Abstract: Online Social Networks (OSNs) are inherently designed to enable people to share personal and public information and make social connections with others. These OSNs provides digital social interactions and social as well as personal information sharing, but in sharing a number of security and privacy problems raised. While OSNs allow users to restrict access to shared data, they currently do not provide any mechanism to totally enforce privacy issue solver associated with multiple users. To this end, we propose an approach to enable the protection of shared data associated with multiple users in OSNs. We formulate an access control model to capture the essence of multiparty authorization requirements, along with a multiparty policy specification scheme and a policy enforcement mechanism. Besides we also implement a proof-of-concept prototype which is called as MController (multi controller) having contributor, stakeholder and disseminator controllers along with owner controller.
Index Terms: social network, multi party access control, MController, decision voting.

[1] Hongxin Hu, Gail-Joon Ahn, Senior Member, IEEE, and Jan Jorgensen "Multiparty Access Control for Online Social Networks: Model and Mechanisms" IEEE transactions,2012.
[2] Besmer and H. Richter Lipford. "Moving Beyond Untagging: Photoprivacy in A Tagged World". pages 1563–1572. ACM, 2010.
[3] L. Bilge, T. Strufe, D. Balzarotti and E. Kirda. "All Your Contacts are Belong to Us: Automated Identity Theft Attacks On Social Networks". pages 551–560. ACM, 2009.
[4] Carminati and E. Ferrari. "Collaborative Access Control in Online Social Networks". pages 231–240. IEEE, 2011.
[5] Carminati, E. Ferrari, and A. Perego. "Rule-Based Access Control for Social Networks". pages 1734–1744. Springer, 2006.
[6] B. Carminati, E. Ferrari, and A. Perego. "Enforcing access control in web-based social networks." ACM Transactions on Information and System Security (TISSEC), 13(1):1–38, 2009.
[7] Carrie. "Access Control Requirements for Web 2.0 Security and Privacy." In Proc. of Workshop on Web 2.0 Security & Privacy (W2SP). Citeseer, 2007.
[8] J. Choi, W. De Neve, K. Plataniotis, and Y. Ro. "Collaborative face recognition for improved face annotation in personal photo collections shared on online social networks." Multimedia, IEEE Transactions on, 13(1):14–28, 2011.
[9] P. Fong. "Preventing sybil attacks by privilege attenuation: A design principle for social network systems." In Security and Privacy (SP), 2011 IEEE Symposium on, pages 263–278. IEEE, 2011.
[10] P. Fong."Relationship-based access control: Protection model and policy language". In Proceedings of the first ACM conference on Data and application security and privacy, pages 191–202. ACM, 2011.

Abstract: Frequent pattern mining is an important chore in the data mining, which reduces the complexity of the data mining task. The usages of frequent patterns in various verticals of the data mining functionalities are discussed in this paper. The gap analysis between the requirements and the existing technology is also analyzed. State of art in the area of frequent pattern mining was thrashed out here. Working mechanisms and the usage of frequent patterns in various practices were conversed in the paper. The core area to be concentrated is the minimal representation, contextual analysis and the dynamic identification of the frequent patterns.

Keywords: Frequent pattern, Association, Clustering, Classification

[1] Jiawei Han, Hong Cheng, Dong Xin,Xifeng Yan, "Frequent pattern mining: current status and future Directions", Data Mining and Knowledge Discovery, Vol. 15 (2007), pp. 55-86.

[2] Agrawal R, Imielinski T, Swami A (1993) Mining association rules between sets of items in large databases. In: Proceedings of the 1993ACM-SIGMODinternational conference on management of data (SIGMOD'93), Washington, DC, pp 207–216

[3] Agrawal R, Srikant R (1994) Fast algorithms for mining association rules. In: Proceedings of the 1994 international conference on very large data bases (VLDB'94), Santiago, Chile, pp 487–499

[4] Mannila H, Toivonen H, Verkamo AI (1994) Efficient algorithms for discovering association rules. In: Proceeding of the AAAI'94 workshop knowledge discovery in databases (KDD'94), Seattle, WA, pp 181–192

[5] Park JS, Chen MS, Yu PS (1995) An effective hash-based algorithm for mining association rules. In: Proceeding of the 1995 ACM-SIGMOD international conference on management of data (SIGMOD'95), San Jose, CA, pp 175–186 [6] Savasere A, Omiecinski E, Navathe S (1995) An efficient algorithm for mining association rules in large databases. In: Proceeding of the 1995 international conference on very large data bases (VLDB'95), Zurich, Switzerland, pp 432–443

[7] Toivonen H (1996) Sampling large databases for association rules. In: Proceeding of the 1996 international conference on very large data bases (VLDB'96), Bombay, India, pp 134–145

