iosr-JCE   Volume-16 ~ Issue-3 ~ May-June 2014

Abstract: The objective of this paper is to develop a tool to identify the white blood cells from blood smear images through segmentation. In our research work, we have identified white blood cells from color images of blood smears. We have used Fuzzy C Means segmentation method and erosion and dilation post processing method to identify the white blood cells. In our obtained result we find that this method successfully identified 98% of white blood cells from which is a satisfactory result.
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
[3] Cseke. A fast segmentation scheme for white blood cell images. In 11th IAPR Int. conf. of Pattern Recognition, Conf. C: Image, Speech and Signal Analysis, volume 3, pages 530-533, 1992.
[4] D.Wermser, G.Haussman, and C.Liedtke. Segmentation of blood smears by hierarchiclal thresholding. In computer vision, Graphics and Image Processing, volume 25, pages 151-168, 1984.
[5] A.R.Katz. Image analysis and supervised learning in the automated differntiation of white blood cells from microscopic images. Master's thesis, Department of Computer Science, RMIT, Feb.2000.

Abstract: Attack graphs are the graphs which describe attack scenarios, play important roles in analyzing network threats. These attack graphs are able to reveal such potential threats by evaluating the all possible sequences that an attacker can follow to compromise given critical resources or nodes. An Attack graph specifies an attack scenario that results in compromising network values. There are so many methods proposed to evaluate the network security in attack graphs. But no method specifies the overhead occurred due to the evaluation of network security at each and every node. This paper addresses the problem of overhead occurred due to the network security evaluation in Short-Normalizedattack graphs by evaluating a factor called network security risk. In this paper first the possible n valid attack paths are going to be calculated and then the security risk is going to be calculated for those n valid paths. This security risk denotes the amount of overhead occurred due to this evaluation.
Keywords: Network Security,Network Configuration, Short-Normalized Attack Graphs, Security Risk Evaluation

[1]. C. A. Phillips and L. P. Swiler, "A graph-based system for network vulnerability analysis," in Workshop on New Security
Paradigms, 1998, pp. 71–79.
[2]. O. Sheyner, J. W. Haines, S. Jha, R. Lippmann, and J. M. Wing, "Automated generation and analysis of attack graphs," in IEEE
Symposium on Security and Privacy, 2002, pp. 273–284.
[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.
[4]. S. Noel, S. Jajodia, B. O'Berry, and M. Jacobs, "Efficient minimum-cost network hardening via exploit dependency graphs," in
ACSAC. IEEE Computer Society, 2003, pp. 86–95.
[5]. L. Wang, T. Islam, T. Long, A. Singhal, and S. Jajodia, "An attack graph-based probabilistic security metric," in DBSec, ser.
Lecture Notes in Computer Science, V. Atluri, Ed., vol. 5094. Springer, 2008, pp. 283–296.

Abstract: Information exchange has become an essential component in modern society. Vendors provide content to consumers, while consumers exchange information using e-mail, peer-to-peer systems, social networks, or other network applications. We rely on embedded software in our cars, the domotics, built into our homes, and other electronic devices on a daily basis. Obviously, all these applications rely on the correct functioning of software and hardware components. Often, software which is the driving force of computer hardware are usually subjected to cracking, a condition whereby hackers bypassing the registration and payments options on a software product to remove copyright protection safeguards or to turn a demo version of software into a fully functioning version by manipulating information such as the serial number, hardware key, dates, etc., without actually paying for the software. In this paper, we proposed a hybridized self-modifying technique for checking against cracking. Our technique combines obfuscation and hashing mechanisms to resist attackers from cracking software. The key idea is to hide the code using hashing by transforming it such that it becomes more difficult to understand the original source code and using obfuscation to resist software reverse engineering. The result shows that our technique is able to block hackers and thus prevent code cracking.
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.
[3] H. Chang and M. Atallah. Protecting Software Codes by Guards, ACM Workshop on Digital Rights Management (DRM 2001), LNCS 2320, pp. 160-175, 2001.
[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.
[5] C. Collberg and C. Thomborson. Watermarking, Tamper-Proofing, And Obfuscation - Tools for Software Protection, IEEE Transactions on Software Engineering, Vol. 28, Issue: 8, pp. 735 – 746, 2002.

