iosr-JCE   Volume-17 ~ Issue-3 ~ May-June 2015

Abstract: Now-a-days the usage of Smartphone has been increasing greatly in recent years. Most of the people are de-pendent on Smartphone for all sort of activities such as checking mails, browsing internet, performing online transactions, surfing social networks, shopping online, paying bills etc. With so many advantages in Smartphone for users, the threats to user are also increasing. The threats are caused by creating malicious applications and game of which most of them are freely available to users on Google play. As the Smartphone have limited processing and computational power to execute highly complex algorithms for intrusion detection, virtual Smartphone images are created in cloud to prevent user from threats and vulnerabilities. In this paper we perform a comparative study on existing methods on intrusion detection system on cloud and on host devices for securing Smartphone. Cloud intrusion detection system is a better solution to achieve higher level of security. The paper discusses architectures of existing Intrusion detection system for Smartphone and their techniques

Keywords: Intrusion Detection System, Cloud Computing, Smartphones, Android Security.

[1]. Rohit S. Thune, J. Thangakumar,"A Cloud-Based Intrusion Detection System for Android Smartphones,"
[2]. Radar, Communication and Computing (ICRCC), 2012 International Conference on, vol., no., pp.180-184, 21-22 Dec. 2012.
[3]. Amir Houmansadr, Saman A. Zonouz, and Robin Berthier,"A Cloud-based Intrusion Detection and Response System for Mobile Phones," Dependable Systems and Networks Workshops (DSN-W), 2011 IEEE/IFIP 41st International Conference on, vol., no., pp.31-32, 27-30 June 2011.
[4]. Dr.Marwan Omar, Dr. Maurice Dawson,"Reseach in Progress-Defending Android Smartphones from Malware Attacks," Advanced Computing and Communication Technologies (ACCT), 2013 Third International Conference on, vol., no., pp.288-292, 6-7 April 2013.
[5]. Muhamed Halilovic, Abdulhamit Subasi, "Intrusion Detection on Smartphone".
[6]. Masoud Ghorbanian, Bharanidharan Shanmugam, Ganthan Narayansamy, Norbik Bashah Idris,"Signature-Based Hybrid Intrusion Detection System(HIDS) for Android Devices," Business Engineering and Industrial Applications Colloquium (BEIAC), 2013 IEEE, vol., no., pp.827-831, 7-9 April 2013.

Abstract: Image retrieval systems are finding their applications in all automation systems, wherein automated decision needs to be taken based on the image contents. The prime requirement of such systems is to develop a very accurate coding system for maximum retrieval accuracy. Due to the processing error or surrounding errors the efficiency of such systems is reduced, so for the optimization of recognition efficiency, a linear coding for curvature based image recognition system is developed. This paper presents an approach of linear representation of curvature scale coding for an image shape descriptor. In this approach, an average curvature scale representation is done and an empirical modeling of signal decomposition is applied for feature description. In the process of empirical feature description, a spectral density based coding approach is also proposed for the selection of descriptive shape information from the extracted contour regions. This approach is named as Linear Curvature Empirical Coding (LCEC) which is simpler to derive shape features from curvature information based on linear signal representation and coding. The results show that our proposed approach performs better in comparison with previous known approaches.

[1] Hankyu Moon, Rama Chellappa, and Azriel Rosenfeld, Optimal Edge-Based Shape Detection, IEEE Transactions on Image
Processing, Vol. 11, No. 11, November, 2002.
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12th international conference on computer vision workshops, IEEE ,2009.
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descriptor and the whitening Zernike moment shape descriptor," IEEE signal processing, Vol. 16, No. 10, October 2009.
[4] Jamie Shotton, Andrew Blake, Roberto Cipolla, Contour-Based Learning for Object Detection", Proc.10th International Conference
on Computer Vision, IEEE, 2005.
[5] Xiang Baia, Xingwei Yang, Longin Jan Latecki, Detection and recognition of contour parts based on shape similarity, Pattern
recognition, Elsevier 2008.