[8] Brin S, Motwani R, Ullman JD, Tsur S (1997) Dynamic itemset counting and implication rules for market basket analysis. In: Proceeding of the 1997 ACM-SIGMOD international conference on management of data (SIGMOD'97), Tucson, AZ, pp 255–264

[9] Cheung DW, Han J, Ng V, Wong CY (1996) Maintenance of discovered association rules in large an incremental updating technique. In: Proceeding of the 1996 international conference on data engineering (ICDE'96), New Orleans, LA, pp 106–114

[10] Park JS, Chen MS, Yu PS (1995) Efficient parallel mining for association rules. In: Proceeding of the 4th international conference on information and knowledge management, Baltimore, MD, pp 31–36

Abstract: Adequate user authentication is a persistent problem, particularly with hand- held devices such as Personal Digital Assistants (PDAs), which tend to be highly personal and at the fringes of an organization's influence. Yet, these devices are being used increasingly in corporate settings where they pose a security risk, not only by containing sensitive information, but also by providing the means to access such information over wireless network interfaces. User authentication is the first line of defense for a lost or stolen PDA. How- ever, motivating users to enable simple PIN or password mechanisms and periodically update their authentication information is a constant struggle. This paper describes a general-purpose mechanism for authenticating a user to a PDA using a visual login technique called Picture Password. The underlying rationale is that image recall is an easy and natural way for users to authenticate, removing a serious barrier to compliance with organizational policy. Features of Picture Password include style dependent image selection, password reuse, and embedded salting, which overcome a number of problems with knowledge-based authentication for handheld devices. Though designed specifically for handheld devices, Picture Password is also suitable for note-books, workstations, and other computational devices. Scrambling technique is applied to make image recognition more complex during the login process and thus protecting from the common attacks in the graphical password system.

Keywords: Graphical Passwords, Security, Image Scrambling,KBRP.

[1] The Quest to Replace Passwords: A Framework for Comparative Evaluation of Web Authentication Schemes,Joseph Bonneau University of Cambridge Cambridge, UK jcb82@cl.cam.ac.uk Cormac Herley Microsoft Research Redmond, WA, USA cormac@microsoft.com Paul C. van Oorschot Carleton University Ottawa, ON, Canada paulv@scs.carleton.ca Frank Stajanoy University of Cambridge Cambridge, UK
frank.stajano@cl.cam.ac.uk

[2] Persuasive Cued Click-Points: Design, Implementation, and Evaluation of a Knowledge-Based Authentication Mechanism Sonia Chiasson, Member, IEEE, Elizabeth Stobert, Student Member, IEEE, Alain Forget, Robert Biddle, Member, IEEE, and Paul C. van Oorschot, Member, IEEE.IEEE TRANSACTIONS ON DEPENDABLE AND SECURE COMPUTING, VOL. 9, NO. 2, MARCH/APRIL 2012

[3] Persuasive Cued Click Points with Click Draw Based Graphical Password Scheme P. R. Devale Shrikala M. Deshmukh, Anil B. Pawar.
[4] Purely Automated Attacks on PassPoints-Style Graphical Passwords Paul C. van Oorschot, Amirali Salehi-Abari, and Julie Thorpe
IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY, VOL. 5, NO. 3, SEPTEMBER 2010

[5] S. Chiasson, P. van Oorschot, and R. Biddle, ?Graphical Password Authentication Using Cued Click Pointsm Pro c. European Symp. Research in Computer Security (ESORICS), pp. 359-374, Sept. 2007.

[6] The science of guessing: analyzing an anonymized corpus of 70 million passwords Joseph Bonneau Computer Laboratory University of Cambridge jcb82@cl.cam.ac.uk. 2012 IEEE Symposium on Security and Privacy

[7] Dimitri Van De Ville, W.P., Rik Van de Walle, Ignace Lemahieu, Image Scrambling Without Bandwidth Expansion. IEEE Transactions on Cirsuits and Systems for Video Technology, 2004. 14

[8] AN IMAGE SCRAMBLING ALGORITHM USING PARAMETER BASED M-SEQUENCES YICONG ZHOU1, KAREN PANETTA1, FELLOW, IEEE, SOS AGAIAN2, SENIOR MEMBER, IEEE.

[9] Guosheng Gu, g.H. The application of chaos and DWT in image scrambling. in Proceeding of the Fifith Interational Conference on Machine Learning and Cybernetics. 2006. Dalian.

[10] S. Agaian, J.A., K. Egiazarian, P. Kuosmanen, Decompositional methods for stack filtering using Fibonacci pcodes. Signal Processing, 1995. 41: p. 101-110.

