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Keywords: Fuzzy C Mean, Segmentation, Clustering, Cell.
[1] Cell image segmentation for diagnostic pathology. www.caip.rutgers.edu/riul/research/papers/ps/cell.ps.gz
[2] Single white blood cell extraction in low resolution http://sun12.cecs.missouri.edu/jpark
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Paper Type | : | Research Paper |
Title | : | A Short-Normalized Attack Graph Based Approach for Network Attack Analysis |
Country | : | India |
Authors | : | Gouri R Patil, A. Damodaram |
: | 10.9790/0661-16390612 |
Keywords: Network Security,Network Configuration, Short-Normalized Attack Graphs, Security Risk Evaluation
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[3]. L. Wang, A. Singhal, and S. Jajodia, "Toward measuring network security using attack graphs," in QoP, G. Karjoth and K. Stølen,
Eds. ACM, 2007, pp. 49–54.
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Lecture Notes in Computer Science, V. Atluri, Ed., vol. 5094. Springer, 2008, pp. 283–296.
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Keywords: Software cracking, reverse engineering, code obfuscation, self-modification, encryption
[1] A. Aucsmith. Tamper-Resistance Software: An Implementation. In Ross Anderson, Editor, Information Hiding, Proceedings of the First International Workshop, volume 1174 of LNCS, pp. 317 – 333.
[2] J. Cappaert, N. Kisserli, D. Schellekens and B. Preneel. Self-Encrypting Code to Protect Against Analysis and Tampering, 1st Benelux Workshop Inf. Syst. Security, 2006.
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[4] Y. Chen, R. Venkatesan, M. Cary, R. Pang, S. Sinha and M. Jakubowski. Oblivious Hashing: A Stealthy Software Integrity Verification Primitive, Proc. 5th Information Hiding Workshop (IHW), Netherlands (October 2002), Springer LNCS 2578, pp. 440 – 414, 2002.
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Abstract: Traditionally, the web contains different semantic relations. The information extraction focuses on pre-specified request from small set of text. The main task of information retrieval is to extract or organize the information items as well as representation and access storage of items. There are various methods available for relation extraction presented by different authors. The main step we are focusing is supervised relation extraction. The method we propose for relation extraction for adapting new relation with supervised relation extraction system. It is based on three major concepts called domain adaptation, relation extraction and transfer learning. Our proposed method uses combination of under-sampling majority class and oversampling minority class. This paper shows that combination of these two methods improves the classifier performance. We evaluate proposed method for relation extraction using different dataset which contains entities for different relation. Using this method we are going to improve the precision, recall, F-score rate of relations which helps to improve the accuracy of relation those are novel or newly adapted. To overcome challenges in relation extraction that novel entities and relations constantly appear on the web as it contains both structured and unstructured text on the web. Our experimental result shows that the proposed method achieves F-score rate of 69.18. Moreover, it outperforms the numerous methods to adapt new relation efficiently.
Keywords: Domain adaptation, Relation extraction, semantic analysis, Entities, Web mining
[1]. DanushkaBollegala, Member, IEEE, Yutaka Matsuo, and Mitsuru Ishizuka, Member, IEEE, "Minimally Supervised Novel Relation Extraction Using a Latent Relational Mapping", IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, VOL. 25, NO. 2, FEBRUARY 2013.
[2]. DanushkaBollegala Yutaka Matsuo Mitsuru Ishizuka, "Relation Adaptation: Learning to Extract Novel Relations with Minimum Supervision", Proceedings of the Twenty-Second International Joint Conference on Artificial Intelligence.
[3]. M. Pasca, D. Lin, J. Bigham, A. Lifchits, and A. Jain. "Organizing and searching the World Wide Web of facts - step one: the one-million fact extraction challenge", In Proc. of AAAI'06, pages 1400–1405, 2006.
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Paper Type | : | Research Paper |
Title | : | Mobile Phone Embedded With Medical and Security Applications |
Country | : | India |
Authors | : | Bhaskar Kamal Baishya |
: | 10.9790/0661-16393033 |
Keywords: ANDROID, Short Message Service (SMS), Global Communication for mobile system (GSM).
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[3]. A. Alheraish, Member, IEEE "Design and Implementation of Home Automation System", IEEE Transactions on Consumer
Electronics, Vol. 50, No. 4, pp. 1087-1092, November 2004.
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[5]. Dhruba Jyoti Gogoi, Rupam Kumar Sharma, "Android Based Emergency Alert Button", In International Journal of Innovative
Technology and Exploring Engineering (IJITEE), ISSN: 2278-3075, Volume-2, Issue-4, pp. 26-27, March 2013.
