iosr-JCE   Volume-9 ~ Issue-1

Abstract:Intermittently connected network often referred to as Delay/Disruption Tolerant Network which is an infrastructure less network suffers from intermittent connection i.e. a connected path from the source to the destination may be absent or a given destination may not be reachable at the moment a message is sent. As a result traditional routing protocols for Ad hoc networks cannot serve the purpose of this type of intermittently connected network. PROPHET routing protocol works on the principle of history of encounters and transitivity. It is called Probabilistic routing prot ocol since it uses a parameter 'Delivery of Predictability'. In this paper the architecture of delay tolerant network is being discussed and PROPHET protocol is implemented.
Keywords: Delay tolerant network, PROPHET routing protocol, Delivery predictability, Epidemic routing protocol

[1] Kevin Fall, ""A delay-tolerant network architecture for challenged internets". Proceedings of ACM SIGCOMM. USA: ACM Press, 2003.
[2] V. Cerf, et al. , Network ""Delay-Tolerant Networking Architecture",April 2007.
[3] Jahnabi Borah," Application of Computational Intelligence Paradigm in the Probabilistic Routing for intermittently connected network," IOSR Journal of Computer Engineering (IOSRJCEVolume 8, Issue 2, PP 32-36, Nov-Dec. 2012.
[4] Lindgren, et al.,""Probabilistic Routing Protocol for Intermittently Connected Networks‟‟,. Internet Research Task Force (IRTF), August 2012.
[5] A. Lindgren, A. Doria, and O. Scheln, "Probabilistic Routing in Intermittently Connected Networks", in Proc. Workshop on Service
Assurance with Partial and Intermittent Resources, August 2004.
[6] Jingfeng Xue, Jiansheng Li, Yuanda Cao, Ji Fang, ""Advanced PROPHET Routing in Delay Tolerant Network" ,International Conference on Communication Software and Networks 2009.
[8] A. Vahdat and B. Becker, "Epidemic Routing for Partially-Connecte Ad- hoc Networks," Technical Report CS-2000-06, Duke
University,July 2000.
[9] T. Spyropoulos, K. Psounis, and C. S. Raghavendra, "Spray and wait: Efficient routing in intermittently connected mobile networks," in Proceedings of ACMSIGCOMM workshop on Delay Tolerant Networking (WDTN), 2005.

Abstract: A Wireless Sensor Network can break into a number of disconnected paths due to failure of some of the nodes known as cut vertices. In this paper, we propose an efficient algorithm to detect vertices. The neighbor node gets failure intimation from the cut vertex so that the information can be passed to source and destination so that the source can initiate data transmission through alternate path before the cut vertices get breakdown completely. In this way, data loss can be minimized and the cut can be detected truly. The algorithm is distributed and asynchronous so that every node needs to communicate with only those nodes that are within their communication range. The most important advantage is that this method can be used to reduce the time delay needed in detecting cut.
Keywords: alternate path, cut vertex, disconnected paths, intimation and detection, wireless network

[1] Shuguang Xiong and Jianzhong Li, " An Efficient Algorithm for Cut Vertex Detection in Wireless Sensor Networks ", in 2010
International Conference on Distributed Computing Systems,pp368-377.
[2] Prabir Barooah, Harshavardha Chenji, Radu Stolera, and Taman Kalmar-Nagy, "Cut Detection in Wireless Sensor Networks", IEEE
Transaction on parallel and distributed system.
[3] X.Liu, L.Xiao, A.Kreling and Y.Liu, "Optimizing Overlay Topology by Reducing Cut Vertices", in ACM Workshop on Network and Operating System support for Digital Audio and Video (NOSSDAV), 2006.
[4] G.Dini, M.Pelagatti, and I.M.Savino, "An algorithm for reconnecting wireless sensor network partitions", in European Conference
on Wireless Sensor Networks, 2008, pp.253-257.
[5] B. Milic and M. Malek, "Adaptation of the Breadth First Search Algorithm for Cut-edge detection in Wireless Multihop Networks", in ACM International Workshop on Modeling Analysis and Simulation of Wireless and Mobile Systems (MSWiM),
[6] T.H.Cormen, C.E. Leiserson, R.LRivest and C.Stein, "Introduction to Algorithms (Second Edition)", The MIT Press, 2002.