Abstract: An algorithm for detection of hidden objects from tera hertz images is presented. Presently, terahertz imaging employs object's radiometric temperatures in human to acquire images of concealed objects. But, it presents problem in temperature sensitive areas like oil and coal mines, factories etc. The aim of the paper is to detect and extract hidden objects underneath person's clothing. Here, a three stage approach is presented: In the first stage, edge based segmentation is applied after smoothing the image using bilateral filter. In the next stage, transform invariant shape descriptors, Gabor and gray level co-occurrence (GLCM) texture features of interested object regions are computed. Finally, a Euclidean distance criterion is used for classification. To appraise the technique, detection error and detection rate are calculated. Test results are compared with ground truth data obtained from the original image. Experiment results are found to be promising with 1.04% detection error and 91.9% as detection rate. Potential applications in security include detection of weapons and explosive in public places like airports, stations etc.

Key words: Edge detection, GLCM features, Gobor features, Shape descriptors, THZ images.

[1]. Jan Flusser , Moment Invariants in Image Analysis, World Academy of Science, Engineering and Technology 11 , 2005,pp:376-381.
[2] KapilevichB.,Detecting Hidden Objects on Human Body Using Active Millimeter Wave Sensor, Sensors Journal, IEEE, Volume: 10, Issue: 11, On Page(s): 1746 – 1752.

[3]. Xilin,Shencharles R Dietlein, Erich Grossman, Zoya Popvic and Francois G Meyer, Detection & Segmentation of concealed objects in Terahertz Images, IEEE Transactions on Image Processing, 17 (12), pp 2465-2475, 2008.

[4]. Federici, John F.; Schulkin, Brian; Huang, Feng; Gary, Dale; Barat, Robert; Oliveira, Filipe; Zimdars, David , THz imaging and sensing for security applications—explosives, weapons and drugs, ,Semiconductor Science and Technology, Volume 20, Issue 7, pp. S266-S280 (2005).

[5]. Hai-Bo Liu, Yunqing Chen, Glenn J. Bastiaans, and X.-C. Zhang, Detection and identification of explosive RDX by THz diffuse reflection spectroscopy, Optics Express, Vol. 14, Issue 1, pp. 415-423 (2006) Magazine:

[6]. H. Chen, S. Lee, R. Rao, M.-A. Slamani, and P. Varshney, Imaging for concealed weapon detection," IEEE Signal Processing Magazine, pp. 52–61, March 2005.

[7]. Dr Alan J. Lipton, Craig H. Heartwell, Dr Niels Haering, and Donald Madden, Critical Asset Protection, Perimeter Monitoring, and Threat Detection Using automated Video Surveillance , IEEE AESS systems magazine , 2003 Books:

[8]. Milan Sonaka, Vaclav Hlavac, Roger Boyle, Image processing, Analysis, and Machine Vision (Thomson learning Inc. ISBN : 981-240-061-3, 1998). [9]. Rafael C.Gonzalez, Richard E.Woods, Digital Image processing ( PHI Learning Private Ltd. New Delhi, ISBN: 978-81-203-3640-7. 2008).

Abstract: In this paper we are identifying the frequently appearing object in a video. This frequently appearing object is called thematic object. If an object appears many times in a video such objects are called thematic object. Identifying this frequently appearing object in a video is helpful for object search and tagging of that object. To identify thematic pattern in the video we must give an object as an input and then we try to find corner points of that object by Harris corner detection algorithm. Later we can find the similarity between the reference image and test frame by extracting the descriptors around the corner point. We are mining the video to identify the common patterns that appears in that video. The proposed approach will help to identify the object even when there is partial occlusion and variation in the viewpoint.

Index Terms: Common Patterns, Corner points, Key object, Video data mining.

[1] Junsong Yuan, Gangqiang Zhao, Yun Fu, Zhu Li, Aggelos K. Katsaggelos and Ying Wu, "Discovering Thematic Objects in Image Collections and Videos" IEEE Transactions on Image Processing vol.21, No. 4, April 2012.
[2] Davide Liu, Tshun Chen: "DISCOV :A Framework for Discovering Objects in Video", IEEE Transactions on Multimedia, Vol. 10,No.2, February 2008.
[3] David Liu and Tshun Chen: "A Topic-Motion Model for Unsupervised Video Object Discovery".
[4] Alok K. Watve: "Object tracking in video scenes".
[5] Zhengwei Yang and Fernand S. Cohen, "Image Registration and Object Recognition Using Affine Invariants and Convex Hulls", IEEE Transactions on Image Processing, Vol 8, No. 7, July 1999.
[6] Ying Shan, Harpreet S. Sawhney, Art Pope: "Measuring the Similarity Of Two Image Sequences".
[7] David Liu, Gang Hua, Tsuhan Chen: " A Hierarchical Visual Model for Video Object Summerization".IEEE Transactions on Pattern analysis and Machine Intelligence vol 32 December 2010.
[8] John Canny: "A Computational approach to Edge Detection". Pattern Analysis and Machine Intelligence, IEEE Transactions on PAMI Nov 1986.
[9] Harris, C., Stephens : "A Combined Corner and Edge Detector", Proceedings of Alvey Vision Conference, 1988.
[10] Hung Khoon Tan and chongwah Ngo " Localized matching using earth mover's distance towards discovery of common patterns from small image samples:

Abstract: In Classical Hypothesis testing volumes of data is to be collected and then the conclusions are drawn, which may need more time. But, Sequential Analysis of Statistical science could be adopted in order to decide upon the reliability or unreliability of the developed software very quickly. The procedure adopted for this is, Sequential Probability Ratio Test (SPRT). It is designed for continuous monitoring. The likelihood based SPRT proposed by Wald is very general and it can be used for many different probability distributions. In the present paper we propose the performance of SPRT on 4 data sets of Time domain data using exponential model and analyzed the results. The parameters are estimated using Maximum Likelihood Estimation method.

Keywords: SPRT, SRGM,HPP,NHPP, MLE, Goel-Okumoto model.

[1] Goel, A.L and Okumoto, K. (1979). "A Time Dependent Error Detection Rate Model For Software Reliability And Other
Performance Measures", IEEE Transactions on Reliability, vol.R-28, pp.206-211, 1979.
[2] Pham. H., (2006). "System software reliability", Springer.
[3] Reckase, M. (1983). A procedure for Decision Making Using Tailored Testing, 238-257, New Horizons In Testing – Latent Trait
Test Theory and Computerized Adaptive Testing, Ed. David J. Weiss, Academic Press, New York.
[4] Satya Prasad (2007)."Half logistic Software reliability growth model "Ph.D Thesis of ANU, India.
[5] Stieber, H.A. (1997). "Statistical Quality Control: How To Detect Unreliable Software Components", Proceedings the 8th
International Symposium on Software Reliability Engineering, 8-12.
[6] Wald. A., 1947. "Sequential Analysis", John Wiley and Son, Inc, New York.
[7] Xie, M., Goh. T.N., Ranjan.P., "Some effective control chart procedures for reliability monitoring" -Reliability engineering and
System Safety 77 143 -150¸ 2002.

Abstract: Real-Time systems are becoming pervasive. In a Real-Time System the correctness of the system behavior depends not only on the logical results of the computations, but also on the physical instant at which these results are produced. A missed deadline in hard real-time systems is catastrophic and in soft real-time systems it can lead to a significant loss .This work talks about static and dynamic scheduling algorithms for real time task. The problem of real-time scheduling spans a broad spectrum of algorithms from simple uniprocessor to highly sophisticated multiprocessor scheduling algorithms which are priority driven and divided into three classes fixed priority, dynamic priority and hybrid priority. Finally conclusion shows that Instantaneous utilization factor scheduling Algorithm gives better result in uniprocessor scheduling algorithms and Modified Instantaneous utilization factor scheduling Algorithm gives better context switching, response time and CPU utilization as compared to previous scheduling algorithms.

Keywords- Deadline, Laxity, Utilization, Precedence, context switching.

[1] Jashweeni Nandanwar, Urmila Shrawankar, "An Adaptive Real Time Task Scheduler", IJCSI International Journal of Computer Science Issues, Vol. 9, Issue 6, November 2012.

[2] H. S. Behera, Naziya Raffat, Minarva Mallik, " A Modified Maximum Urgency First Scheduling Algorithm with EDZL for Multiprocessors in Real Time Applications", Volume 2, Issue 4, April 2012.

[3] Jinkyu Leea, Arvind Easwaranb, Insik Shina,∗, Insup Lee, "Zero-laxity based real- time multiprocessor scheduling", The Journal of Systems and Software, 2011.

[4] Francis Cottet,"Scheduling in Real Time Syatem", John W. Wiley & Sons Ltd, The Atrium, Southern Gate, Chichester, West Sussex PO19 8SQ, England, 2002.

[5] Arezou Mohammadi and Selim G. Akl, "Scheduling Algorithms for Real-Time Systems", Technical Report No. 2005-499, July 15, 2005.

[6] Yoo, Myungryun and M. Gen, "Study on Scheduling for Real- time Task by Hybrid Multiobjective Genetic Algorithm", Thesis, 2006.

[7] David B. Stewart, Pradeep Khosla, "Real-Time Scheduling of Sensor-Based Control Systems", 1991.

[8] Komal S. Bhalotiya, "Customised Multiprocesssor Scheduling Algorithms For Real time Systems", Proceedings published by International Journal of Computer Applications® (IJCA) ISSN: 0975 – 8887, April, 2012.

[9] Radhakrishna Naik, "Instantaneous Utilization Based Scheduling Algorithms for Real Time Systems", (IJCSIT) International Journal of Computer Science and Information Technologies, Vol. 2 (2), 654-662, 2011.