Abstract: The cyberspace driven by information systems and the Internet is transforming our environment in extraordinary ways by enabling economic growth and providing new means by which people connect, interact and collaborate with one another. The continuous evolution of components of information and communications technology (ICT); advances in the underlying digital components (core electronics) and the corresponding reduction in costs suggest that the Internet is increasingly becoming more readily available and accessible worldwide. The outcome is that more and more people around the globe will ultimately rely on the effective functioning of the Internet to survive and prosper.

[1]. UK Cabinet Office, (2011), The UK Cyber Security Strategy, [online], Available from:www.cabinetoffice.gov.uk, [Accessed:25/03/2014]
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[3]. Steve Ranger, (2015), inside the secret digital arms race: Facing the threat of a global cyberwar. [online] Available from: http://www.techrepublic.com/article/inside-the-secret-digital-arms-race/. [Accessed:25/04/2015]
[4]. BBC, (2007), The cyber raiders hitting Estonia, [online] Available from: http://news.bbc.co.uk/2/hi/europe/6665195.stm. [Accessed: 25/04/2015]
[5]. James Bamford (2013), God of War (The Secret War), Wired USA

Abstract: Hausa, a highly inflected language, needs a worthy stemming approach for efficient information retrieval (IR). However, there is a limited or unavailable study to stemming in the language. Stemming refers to the systematic way of reducing a word to its base or root form. It is a crucial aspect in the field of natural language processing (NLP) such as text summarization and machine translation. As such, this study inspirationally presents an automatic word stemming system for Hausa language with a view to contributing to the field of electronic text processing, as well as NLP, in general.

[1]. Lovins, Julie B. Development of a stemming algorithm. MIT Information Processing Group, Electronic Systems Laboratory, 1968.
[2]. Frakes, W. B. "Introduction to information storage and retrieval systems." Space 14 (1992): 10.
[3]. Abdullah, Syed, Engku Fadzli Hasan, Syarilla Ahmad Saany, Hasni Hassan, Mohd Satar, and Siti Dhalila. "Simple Rules Malay Stemmer." In The International Conference on Informatics and Applications (ICIA2012), pp. 28-35. The Society of Digital Information and Wireless Communication, 2012.
[4]. Pande, B. P., Pawan Tamta, and H. S. Dhami. "Generation, Implementation and Appraisal of an N-gram based Stemming Algorithm." arXiv preprint arXiv:1312.4824 (2013).
[5]. Dianati, Mohammad Hassan, Mohammad Hadi Sadreddini, Amir Hossein Rasekh, Seyed Mostafa Fakhrahmad, and Hossein Taghi-Zadeh. "Words Stemming Based on Structural and Semantic Similarity." Computer Engineering and Applications Journal 3, no. 2 (2014): 89-99.
[6]. Smirnova, Mirra Aleksandrovna. The Hausa language: a descriptive grammar. Routledge & Kegan Paul, 1982.
[7]. Newman, Paul. The Hausa language: An encyclopedic reference grammar. Yale University Press, 2000.

Abstract: Users face many challenges in successfully completing web forms (either online or offline i.e. application-based). This research examines the pitfalls in these forms with respect to its user interface (UI) attributes and how they affect the overall form-filling experience. The factors on which the study was carried out are based on the look, arrangement of elements, validation and alert-patterns, etc. We also explore the potential solutions to some common web form problems and provide new directions based on our explorations with surveys and case studies. This paper aims to ensure productive usability through understanding the techniques and practices of implementing responsive UI. The intention of this research is: i) To study issues and usability scenarios when dealing with UI of online web forms through a Case Study and illustrated examples.