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.
[4]. ZornistaKozareva and Eduard Hovy, "Not all seeds are equal: Measuring the quality of text mining seeds" In NAACL'10, 2010.
[5]. M. Banko, M. Cafarella, S. Soderland, M. Broadhead, and O. Etzioni, "Open information extraction from the web", In IJCAI'07, pages 2670–2676, 2007

Abstract: This paper introduces MOBILE PHONE EMBEDDED WITH ANDROID BASED EMERGENCY ALERT BUTTON AND MEDICAL TOOLS - a mobile phone can serve us with various functions of security applications and medical tools. This serves us with facilities of (1)ANDROID BASED EMERGENCY ALERT BUTTON, (2)ACCU-CHEK GLUCOMETER, (3)BODY MASS INDEX CALCULATOR, (4)BASAL METABOLIC RATE CALCULATOR, (5)BODY FAT CALCULATOR, (6)ACTIVITY CALCULATOR, (7)ANDROID BASED HOME SECURITY SYSTEM. Thus this embedded system will act like a self-doctor which can help us as medical equipment. Collectively the mobile phone can be used as a modern medical toolbox having all the facilities we can inherit and also it can use as for managing or analysing the daily common diseases. The application like home security system discussed here can be incorporated with mobile phones is sure to benefit every people who always have a doubt of their belongings being secure in the house in their absence. Most of the mobile devices that are manufactured nowadays in the market are ANDROID OS based. Taking this into interest the application can be developed in ANDROID and made user friendly, thereby making the applications highly robust across different mobile devices and variety of users.
Keywords: ANDROID, Short Message Service (SMS), Global Communication for mobile system (GSM).

[1]. http://www.britishnutritions.in/activity-calculator.html
[2]. http://www.britishnutritions.in/bmi-calculator.html
[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.
[4]. http://www.britishnutritions.in/body-fat-calculator.html
[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.
[6]. http://www.britishnutritions.in/bmr-calculator.html

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

Abstract: Cloud computing provides shared resources to various cloud users. All the users share various computing resources e.g., being connected through the same switch, sharing the same data storage and the file systems. Hence the cloud security is the major concern in the cloud computing and has attracted lot of research activities. The most common issue with the cloud computing is the Distributed-Denial-of-Service (DDoS) attacks. The DDoS attacks involve actions such as multistep exploitation and compromising identified vulnerable virtual machines as zombies. In the Infrastructure-as-a-service (IaaS) model, the detection of zombie virtual machines is difficult as the user may install vulnerable applications in their own Virtual machines. To detect and prevent the virtual machines from becoming zombie, we propose Defense-in-depth intrusion detection framework called NIDCS, which is an attack graph based analytical model.
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.

Abstract: This paper present the implementation of genetic algorithm for operating system process scheduling. Scheduling in operating systems has a significant role in overall system performance and throughput. An efficient scheduling is vital for system performance. The scheduling is considered as NP hard problem .In this paper, we use the power of genetic algorithm to provide the efficient process scheduling. The aim is to obtain an efficient scheduler to allocate and schedule the process to CPU. we will evaluate the performance and efficiency of the proposed algorithm using simulation results.
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
[2]. Garey, M. & Johnson, D. (1979). Computers and Intractability: a theory of NP- Completeness. W.H.Freeman, San Francisco Proceedings of the Second International Conference on Genetic Algorithms, pp. 252-256
[3]. Back, T., Fogel, David B. & Michalewicz, Z. (Eds.) (1997). Handbook of Evolutionary Computation. Computational Intelligence, Library Oxford University Press in cooperation with the Institute of Physics Publishing / CRC Press, Bristol, New York, ring bound edition. ISBN: 0-7503-0392-1, 978-0-75030-392-7, 0-7503-0895-8, 978-0-75030-895-3. [Also available online at:http://books.google.de/books?id=n5nuiIZvmpAC]
[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]
[5]. Tomassini, M. (1999). Parallel and Distributed Evolutionary Algorithms: A Review. In Miettinen, K., Makela, M., & Periaux, J. (Eds.), Evolutionary Algorithms in Engineering and Computer Science (pp. 113 - 133). Chichester: J. Wiley and Sons