[10] Yi-Hsiung Chao, Shun-Shii Lin, Kwei-Jay Lin, "Schedulability issues for EDZL scheduling on real-Time multiprocessor systems", 2008.

Abstract: Image compression is now essential for applications such as transmission and storage in data bases. In this paper we review and discuss about the image compression, need of compression, its principles, and types of compression and various algorithm of image compression. This paper attempts to give a recipe for selecting one of the popular image compression algorithms based on Wavelet, DCT, and VQ. We review and discuss the implementation of these algorithms. Initially, the colored image of any resolution is selected by the user which gets converted into grayscale image to be taken as an input image for both the techniques. Finally the Performance analysis of the image compression using self organized feature maps and JPEG 2000 Algorithm.

Keywords: - Image Compression, Types, SOM, JPEG2000, Algorithms.

[1.] Banerjee and A. Halder,"An Efficient Dynamic Image Compression Algorithm based on Block Optimization, Byte Compression and Run-Length Encoding along Y-axis", IEEE Transaction, 2010.
[2.] Y. H. Dandawate and M.A. Joshi, "Performance analysis of Image Compression using Enhanced Vector Quantizer designed with Self Organizing Feature Maps: The Quality perspective" IEEE transaction, pg. 128-132, 2007.
[3.] S. Immanuel Alex Pandian and J.Anitha,"A Neural Network Approach for Color Image Compression in Transform Domain", International Journal of Recent Trends in Engineering, Vol 2, No. 2, November 2009, 152.
[4.] H. G. Lalgudi, A. Bilgin, M. W. Marcellin, and M. S. Nadar, "Compression of Multidimensional Images Using JPEG2000", IEEE Signal processing, vol. 15, pg. 393-396, 2008.
[5.] Cheng-Fa Tsai, Chen-An Jhuang, Chih-Wei Liu, "Gray Image Compression Using New Hierarchical Self-Organizing Map Technique, IEEE conference, 2008.
[6.] D. Kumar, C.S. Rai and S. Kumar, "Face Recognition using Self-Organizing Map and Principal Component Analysis", IEEE Transaction, 2005.
[7.] Gregory K. Wallace, "The JPEG Still Picture Compression Standard", IEEE Transactions on Consumer Electronics, December 1991.
[8.] S. Anna Durai & E. Anna Saro, "An Improved Image Compression approach with Self-Organizing Feature Maps", GVIP Journal, Volume 6, Issue 2, September, 2006.
[9.] Sonal, Dinesh Kumar, "A Study of various Image Compression Techniques", IEEE Transaction, 2005.

Abstract: Cached data not only replies local access, but also replies data request issued from other nodes. Wireless Mesh Networks (WMNs) have emerged as an important technology in building next generation fixed wireless broadband networks that provide low cost Internet access for fixed and mobile users. Reduce the number of hops that request/data need to travel in the network. In these attacks, the adversary selectively targets specific packets of "high" importance by exploiting his knowledge on the implementation details of network protocols at various layers of the protocol stack. We illustrate the impact of selective jamming on the network performance by illustrating various selective attacks against the TCP protocol. We show that such attacks can be launched by performing real-time packet classification at the physical layer. We study the idealized case of perfect knowledge by both the jammer and the network about the strategy of one another, and the case where the jammer or the networks lack this knowledge. The latter is captured by formulating and solving optimization problems, the solutions of which constitute best responses of the attacker or the network to the worst-case strategy of each other.

Keywords: Denial-of-service, jamming, Wireless network, packet classification

[1] IEEE Std 802.11i/d3.0. Available at http://www.cs.umd.edu/ mhshin/doc/802.11/802.11i-D3.0.pdf.

[2] AusCERT. AA-2004.02 - denial of service vulnerability in IEEE 802.11 wireless devices. http://www.auscert.org.

[3] P. Bahl and V. Padmanabhan. RADAR: An in-building RF-based user location and tracking system. In Proceedings of IEEE Infocom 2003, pages 775 to784, 2000.

[4] J. Bellardo and S. Savage. 802.11 denial-of-service attacks: Real vulnerabilities and practical solutions. In Proceedings of the USENIX Security Symposium, pages 15 to 28, 2003.

[5] S. Capkun and J. Hubaux. Secure positioning in sensor networks. Technical report EPFL/IC/200444, May 2004

[6] I. Damgard. Commitment schemes and zero-knowledge protocols. Lecture notes in computer science, 1561:63–86, 1999.

[7] A. Juels and J. Brainard. Client puzzles: A cryptographic countermeasure against connection depletion attacks. In Proceedings of the Network and Distributed System Security Symposium, pages 151–165, 1999.

[8] Y. W. Law, M. Palaniswami, L. V. Hoesel, J. Doumen, P. Hartel, and P. Havinga. Energy-efficient link-layer jamming attacks against WSN MAC protocols. ACM Transactions on Sensor Networks, 5(1):1–38, 2009.