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Abstract: There is an increase in the searching where name aliases are concerned. Approximately 30 percent of searches are based on aliases; hence it becomes important to obtain correct aliases. Lexical pattern based method is used to obtain the aliases of any personal or place from the web The aliases obtained are ranked and filtered based on the co-occurrence frequency and web dice methods These final aliases are then used to cluster the text documents present in a huge database. To get the best cluster cuckoo method of clustering is used. This method is based on the reproduction system of the cuckoo bird. According to the studies this clustering method when used with levy flight concept gives the best results when huge data is concern and also outperforms particle swarm optimization algorithm and genetic algorithm. The result will be compared with the result of k-means clustering method.
Keywords: Co-occurrence frequency, Genetic algorithm, K-means clustering method
[1] Danushka Bollegala, Yutaka Matsuo, and Mitsuru Ishizuka, Automatic Discovery of Personal Name Aliases from the Web, IEEE Transactions on knowledge and data engineering, Vol. 23, No. 6, June 2011.
[2] Moe Moe Zaw and Ei Ei Mon, Web Document Clustering Using Cuckoo Search Clustering Algorithm based on Levy Flight, Faculty of Information and Communication Technology, University of Technology (Yatanarpon Cyber City), Myanmar, International Journal of Innovation and Applied Studies ISSN 2028- 9324 Vol. 4 No. 1 Sep. 2013, pp. 182-188 2013 Innovative Space of Scientific Research Journals http://www.issr-journals.org/ijias/.
[3] J. Senthilnath, Vipul Das, S.N. Omkar, V. Mani, "Clustering using Levy Flight Cuckoo Search", J. C. Bansal et al. (eds.), Proceedings of Seventh International Conference on Bio-Inspired, Computing: Theories and Applications (BIC-TA 2012), Advances in Intelligent Systems and Computing 202, DOI: 10.1007/978-81-322-1041-2_6 Ó Springer India 2013.
[4] Pinar Civicioglu, Erkan Besdok "A conceptual comparison of the Cuckoo-search, particle swarm optimization, differential evolution and artificial bee colony algorithms", Artif Intell Rev DOI 10.1007/s10462-011-9276-0, Springer Science+ Business Media B.V. 2011
[5] M. Mitra, A. Singhal, and C. Buckley, "Improving Automatic Query Expansion," Proc. SIGIR '98, pp. 206-214, 1998
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Index Terms: Network security, cloud computing, attack graph, intrusion detection, zombie detection
[1]. Coud Sercurity Alliance, "Top Threats to Cloud Computing v1.0,"https://cloudsecurityalliance.org/topthreats/csathreats. v1.0.pdf, Mar. 2010.
[2]. M. Armbrust, A. Fox, R. Griffith, A.D. Joseph, R. Katz, A. Konwinski, G. Lee, D. Patterson, A. Rabkin, I. Stoica, and M.Zaharia, "A View of Cloud Computing," ACM Comm., vol. 53,no. 4, pp. 50-58, Apr. 2010.I.
[3]. H. Takabi, J.B. Joshi, and G. Ahn, "Security and Privacy Challenges in Cloud Computing Environments," IEEE Security and Privacy, vol. 8, no. 6, pp. 24-31, Dec. 2010.
[4]. L. Wang, A. Liu, and S. Jajodia, "Using Attack Graphs for Correlating, hypothesizing, and Predicting Intrusion Alerts," Computer Comm., vol. 29, no. 15, pp. 2917-2933, Sept. 2006.
[5]. Roy, D.S. Kim, and K. Trivedi, "Scalable Optimal Countermeasure Selection Using Implicit Enumeration on Attack Countermeasure Trees," Proc. IEEE Int'l Conf. Dependable Systems Networks (DSN '12), June 2012.
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Paper Type | : | Research Paper |
Title | : | Dynamic Process Scheduling and Sequencing Using Genetic Algorithm |
Country | : | India |
Authors | : | Priyanka Rani, Shakti Nagpal |
: | 10.9790/0661-16394853 |
Keywords: Genetic algorithm, NP-hard, CPU, Sequencing and Scheduling.