Abstract:Top-K dominating query is a preference based query which determines the dominating itemset from the data stream. This query combines the notion of ranking function with the concept of dominance. Datastream mining has more constraints and requirements. It determines valuable information from a great deal of primitive data. This is adequate for static datasets, where updates are rare. As many modern applications adopt dynamic datasets, they need continuous query processing algorithms to revive the query result. The Sliding Window defines the set of active points which are the most recently arrived points. The existing work combines the ADVANCED ALGORITHM, the APPROXIMATE HOEFFDING BOUND ALGORITHM and the APPROXIMATE MINIMUM SCORE ALGORITHM. This combination guarantees accuracy, provides faster processing and best performance. The enhancement work proposes the TOP-K SCRUTINIZING ALGORITHM for finding dominant itemset from datastream by partitioning the Sliding Window into buckets of equal size. This is an Event processing algorithm which includes event scheduling and rescheduling towards avoiding the examination of points for inclusion in the Top-K. Experimental results using real datasets and synthetic datasets show that the proposed method reduces CPU time and memory overhead. Also, it is quite efficient and achieves high accuracy.
Keywords: Data-stream, Itemset, Event Processing Algorithms, Sliding Window, Top-K Dominating Queries.

[1] M. Kontaki, A. N. Papadopoulos and Y. Manolopoulos, Continuous Top-K Dominating Queries, Proc. IEEE Transactions on
Knowledge & Data Engineering, Vol. 24, 2012, 840-853.
[2] Di Yang, Avani Shastri, Elke A. Rundensteiner and Mathew O. Ward, An Optimal Strategy for Monitoring Top-k Queries in
Streaming Windows, Proc. Int'l Conf. Extending Database Technology: Advances in Database Technology, 2011.
[3] Kuen-Fang Jea and Chao-Wei Li, A Sliding-Window Based Adaptive Approximating Method to Discover Recent Frequent Itemsets
from Data Streams, Proc. IMECS, 2010.
[4] A. Vlachou, C. Doulkeridis, Y. Kotidis and K. Nørvag, Reverse Top-k Queries, Proc. IEEE Int'l Conf. Data Engg., 2010.
[5] X. Lian and L. Chen, Top-k Dominating Queries in Uncertain Databases, Proc. 12th Int'l Conf. Extending Database Technology:
Advances in Database Technology, 2009.
[6] M. L. Yiu and N. Mamoulis, Multidimensional Top-k Dominating Queries, Proc. Int'l Conf. Very Large Data Bases, 2009, 1-23.
[7] M. Kontaki, A. N. Papadopoulos, and Y. Manolopoulos, Continuous Top-k Dominating Queries in Subspaces, Proc. Panhellenic
Conf. Informatics, 2008.
[8] M. L. Yiu and N. Mamoulis, Efficient Processing of Top-k Dominating Queries on Multi-Dimensional Data, Proc. Int'l Conf. Very
Large Data Bases, 2007, 483-494.
[9] K. Mouratidis, S. Bakiras, and D. Papadias, Continuous Monitoring of Top-k Queries over Sliding Windows, Proc. ACM SIGMOD
Int'l Conf. Management of Data, 2006, 635-646.

Abstract: As the advent of computer has thrown light to the storage of massive data in small spaces the resources has been reduced broadly. Cloud computing in recent times has become a trend among organization to store data and retrieve it on-the-go around the globe. With this the data storage devices and data retrieval process arise a greater responsibility of security that should be provided to the client. This task provides a challenge to the service providers in terms of security and consistency. As shared systems are prone to be attacked, various counter measures have been proposed by experts to secure the stored data. In this work yet another efficient technique is introduced to the storage and retrieval process. Here the data is being encrypted by the advanced encryption algorithm which is considered to be the most competent in the present security scenario. A symmetric key is generated to the stored file. To further enhance the trust of the service provider the trust certificate of the company is being sent along with the keys to the client. The data is being encrypted by the AES-NI algorithm which is considered to be the most efficient up to date. A hash function is also generated to further enhance the security of the stored file. Also the trust of the service provider is provided to the client by sending the trust certificate of the company along with the keys to the client. All the communication process is taken place using the DH Key Exchange protocol. These techniques are performed to ensure the client that the stored data is being secured, integrated and a total control over the route in which the data is being communicated. In this research work, a new efficient technique is proposed which indicates the effectiveness, flexibility of the storage and retrieval process by a generic framework. This framework fills the gap between the security needs and challenges.
Keywords: Diffie Hellman, Advanced Encryption Standards – New Instructions, Cloud Service Provider, Data Encryption Standards, Message Digest, Message Authentication Code and Cloud Security Alliance group