[9] L. Lazos, S. Liu, and M. Krunz. Mitigating control-channel jamming attacks in multi-channel ad hoc networks. In Proceedings of the second ACM conference on wireless network security, pages 169– 180, 2009.

[10] R. C. Merkle. Secure communications over insecure channels. Communications of the ACM, 21(4):294–299, 1978.

Abstract: Distributed file systems are key building blocks for cloud computing applications based on the Map Reduce programming paradigm. In such file systems, nodes simultaneously serve computing and storage functions; a file is partitioned into a number of chunks allocated in distinct nodes so that Map Reduce tasks can be performed in parallel over the nodes. However, in a cloud computing environment, failure is the norm, and nodes may be upgraded, replaced, and added in the system. This dependence is clearly inadequate in a large-scale, failure-prone environment because the central load balancer is put under considerable workload that is linearly scaled with the system size, and may thus become the performance bottleneck and the single point of failure. In this paper, a fully distributed load rebalancing algorithm is presented to cope with the load imbalance problem. Our algorithm is compared against a centralized approach in a production system and a competing distributed solution presented in the literature. The simulation results indicate that our proposal is comparable with the existing centralized approach and considerably outperforms the prior distributed algorithm in terms of load imbalance factor, movement cost, and algorithmic overhead.

Keywords: DHT, CentraliseSystem, LoadImBalancing, Distributed System

[1] I. Stoica, R. Morris, D. Liben-Nowell, D. R. Karger, M. F. Kaashoek, F. Dabek, and H. Balakrishnan, "Chord: a Scalable Peer-to-Peer Lookup Protocol for Internet Applications," IEEE/ACM Trans. Netw., vol. 11, no. 1, (Feb. 2003), 17–21.

[2] A. Rowstron and P. Druschel, "Pastry: Scalable, Distributed Object Location and Routing for Large-Scale Peer-to-Peer Systems," LNCS 2218, (Nov. 2001), 161–172.

[3] G. DeCandia, D. Hastorun, M. Jampani, G. Kakulapati, A. Lakshman, A. Pilchin, S. Sivasubramanian, P. Vosshall, and W. Vogels, "Dynamo: Amazon's Highly Available Key-value Store," in Proc. 21st ACM Symp. Operating Systems Principles (SOSP'07), (Oct. 2007), 205–220.

[4] A. Rao, K. Lakshminarayanan, S. Surana, R. Karp, and I. Stoica, "Load Balancing in Structured P2P Systems," in Proc. 2nd Int'l Workshop Peerto-Peer Systems (IPTPS'02), (Feb. 2003), 68–79.

[5] D. Karger and M. Ruhl, "Simple Efficient Load Balancing Algorithms for Peer-to-Peer Systems," in Proc. 16th ACM Symp. Parallel Algorithms and Architectures (SPAA'04), (June 2004), 36–43.

[6] D. DeWitt, R. H. Gerber, G. Graefe, M. L. Heytens, K. B. Kumar, and M. Muralikrishna. Gamma -a high performance dataflow database. In Proc. VLDB, 1986.

[7] H. Feelifl, M. Kitsuregawa, and B. C. Ooi. A fast convergence technique for online heat-balancing of btree indexed database over shared-nothing parallel systems. In Proc. DEXA, 2000.

[8] P. Ganesan, M. Bawa, and H. Garcia-Molina. Online balancing of range-partitioned data with applications to p2p systems. Technical Report http://dbpubs.stanford.edu/pubs/2004-18, Stanford U., 2004.

[9] P. Ganesan, B. Yang, and H. Garcia-Molina. One torus to rule them all: Multi-dimensional queries in p2p systems. In WebDB, 2004.

[10] D. R. Karger and M. Ruhl. Simple efficient load-balancing algorithms for peer-to-peer systems. In Proc. IPTPS, 2004.

Abstract: Many web applications available today make use of some way of session to be able to communicate between the server and client. Unfortunately, it is possible for an attacker to exploit session in order to impersonate another user at a web application. The session hijacking is the most common type of attack in the infrastructure type of network. The confidentially is not providing under this attack to user information. Session hijacking attack is launched by making fake access point. If we detect the fake access point then we can stop session hijacking, and various techniques had been proposed. In this paper, we are giving a new mechanism to detect the fake access point with the use of sensor nodes in the network. In this mechanism we are also giving the protection against IP Spoofing by the use of public private key cryptography key exchange algorithm. We also discuss the results through simulations in Network Simulator 2.

Keywords: Session Hijacking, Fake Access Point, IP spoofing.

[1] Thawatchai Chomsiri ―A Comparative Study of Security Level of Hotmail, Gmail and Yahoo Mail by Using Session Hijacking Hacking Test‖ in International Journal of Computer Science and Network Security, VOL.8 No.5, May 2008.

