by users employing this anonymity for abusive purposes such as defacing popular Web sites. Web site administrators routinely rely on IP-address blocking for disabling access to misbehaving users, but blocking IP addresses is not practical if the abuser routes through an anonymizing network. As a result, administrators block all known exit nodes of anonymizing networks, denying anonymous access to misbehaving and behaving users alike. To address this problem, we present Nymble, a system in which servers can "blacklist" misbehaving users, thereby blocking users without compromising their anonymity. Our system is thus agnostic to different servers' definitions of misbehavior—servers can blacklist users for whatever reason, and the privacy of blacklisted users is maintained.

Keywords: Anonymous Blacklisting, Anonymizing Networks, Backward Unlinkability, Privacy, Revocation, Realibility and Security.

[1] P.C. Johnson, A. Kapadia, P.P. Tsang, and S.W. Smith, ―Nymble: Anonymous IP-Address Blocking‖ in Proc, Conf. Privacy Enhancing Technologies, Springer, pp. 113-133, 2007.
[2] B.N. Levine, C. Shields, and N.B. Margolin, ―A Survey of Solutions to the Sybil Attack‖, Technical Report 2006-052, Univ. of Massachusetts, Oct. 2006.
[3] D. Boneh and H. Shacham, ―Group Signatures with Verifier-Local Revocation‖, Proc. ACM Conf. Computer and Comm. Security, pp. 168-177, 2004.
[4] T. Nakanishi and N. Funabiki, ―Verifier-Local Revocation Group Signature Schemes with Backward Unlinkability from Bilinear Maps‖, Proc. Int'l Conf. Theory and Application of Cryptology and Information Security (ASIACRYPT), Springer, pp. 533-548, 2005.
[5] G. Ateniese, J. Camenisch, M. Joye, and G. Tsudik,‖ A Practical and Provably Secure Coalition-Resistant Group Signature, Scheme‖, Proc. Ann. Int'l Cryptology Conf. (CRYPTO), Springer, pp. 255-270, 2000.
[6] R. Dingledine, N. Mathewson, and P. Syverson, ―Tor: The Second- Generation Onion Router,‖ Proc. Usenix Security Symp., pp. 303-320, Aug. 2004.
[7] C. Cornelius, A. Kapadia, P.P. Tsang, and S.W. Smith, ―Nymble: Blocking Misbehaving Users in Anonymizing Networks,‖ Tech- nical Report TR2008-637, Dartmouth College, Computer Science, Dec. 2008.
[8] J.E. Holt and K.E. Seamons, ―Nym: Practical Pseudonymity for Anonymous Networks,‖ Internet Security Research Lab Technical Report 2006-4, Brigham Young Univ., June 2006.
[9] A. Lysyanskaya, R.L. Rivest, A. Sahai, and S. Wolf, ―Pseudonym Systems,‖ Proc. Conf. Selected Areas in Cryptography, Springer, pp. 184-199, 1999.
[10] J.R. Douceur, ―The Sybil Attack,‖ Proc. Int'l Workshop on Peer-to- Peer Systems (IPTPS), Springer, pp. 251-260, 2002.