[1] Yashaswi Singh, Farah Kandal and Weiyi Zhang, "A Secured Cost-Effective Multi-cloud Storage in Cloud Computing," IEEE
INFOCOM 2011 Workshop on Cloud Computing.
[2] SravanKumar.R, "Data integrity proofs in cloud storage," Third International Conference on Communication Systems and Networks
(COMSNETS), pp: 1 – 4, 2011.
[3] Anthony Bisong&Sayed.M.Rahman, "An Overview Of The Security Concerns In Enterprise Cloud Computing," IJNSA, Vol.3,
No.1, Jan 2011.
[4] Bernd Grobauer, Tobias Walloschek and Elmar Stocker, "Understanding Cloud Computing Vulnerabilities," A white paper by
SIEMENS, co-published by The IEEE Computer and Reliability Societies, March/April 2011.
[5] EmanM.Mohammed, Hatem.S.Abdelkader and Sherif El-Etriby, "Enhanced Data Security Model For Cloud Computing,"
INFOS2012, 14-16 May, 2012.
[6] Deyan Chen and Hong Zhao, "Data Secuity and Privacy protection Issues in Cloud Computing," IEEE International Conference of
Computer Science and Electronics Engineering, 2012.
[7] National institute of Science and technology, "the NIST Definition of Cloud Computing," p.7, Retrieved July 24 2011.
[8] Mohamed Al Morsy, John Grundy and Ingo Müller, "An Analysis of The Cloud Computing Security Problem," In Proceedings of
APSEC 2010 Cloud Workshop, Sydney, Australia, 30th Nov 2010.
[9] ChipurupalliSekhar, U. Nanaji, "Secure Cloud By It Auditing," International Journal Of Modern Engineering Research (IJMER)
www.ijmer.com vol.1, Issue.2, pp-332-337 issn: 2249-6645.
[10] David C. Wyld, "The Cloudy Future of Government It: Cloud Computing and the Public Sector Around The World," International
Journal of Web & Semantic Technology (IJWesT), Vol 1, Num 1, January 2010.

Abstract:Quality and cost have close relationship in software development process. That's why quality has to be better and cost must to be lower for a software developer organization. In our paper, we are presenting an approach that will give details analysis how cost can be reduced by detect defection in code using static analysis tool and formal inspection together with. Our proposed method will help software industry to think acutely about cost reduction by defect detection in code.
Keywords- Cost reduction, Code inspection Quality assurance, Static analysis tool, inspection.

[1] Laitenberger, L. Briand, and K. Emam, C.1998. Simulation to Build Inspection Efficiency for development Projects,
[2] Boehm and Basili .2001. Top 10 List of Defect Reduction in Software. IEEE Computer.
[3] Barry Boehm and S. Chulani, " Modeling Software Defect Introduction", University of Southern California .
[4] S. Chulani, 1999. " Software Cost and Quality Models in Bayesian Analysis". PhD thesis. University of Southern California.
[5] W. Mandeville , J. "Costs of quality in software ", International Journal of IEEE.
[6] W. S. Humphrey , " Discipline of Software Engineering, Addison-Wesley".
[7] Fagan, M. E. "Inspections of code and design for error reduction in program development. IBM Systems"
[8] Reasoning Inc. "Automated Software Inspection: A New Approach to Increase Software Quality and Productivity".
[9] O.Laitenberger, T.Beil, and Schwinn, "A case study to inspect a non conventional Inspection for Requirements Specifications".
[10] Boehm Barry W.1987. "Improving Software Productivity", IEEE Computer.
[11] Fagan, Michael E. "Advance of Software Inspections," Software Engineering, IEEE, 1986.
[12] Ge Fan, Fang Fang and Stacy Lacy " Using Formal Inspections in Software Quality Assurance" chapter 3,Web Book , 1999.

Abstract: In this digital world, huge amount information exchange takes place due to enhanced facilities of networking. Therefore it is necessary to secure the information which we transmit. The need for secured communication introduces the concept of "Steganography". Steganography, the word itself indicates that information within information; it is the best technique to hide the secret information by using cover objects. Secret information may be a text, image or an audio file. But as per secret information format there are different steganographic techniques are available. This paper proposes a method of audio steganographic system that provides a unique platform to hide the secret information in audio file though the information is in text, image or in an audio format. So there is no need to go for different techniques of steganography as per information format. Many steganographic methods follow the LSB insertion technique to hide the secret information. But there are many statistical techniques available to determine if a stego object has been subjected to LSB Embedding. The proposed system hides secret information in audio file through random based approach and provides security by using PKE algorithm. This paper focuses on combining the strengths of cryptography and steganography for secured communication.

Keywords – Audio Steganography, PKE algorithm, Random based approach etc.