[2] Srikanth Kamuni, S.ShreehaTejaswini, Bhaskar.J ―Wavelet Based Real Time Session Hijack Detection Based On Bluetooth Signal Analysis‖ in GJCAT, Vol 2 (2), 2012, 1210-1213 ISSN: 2249-1945.

[3] Rupinder Gill, and Smith, Jason and Clark, Andrew ―Experiences in Passively Detecting Session Hijacking Attacks in IEEE 802.11 Networks‖ in: Proceedings of 4th Australasian Information Security Workshop (Network Security), 16-19 January 2006, Hobart, Tasmania.

[4] Bhavna C.K. Nathani Erwin Adi ―Website Vulnerability to Session Fixation Attacks‖ Journal of Information Engineering and Applications ISSN 2224-5782 (print) ISSN 2225-0506 (online)Vol 2, No.7, 2012.

[5] Al-Sammarraie Hosam ,Adli Mustafa and Shakeel ―Exception Agent Detection System for IP Spoofing Over Online Environments‖ International Journal of Computer Science and Information Security, Vol. 6, No. 1, 2009. [6] Mrs. Mridu Sahu and Rainey C. Lal ―Controlling IP spoofing through packet filtering‖ Int.J.Computer Techology & Applications,Vol 3 (1),155-159 ISSN:2229-6093.

[7] Vimal Upadhyay , Rajeev kumar ―Detection and preventing IP spoofing attack by Hashed Encryption‖ International Journal of Enterprise Computing and Business Systems ISSN (Online) : 2230-8849 Vol. 1 Issue 2 July 2011.

[8] Noureldien A. Noureldien, Mashair O. Hussein ―Block Spoofed Packets at Source (BSPS): A method for Detecting and Preventing All Types of Spoofed Source IP Packets and SYN Flooding Packets at Source: A Theoretical Framework‖ International Journal of Networks and Communications 2012, 2(3): 33-37 DOI: 10.5923/j.ijnc.20120203.03.

[9] N.Arumugam, Dr.C.Venkatesh ―A Dynamic Method to Detect IP Spoofing on Data Network Using Ant Algorithm‖ IOSR Journal of Engineering (IOSRJEN) e-ISSN: 2250-3021, p-ISSN: 2278-8719, www.iosrjen.org Volume 2, Issue 10 (October 2012), PP 09-16.

[10] Hemanshu Kamboj, Gurpreet Singh ― Detection of Fake Access Point to Prevent Session Hijacking‖ International Journal for Advance Research and Technology Vol. 1, Issue II, Mar. 2013 ISSN 2320-6802.

Abstract: The emergence of extremely powerful mobile communication devices in recent times has triggered off the development of many exploitative technologies that attempt at leveraging the ever increasing processing, storage and communicating capacities of these devices. One of the most developing area of network is opportunistic network. It provides communication even in disconnected mode. Nodes are mobile and can change their location and message is forward through many intermediate nodes so identity of usersis shown to all.Any intermediate can drop the data packetsif he is not wishes to forward the data to a particular destination id. A few privacy preventing algorithms are proposed to maintain it. In this research we propose an algorithm to maintain the privacy of user if user wants it . We are ensuring the privacy of the data with the use of concept of cluster estimation. In this we use the public private cryptography technique for data encryption and decryption. Algorithm is implemented on NS2 (Network Simulator 2.35).

Keywords: Attacks, Virtual ID, Privacy, NS2

[1]. Anna Scaglione "Opportunistic Large Arrays: Cooperative Transmission in Wireless Multihop Ad Hoc Networks to Reach Far Distances" IEEE TRANSACTIONS ON SIGNAL PROCESSING, VOL. 51, NO. 8, AUGUST 2003.
[2]. Chiara Boldrini, Marco Conti, Andrea Passarella "Exploiting users' social relations to forward data in opportunistic Networks" 1016/j.pmcj.2008.04.003 2008 Elsevier.
[3]. Zehua Wang "CORMAN: A Novel Cooperative Opportunistic Routing Scheme in Mobile Ad Hoc Networks" IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS, VOL. 30, NO. 2, FEBRUARY 2012.
[4]. J.P. Tower and T.D.C. Little "A Proposed Scheme for Epidemic Routing with Active Curing for Opportunistic Networks" In Proc. 1st IEEE Intl. Workshop on Opportunistic Networking, Okinawa, Japan, March 2008.
[5]. Gokce Gorbil, Erol Gelenbe "Opportunistic Communications for Emergency Support Systems" 1877–0509 © 2011 Published by Elsevier 10.1016/j.procs.2011.07.008.
[6]. B.Poonguzharselvi1 and V.Vetriselvi "Trust Framework for Data Forwarding in Opportunistic network Using Mobile Traces" International Journal of Wireless & Mobile Networks (IJWMN) Vol. 4, No. 6, December 2012.
[7]. Abdullatif Shikfa , Melek Önen , Refik Molva "Privacy and confidentiality in context-based and epidemic forwarding" 2010 Published by Elsevier B.V:10.1016/j.comcom.2010.04.035
[8]. Abdullatif Shikfa and Melek Önen and Refik Molva "Local key management in opportunistic networks" Int. J. Communication Networks and Distributed Systems, Vol. 9, Nos. 1/2, 2012.
[9]. Enrico Scalavino, Giovanni Russello and Rudi Ball "An Opportunistic Authority Evaluation Scheme for Data Security in Crisis Management Scenarios" ASIACCS'10 April 13–16, 2010, Beijing, China.
[10]. Ram Ramanathan, Richard Hansen "Prioritized Epidemic Routing for Opportunistic Networks" June11, 2007, San Juan, Puerto Rico, USA.