[1]. Wilbert O. Galitz, "The Essential Guide to User Interface Design", Wiley India Edition
[2]. Designing User Interfaces For Business Web Applications by Janko Jovanovic www.smashingmagazine.com/2010/02/25/designing-user-interfaces-for-business-web-applications/
[3]. www.disneyresearch.com
[4]. Web Security Context: User Interface Guidelines, W3C Recommendation (12 August 2010)
[5]. www.w3.org/TR/wsc-ui/
[6]. Flat UI and Forms by Jessica Enders (October 15, 2013)

Abstract: The securityof videoapplications such as commercial videos, military videos and othershave become an important field of research recently. One of the most secure algorithms is Advanced Encryption Standard (AES) algorithm;however this algorithm is inefficient for dealing with video encryption due to its slowness property. This paper proposes a new modifiedof AES to make it more suitable for encrypting digital video. The Modification focuses on the slowest transformations in original AES which is mix columnstransformationsand replace them with newHenon map chaoticbased mask and one mix columns transformation. Resulting in a significant reduction in encryption and decryption time and enhance the security level of AES algorithm, and also the key space is increased as observed in the simulation results of proposed system.
Keywords: AES-128, Chaotic mask, Henon map, Sub-Byte, Mix columns.

[1]. S. Al-Maadeed, A. Al-Ali, and T. Abdalla, "A New Chaos-Based Image-Encryption and Compression Algorithm", Journal of Electrical and Computer Engineering, 2012.
[2]. K.Sakthidasan, A. Sankaran And B.V.Santhosh Krishna "A New Chaotic Algorithm For Image Encryption And Decryption Of Digital Color Images", International Journal Of Information And Education Technology, June 2011.
[3]. Axantum Software AB, "About AES – Advanced Encryption Standard", Svante, Seleborg, 2007.
[4]. H. Kezia and Gnanou F. Sudha, "Encryption of Digital Video Based on Lorenz Chaotic System", IEEE, 2008.
[5]. S.Kamaliand et al, " A New Modified Version of Advanced Encryption Standard Based Algorithm for Image Encryption" International Conference on Electronics & Information Engineering, IEEE,2010.

Abstract: In this paper, proposing visualized and quantitative evaluation methods for validation dimensionality reduction techniques performance. Four well known techniques for dimensionality reduction evaluated, verify the capacity of generating a lower dimensional chemical space with minimum information error. Real chemical database used to generate a sample with specific structure as an input to evolution process. The evaluation is performed in two ways: first visually checking the sample structure, second measuring the local and global distance based error rate that are trained on the low-dimensional data representation. All the evaluation have been done for the four dimensional reduction techniques then result shows weather "trustable" to technique that likely preserves properties with low generalization error and "Un-trustable" which does not preserve the properties.

[1]. K. Fukunaga. Introduction to Statistical Pattern Recognition. Academic Press Professional, Inc., San Diego, CA, USA, 1990.
[2]. J. Gastring (2003). Handbook of Chemoinformatics Vol(1): pp 231-251.
[3]. H. Hotelling (1933). Analysis of a complex of statistical variables into principal components. Journal of Educational Psychology, 24,pp417–441.
[4]. J. Goldberger, S. Roweis, G. Hinton and R. Salakhutdinov, "Neighbourhood Components Analysis," Advances in Neural Information Processing Systems, vol. 17, pp. 513-520, 2005.
[5]. S. Lafon, A.B. Lee (2006). Diffusion maps and coarse-graining: A unified framework for dimensionality reduction, graph partitioning, and data set parameterization. IEEE Transactions on Pattern Analysis and Machine Intelligence, 28(9), pp1393–1403.
[6]. C. Lipinski, A. Hopkins (2004). Chemical space and biology Nature, 432, 855-861.

Abstract: Most business processes update with respect time, existing or old process mining strategies used to resolve those processes when they are under the stable position. My attempt is to improve the existing Drift Detection in complex Datasets. Organizations would be interested in discovering the progression of change. There are other applications such as deriving a configurable model for the process change. Online learning algorithms manage concept drifts in process. There are many dissimilar diversity levels in learning machines are needed for keep high generalization. Motivated by this concept, propose a new online learning model named as Diversity for Dealing with Drifts (DDD). By Comparing DDD with other method EDDM conclude that DDD gives higher accuracy. It keeps ensembles with many dissimilar diversity levels and can achieve good accuracy than EDDM. Moreover, it is strong and precise when there are false positive drift detections occur than EDDM. DDD always performed drift handling under many different situations, with very low errors.

Keywords: Ensemble learning, Diversity, Concept Drift, DDD.