[1] Manoj .T.H, Vimalanathan P, A Santha Rubia, R Sri Vidya, Secured way of encrypted message transmission using audio file,
IJCTA Vol 3 July-August 2012
[2] Dalal N. Hmood, Khamael A. Khudhiar, Mohammed S. Altaei, A new steganographic method for embedded image in audio file,
International Journal of Computer Science and Security (IJCSS), Volume (6) : Issue (2) : 2012)
[3] Jeddy Nafeesa Begum1, Krishnan Kumar1, Vembu Sumathy, Design and implementation of multilevel access control in
synchronized audio to audio steganography, Journal of Information Security, 2010)
[4] M. Asad, J. Gilani, and A. Khalid, An enhanced least significant bit modification technique for audio steganography, International
Conference on Computer Networks and Information Technology (ICCNIT), IEEE, 2011.
[5] K. Bhowal, A. Pal, G. Tomar, and P. Sarkar, Audio steganography using GA, International Conference on Computational
Intelligence and Communication Networks (CICN), IEEE, 2010.
[6] P. Jayaram, H. Ranganatha, and H. Anupama, Information hiding using audio steganography-a survey, International Journal of
Multimedia and its Applications, 2011.
[7] F. Djebbar, B. Ayad, H. Hassmam, and K. Abed-Meraim, A view on latest audio steganography techniques, International Conference on Innovations in Information Technology (IIT), IEEE, 2011.
[8] M. Nutzinger and J. Wurzer, A novel phase coding technique for steganography in auditive media, Sixth International Conference on
Availability, Reliability and Security (ARES), IEEE, 2011. Proceedings Papers:
[9] K. Gopalan and S. Wenndt, Audio steganography for covert data transmission by imperceptible tone insertion, Proceedings of
Communications Systems and Applications, IEEE, 2004.
[10] Cvejic and T. Seppanen, A wavelet domain lsb insertion algorithm for high capacity audio steganography, Proceedings of 2002
IEEE 10th Digital Signal Processing Workshop, 2002 and the 2nd Signal Processing Education Workshop, IEEE, 2002.

Abstract: The volume of data has been growing tremendously in the past few years and is causing serious problems. The one of the major challenge is how to classify the newly emerging data and what basis. Finding effective methods for developing an ensemble of models has been an active research area of large-scale data mining in recent years. Models learned from data are often subject to some degree of uncertainty, for a variety of reasons. In classification, ensembles of models provide a useful means of averaging out error introduced by individual classifiers, hence increasing the accuracy of classification.

Keywords: Ensemble Learning, Machine Learning, Naïve Bayes Classification, Bagging, data mining, weighted majority vote

[1] www.abeautiful.com
[2] www.ics.uci.edu/~mlearn/ C. Blake and C. Merz. UCI repository of machine
[3] www.ensembleLearning\articles
[4] http://www.cs.ucla.edu.
[5] http://itee.uq.edu.au
[6] Margaret H. Dunham, S. Sridhar Data Mining:Introductory and AdvancedTopics, Pearson Education.
[7] Lectures on Machine Learning by www.coursera.org

Abstract:This paper proposes a new perceptual hashing based approach for Image Retrieval. Information in form of images is increasing at a very fast rate therefore there is need for faster and effective retrieval of specific image from image repositories. Content Based Image Retrieval (CBIR) is considered most efficient to search large image collections. The proposed method uses perceptual hash function which calculates similar hash value for similar images. Finally, using an adequate distance or similarity function to compare two perceptual hash values, it can be decided whether two images are perceptually different or not. Perceptual image hash functions can be used e.g. for the identification, authentication or integrity verification of images. In this paper we also propose a hash algorithm that is robust and secure to non malicious manipulation and sensitive to the malicious tampering.

Keywords - Content based Image Retrieval (CBIR), Perceptual Hash algorithm, Image Retrieval using Perceptual Hashing, Query by Image Content (QBIC).