[1]. H.Nazif(2009). A Genetic Algorithm on Single Machine Scheduling Problem to Minimise Total Weighted Completion Time. European Journal of Scientific Research,Vol.35 No.3, pp.444-452
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[4]. Back, T. (1996). Evolutionary Algorithms in Theory and Practice: Evolution Strategies, Evolutionary Programming, Genetic Algorithms. Oxford University Press US. ISBN: 0-1950-9971-0, 978-0-19509-971-3.[ Also available online at: http://books.google.de/books?id=EaN7kvl5coYC]
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Paper Type | : | Research Paper |
Title | : | Content Evocation Using Web Scraping and Semantic Illustration |
Country | : | India |
Authors | : | Vasani Krunal A. |
: | 10.9790/0661-16395460 |
Keywords: web scraping; data mining; tree edit distance
[1]. Sanjay Kumar Malik, Sam Razvi: Information Extraction using Web Usage Mining, Web Scrapping and Semantic Annotation, International Conference on Computational Intelligence and Communication Systems, 2011.
[2]. Syeda Farha Shazmeen, Etyala Ramyasree: Semantic Web Mining: Benefits, Challenges and Opportunities, International Journal of Advanced Computer Research (ISSN (print): 2249-7277 ISSN (online): 2277-7970) Volume-2 Number-4 Issue-7 December-2012.
[3]. Parminder Pal Sing Bedi, Sumit Kumar: Web scraping and implementation using prolog server pages in semantic web, IJREAS Volume 2, Issue 2 ISSN: 2249- 3905, February-2012.
[4]. Eloisa Vargiu, Mirko Urru: Exploiting web scraping in a collaborative filtering based approach to web advertising, www.sciedu.calair, Artificial Intelligence Research, Vol 2, No. 1, 2013, online published at December 5,2012.
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To resist attempts at correlation, the attacker may encrypt or otherwise manipulate the connection traffic. Timing based correlation approaches are subject to timing perturbations that may be deliberately introduced by
the attacker at stepping stones. So watermark-based correlation scheme is proposed which is designed specifically to be robust against timing perturbations. Unlike most previous timing based correlation approaches, our watermark-.based approach is "active" in that it embeds a unique watermark into the encrypted flows by slightly adjusting the timing of selected packets.
Keywords: DDOS-Distributed Denial Of Service, IDS- Intrusion Detection System ,MANET-Mobile Ad-hoc Network ,NUM – Network Utility Maximization.
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Keywords: Intrusion Detection, Anomaly-based Detection, Signature-based detection
[1]. Sharmila Kishore Wagh, Vinod K Pachghare, "Survey on Intrusion Detection System using Machine Learning Techniques", International Journal of Computer Applications (0975 – 8887) Volume 78 – No.16, September 2013.
[2]. Mahdi Zamani , "Machine Learning Techniques For Intrusion Detection " , arXiv:1312.2177vl [cs.CR] Dec 2013
[3]. Mahesh kumar sabhnani, Gursel Serpen , "Application of Machine Learning Algorithms to KDD Intrusion Detection Dataset within Misuse Detection Context",
[4]. Hua Tang, Zhuolin CAO, "Machine Learning based Intrusion Detection Algorithms", Journal of Computational Information Systems, june2009, Available at http://www.JofCI.org.
[5]. Chris Sinclair, Lyn Pierce, Sara Matzner, "An Application of Machine Learning To Network Intrusion Detection",
[6]. Deepika P Vinchurkar, Alpa Reshamwala, "A Review of Intrusion Detection System Using Neural Network and Machine Learning Technique", International Journal of Engineering Science and Innovative Technology (IJESIT) Volume 1, Issue 2, November 2012
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Keywords: Authentication, Encryption, HTTP, VOICE, WiMAX Security, WiMAX-WLAN Interface, WiMAX threats/Attacks.
[1] Mrs.M.Rekha ,Dr.C.Chandrasekar, "Trust Based Authentication Technique For Security In WiMAX Networks" in International Journal of Computer Aided Engineering , Volume 03– No.3, Issue: 01, 2012 .
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[3] Michel Barbeau, "" WiMAX/802.16 Threat Analysis‟‟ School of Computer Science Carleton University, ACM 1-59593-241-0/05/0010, 2005.
[4] Cao, Maode Ma, Muhammad Ashaari Bin Ariff, "Security Enhancements in WiMAX Mesh Networks" in IEEE International Conference, ISBN 978-1-61284-159-5, 2011.
[5] Shah-An Yang and John S. Baras, "TORA, Verification, Proofs and Model Checking" MD 20742, USA, 2003
[6] Karen Scarfone, Cyrus Tibbs, Matthew Sexton,"Guide to Securing WiMAX wireless communications"2010.