[1]. Manoj Kumar M V,Likewin Thomas, Annapa B, "Phenomenon Of Concept Drift From Process Mining Insight"Department Of CSE,NITK,978-1-4799-2572-8/14/$31.00 2014 IEEE.
[2]. Stb Prof. Dr. Nick Gehrke Nordakademie "Process Mining" Chair For Information Systems Köllner Chaussee 11,Michael Werner, Dipl.-Wirt.-Inf. University Of Hamburg Chair For Information Systems , Max-Brauer-Allee 60 D-22765 Hamburg.
[3]. R. P. Jagadeesh Chandra Bose, Wil M. P. Van Der Aalst, Indr˙E Žliobait˙E, And Mykola Pechenizkiy, "Dealing With Concept Drifts In Process Mining", Ieee Transactions On Neural Networks And Learning Systems, Vol. 25, No. 1, January 2014.
[4]. Online Techniques For Dealing With Concept Drift In Process Mining, Josep Carmona And Ricard Gavalda, Universitat Polit_Ecnica De Catalunya Barcelona, Spain 2013.
[5]. J. Carmona And R. Gavaldà, "Online Techniques For Dealing With Concept Drift In Process Mining," In Proc. Int. Conf. IDA, 2012, Pp. 90–102.

Abstract: The Task scheduling is an importantevent for the act of network infrastructure, in the reality of users request and dependency of load the network to provide convenient quality of service for managing the millions of files. The file sharing is particularly widespread web service within the recent years the load balancing is in troublesome issue as these facilities extents. The server ineffectual to tolerate the load given by the users and does not give a response of the time below the circumstances of traffic.

[1]. E. Ilavarasan and P. Thambidurai, ``Low complexity performance effective task scheduling algorithm forheterogeneous computing environments,'' J. Comput. Sci., vol. 3, no. 2, pp. 94_103, 2007.
[2]. [2] Q. Kang, H. He, and H. Song, ``Task assignment in heterogeneous computing systems using an effective iteratedgreedy algorithm,'' J. Syst. Softw., vol. 84, no. 6, pp. 985_992, 2011.
[3]. S. Kang and A. Dean, ``DARTS: Techniques and tools for predictably fast memory using integrated data allocation and real-time task scheduling,'' in 948 Proc. 16th IEEE RTAS, Apr. 2010, pp. 333_342.
[4]. J. Kreku, K. Tiensyrjä, and G. Vanmeerbeeck, ``Automatic workload generation for system-level exploration based on modified GCC compiler,'' in Proc. Des., Autom. Test Eur. Conf. Exhibit., 2010, pp. 369_374.
[5]. K. Lakshmanan, D. de Niz, and R. Rajkumar, ``Coordinated task scheduling, allocation and synchronization on multiprocessors,'' in Proc. 30th IEEE RTSS, Dec. 2009, pp. 469_478.

Abstract: Now a day's text documents is advancing over internet, e-mails and web pages. As the use of internet is exponentially growing, the need of massive data storage is increasing. Normally many of the documents contain morphological variables, so stemming which is a preprocessing technique gives a mapping of different morphological variants of words into their base word called the stem. Stemming process is used in information retrieval as a way to improve retrieval performance based on the assumption that terms with the same stem usually have similar meaning.

[1]. Sandeep R. Sirsat, Dr. Vinay Chavan and Dr. Hemant S. Mahalle, Strength and Accuracy Analysis of Affix Removal Stemming Algorithms, International Journal of Computer Science and Information Technologies, Vol. 4 (2) , 2013, 265 - 269.
[2]. S.P.Ruba Rani, B.Ramesh, M.Anusha and Dr. J.G.R.Sathiaseelan, Evaluation of Stemming Techniques for Text Classification ,International Journal of Computer Science and Mobile Computing, Vol.4 Issue.3, March- 2015, pg. 165-171
[3]. Ms. Anjali Ganesh Jivani, A Comparative Study of Stemming Algorithms, International Journal Comp. Tech. Appl.(IJCTA) 2011, Vol 2 (6), 1930-1938 ISSN:2229-6093
[4]. Deepika Sharma, Stemming Algorithms: A Comparative Study and their Analysis, International Journal of Applied Information Systems (IJAIS) Foundation of Computer Science, FCS, New York, USA September 2012 ISSN : 2249-0868 Volume 4– No.3