Abstract: Web scraping is the process of automatically collecting information from the World Wide Web. It is a field with active developments, sharing a common goal with the semantic web vision, an ambitious initiative that still requires breakthroughs in text processing, artificial intelligence and human-computer interactions. It means extraction of content from different web pages using web scrapping and semantic illustration. Web Scrapping is a process of evocation of content from HTML pages and related to web indexing. A commonly used measure for tree similarity is the tree edit distance which easily can be extended to be a measure of how well a pattern can be matched in a tree. An obstacle for this approach is its time complexity, so we consider if faster algorithms for constrained tree edit distances are usable for web scraping, and to reduce the size of the tree representing the web page. Different applications of web scraping are used by current market to achieve best web scraping output, Like Web Data Extraction, Data Collection, Screen Scraping. Many different algorithms are used for web scraping like "tree pattern matching", "tree mapping", "approximate tree matching". But in general "tree edit distance" algorithm is used. But with this algorithm many issues of incorrectness of data, low efficiency and higher time complexity have analyzed. In this research I am focus to improve the performance of tree edit distance problem. And I am also trying to focus on higher bound time complexity of this algorithm.
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.
[5]. Sareh Aghaei, Mohammad Ali Nematbakhsh, Hadi Khosravi Farsani, International Journal of Web & Semantic Technology(IJWest) Vol 3, No.1, January 2012.

Abstract: Multiple-path routing protocols allow data source node to distribute the total traffic among available paths. We consider the problem of jamming-aware source routing in which the source node performs traffic allocation based on empirical jamming statistics at individual network nodes. We formulate this traffic allocation as a lossy network flow optimization problem using portfolio selection theory. This centralized optimization problem can be solved using a distributed algorithm based on decomposition in NUM. Along with this Network based attacks have become a serious threat to the critical information infrastructure. There are many security attacks in MANET e.g. DDOS. The effect of DDOS leads to routing load, packet drop rate, end to end delay in network. So considering these parameters we build secure IDS to detect such attack and block it. Identifying the source of the attackers is necessary to correlate the incoming and outgoing flows or connections.
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.

[1] I. F. Akyildiz, X. Wang, and W. Wang, "Wireless mesh networks: A survey," Computer Networks, vol. 47, no.4, pp. 445–487, Mar. 2005.
[2] E. M. Sozer, M. Stojanovic, and J. G. Proakis, "Underwater acoustic networks," IEEE Journal of Oceanic Engineering, vol. 25, no. 1, pp. 72–83, Jan. 2000.
[3] R. Anderson, Security Engineering: A Guide to Building Dependable Distributed Systems. JohnWiley&Sons, Inc.,2001.
[4] J. Bellardo and S. Savage, "802.11 denial-of-service attacks: Real vulnerabilities and practical solutions," in Proc. USENIX Security Symposium,Washington, DC, Aug. 2003, pp. 15–28.
[5] D. J. Thuente and M. Acharya, "Intelligent jamming in wireless networks with applications to 802.11b and other networks," in Proc. 25th IEEE Communications Society Military Communications Conference (MILCOM'06), Washington, DC, Oct. 2006, pp. 1–7.

Abstract: With the advent of anomaly-based intrusion detection systems, many approaches and techniques have been developed to track novel attacks on the systems. High detection rate of 98% at alow alarm rate of 1% can be achieved by using these techniques. Though anomaly-based approaches are efficient, signature-based detection is preferred for mainstream implementation of intrusion detection systems. As a variety of anomaly detection techniques were suggested, it is difficult tocompare the strengths, weaknesses of these methods. The reason why industries don‟t favor the anomaly-based intrusion detection methods can be well understood by validating the efficiencies of the all the methods. To investigate this issue, the current state of the experiment practice in the field of anomaly-based intrusion detection is reviewed and survey recent studies in this. This paper contains summarization study and identification of the drawbacks of formerly surveyed works..
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

Abstract: We are in advanced world of internet with new technologies in now these days. So many new wireless networks technologies have been emerged. WiMAX is one of the advanced technologies from those. Due to advancement, the security related issues has also been increased in this technology. Information Security has become one of the challenging and important tasks to maintain the confidentiality, integrity and availability of the information. This paper is all about the security of WiMAX technology. During the research we learn that there are several security related threats and attacks in this technology by which the adversary can perform several malicious activities. We also found some security methods which can be applied against several security related threats and attacks. The scope of this paper is to research the security related issues in the WiMAX technology and find the possible security solutions against that issues.
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 .
[2] Yih-Chun Hu, Adrian Perrig, and David B. Johnson, "Wormhole Attacks in Wireless Networks" in IEEE, Volume 24, No. 2, 2006.
[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.