Abstract: TRIZ, which is a Russian word that stands for "Theory of Inventive Problem Solving", is a problem-solving methodology that was invented based on the belief that there are universal principles of invention that are the foundation for creative innovations that help in advancing technology. One of the most widely used approaches to problem-solving in most technology-related fields is the structured problem-solving methodology. Actually, TRIZ enhances the structured problem-solving methodology by applying its principles to the first few phases of the conventional structured methodology with more creative and advanced steps that makes the problem-solving process more efficient and effective. A brief description of the structured problem-solving methodology is presented since it has a big influence on the original TRIZ methodology. TRIZ's ways of solving problems are explained in detail, and several main applications of TRIZ in the technology-related and other new fields (non-technology) are discussed. Several suggestions are put forward in order to overcome some of the main issues faced by TRIZ in order to improve its effectiveness in solving problems, especially in non-technical and non-scientific domains.

Keywords – Inventive Problem Solving, Problem-Solving Methodology, Structured Problem-Solving, TRIZ

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Abstract: The ability to hold individuals or organizations accountable for transactions is important in most of the commercial and legal or e-transactions. Cloud computing is a new term that is introduced in business environment where users can interact directly with the virtualized resources and safe the cost for the consumers. Where user have everything to be deal on internet on e-transaction to save work and time but we fear for our confidential and individual data is in safe or not, is it been hacked and misused is a fear that stops to use of modern technology. Moreover, users may not know the machines which actually process and host own data. While enjoying the convenience brought by this new technology, end users also start worrying about security of their own personal and important data. Accountability traces every important aspect of any data sharing on data usage in cloud where it accounts every action in the system can be traced back to some entity with assuring the safety and security including the handling of personally identifiable information. In this paper we review the cloud information accountability framework for the data sharing in which procedural and technical solutions are co-designed to demonstrate accountability by the various researchers to resolving privacy and security risks within the cloud and presents a review on new way to supplement the current consumption and delivery model for IT services based on the Internet, by providing for dynamically scalable framework.

Keywords: e-transactions, Accountability, TPA, Tracing Authority.

[1] S. Sundareswaran, A. Squicciarini, D. Lin, " Distributed Accountability for Data Sharing in the Cloud," Proc. IEEE Transactions on Dependable and Secure Computing, Vol. 9, No.4, Aug. 2012.
[2] S. Pearson, "Towards Accountability in the Cloud ," Proc. IEEE Internet Computing, pp. 64-69, 2011
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[4] Siani Pearson and Andrew Charles worth " Accountability as a Way Forward for Privacy Protection in the Cloud".
[5] A. Squicciarini, S. Sundareswaran, and D. Lin, "Preventing Information Leakage from Indexing in the Cloud," Proc. IEEE Int'l Conf. Cloud Computing, 2010.
[6] S. Sundareswaran, A. Squicciarini, D. Lin, and S. Huang, "Promoting Distributed Accountability in the Cloud," Proc. IEEE Int'l Conf. Cloud Computing, 2011.
[7] Shraddha B. Toney, Sandeep U.Kadam "Cloud Information Accountability Frameworks for Data Sharing in Cloud." 13th May 2012.

Abstract: Computers have become indispensable in all domains, and the medical segment does not represent an exception. The need for accuracy and speed has led to a tight collaboration between machines and human beings.Maybe the future will allow the existence of a world where the human intervention won't be necessary, but for now,the best approach in the medical field is to create semiautomatic applications, in order to help the doctors with the diagnoses, with following the patients' evolution and managing them and with other medical activities. Our application is designed for automatic measurements of orthopedic parameters, and allows the possibility of human intervention in case the parameters have not been detected properly. The segment of the application is Hip Arthroplasty. Keywords: Hip Arthroplasty, Canny Edge Detection, DICOM, Hough Transform, Radiographic Image Processing.

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