Abstract: In today's world, social media is used every individual for expressing their feelings, opinion, experiences' and emotions. Applying data mining on all these emotions expressed in posts, comments and likes called as social media data. In Existing system, only the prominent themes are identified with relatively large number of tweets in the data. There are a variety of other issues hidden in the "others" theme. Several of these issues may be of great interest to education researchers and practitioners. The fact that the most relevant data which are found on engineering students' learning experiences involve complaints, issues, and problems does not mean there are no positive sides in students' learning experiences'.

[1]. Xin Chen, Mihaela Vorvoreanu, and Krishna Madhavan "Mining Social Media Data for Understanding Students' Learning Experiences," IEEE transactions on learning technologies, manuscript id 1, pp. 1-14, 2013.
[2]. Ajay Kumar Pal, Saurabh Pal, "Classification model of Predication for Placement of Students," in I.J. modern Education and Computer Science, pp. 49-56, November 2013.
[3]. Hsin-Ying Wu, Kuan-Liang Liu and Charles Trappey, "Understanding Customers Using Facebook Pages: Data Mining Users Feedback Using Text Analysis", IEEE 18th International Conference on Computer Supported Cooperative Work in Design, 2014, pp. 346-350.
[4]. I-Hsien Ting, Shyue-Liang Wang, Hsing-Miao Chi and Jyun-Sing Wu, "Content Matters: A study of hate groups detection based on social networks analysis and web mining ", IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, 2013,pp. 1196-1201.

Abstract: In this paper, we propose study of weather advisory system development by using Fuzzy Logic based approach. Agricultural productivity largely depends upon weather. Weather forecasts in all temporal ranges are desirable for effective planning and management of agricultural practices. The development of response strategy helped farmers realize the potential benefits of using weather-based agro meteorological information in minimizing the losses due to adverse weather conditions, thereby improving yield, quantity and quality of agricultural productions. The nature of weather is uncertain and viable we are using Fuzzy approach for the development of system.

[1]. Parvinder M., Rathore L., (2011) "Economic impact assessment of the Agrometeorological Advisory Service of India" Current Science, Vol. 101, No. 10
[2]. L.S.Rathore., Parvinder Maini., (2008) "Project report on Economic Impact Assessment of Agro-Meteorological Advisory Service of The National Centre For Medium Range Weather Forecast"

Abstract: The cloud computing is considered the latest network infrastructure that supports the decentralization of computing. The main features of the Cloud are the possibilities for building applications and providing various services to the end user by virtualization on the internet. One of the main challenges in the field of the cloud computing is the task scheduling problem. Task scheduling problem concerns about the dynamic distribution of the tasks over the Cloud resources to achieve the best results. Many of the algorithms have been existed to resolve the task scheduling problem such as a Particle Swarm Optimization algorithm (PSO). The PSO is a simple parallel algorithm that can be applied in different ways to resolve the task scheduling problems.

[1]. Mishra, R. and A. Jaiswal, Ant colony optimization: A solution of load balancing in cloud. International Journal of Web & Semantic Technology (IJWesT), 2012. 3(2): p. 33-50.
[2]. Uma, J., V. Ramasamy, and A. Kaleeswaran, Load Balancing Algorithms in Cloud Computing Environment-A Methodical Comparison. International Journal of Advanced Research in Computer Engineering & Technology (IJARCET) Volume. 3.
[3]. Nishant, K., et al. Load balancing of nodes in cloud using ant colony optimization. in Computer Modelling and Simulation (UKSim), 2012 UKSim 14th International Conference on. 2012. IEEE.
[4]. Calheiros, R.N., et al., CloudSim: a toolkit for modeling and simulation of cloud computing environments and evaluation of resource provisioning algorithms. Software: Practice and Experience, 2011. 41(1): p. 23-50.
[5]. Kennedy, J. and R. Eberhart. Particle swarm optimization. in Neural Networks, 1995. Proceedings., IEEE International Conference on. 1995.