[1] T. Sumathi, C. Lakshmi Devasena, M. Hemlata, "An Overview of Automated Image Annotation Approaches", International Journal
of Research and Reviews in Information Sciences, Vol. 1, March 2011.
[2] A. Vadivel, A. K. Majumdar, S. Sural, "Characteristics of Weighted Feature Vector In Content-Based Image Retrieval Applications",
Proceedings of Intelligent Sensing and Information Processing, 2004, ICISIP, 2004.
[3] M. Swain, D. Ballard, "Color indexing", International Journal of Computer Vision, 1991.
[4] C.H. Lin, R.T. Chen and Y.K. Chan, "A smart content-based image retrieval system based on color and texture feature", International
Journal of Computer Vision, 1991.
[5] P. S. Hiremath, J. Pujari, "Content Based Image Retrieval based on Color, Texture, Shape features using Image and its complement",
15th International Conference on Advance Computing and Communications. IEEE, 2007.
[6] M.B. Rao, B.P Rao, A. Govardhan, "CTDCIRS: Content based Image Retrieval System based on Dominant Color and Texture
Features", International Journal of Computer Applications, Vol. 18, No.6, pp-0975-8887, 2011.
[7] Manimala Singha, K. Hemchandran, "Performance analysis of Color Spaces Image Retrieval", Assam University Journal of Science
& Technology: Physical Sciences and Technology, Vol. 4, 2011.
[8] Mircea Ionescu, Anea Ralescu, "Fuzzy Hamming Distance in a Content-Based Image Retrieval System", International Journal of
Information Technology and Knowledge Management, IEEE, 2004.

Abstract: During the course of an extensive study of the ecology and systematics of the rotifera from Ahansar lake , 26 species of rotifer belonging to 14 genera, 9 families were recorded for the first time . An analysis of the family wise representation of the recorded species depicted the relative qualitative sequence to be Brachionidae > Trichocercidae = Lecanidae . Brachionidae comprised 65% of the overall species richness . Shannon,s diversity index showed highest species richness at macrophyte infested littoral zone and maximum diversity was recorded in Summer .

Key Words: Rotifers , Species richness , Littoral zone

1] APHA ; 1998 . Standard methods for examination of water and Waste water. American public health association 20th Ed , APHA
,New York
[2] De Azevedo ,F and C.C , Bonecker .2003 . Community size structure of zooplanktonic assemblages in three lakes on the upper
River Parans flood plain , PP – MS , Brazil . Hydrobiologia ,505 : 147 – 158 .
[3] Dodson , S . I ; 1992 . Predicting zooplankton species richness .Limnol . Oceanogr .37 , 848 – 856
[4] Edmondson ,W . T ; 1959 .Fresh water Biology ( Ed : W . T . Edmond ) . 2nd Edn , John Willey and sons , Inc ; New York .
[5] Hakenson , L . Boulin , v. v and Ostapenia , A ; 2003 . The influence of biomanipulation ( fish removal ) on the structure of lake
and web , case studies .
[6] Jacek Lawniczak ; Kasper Swidnicki , Malgorzata Wisniewska ,Adam Bodziocl ,Natalia Kuczynskan Kippen Scientific society of
naturalists : Hydrobiology section ,Faculty of Biology , Adam Mickiewicz University , Umultowska 89 , 61 -614 , Poznam ,Poland
[7] Nogueira .M .G ; 2001 . zooplankton composition , dominance and abundance as indicator of environmental compartmentalization
in Jurumirim reservoir ( Parana Panema River ) , Sao Paulo , Brazil , Hydrobiologia 455 : 1 – 18 .l
[8] Pejler . B ; 1995 .Relation to habitats in rotifers . Hydrobiologia 313 -314 : 267 278 .
[9] Pejler . B and Berzins .B; 1993a. On the ecology of Trichocercidae (Rotifera ). Hydrobiologia 263 :55 -99 . Preference Of Rotifera In Ahansar Lake
[10] Pennak, R. W; 1966. Structure of zooplankton population in littoral macrophytes zone of some Colorado lakes. Trans. Am. microsc . Sic. 85. 329 – 349.

Abstract:Secure multi party computation allows several parties to compute some function of their inputs without disclosing the actual input to one another. Secure sum computation is an easily understood example and the component of the various secure multi party computation solutions. Secure sum computation allows parties to compute the sum of their individual inputs without disclosing the inputs to one another. In this paper, we propose a protocol with more security, when a group of the computing parties want to know the data of some other party.

Keywords: Distributed Database Partition, Multi Party Computation, Privacy Preserving, Secure Sum Protocol.

1] A.C.Yao, "protocol for secure computations," in proceedings of the 23rd annual IEEE symposium on foundation of computer
science, 1987, pp. 160-164.
[2] C. Clifton, M. Kantarcioglu, J.Vaidya, X. Lin, and M. Y. Zhu, "Tools for Privacy-Preserving Distributed Data Mining," J.SIGKDD
Explorations, Newsletter, vol.4, no.2, ACM Press, 2002, pp.28-34.
[3] R. Sheikh, B. Kumar and D. K. Mishra, "Changing Neighbors k- Secure Sum Protocol for Secure Multi-party Computation,"
Accepted for publication in the International Journal of Computer Science and Information Security, USA, Vol.7 No.1, 2010, pp.
239-243.
[4] R. Sheikh, B. Kumar and D. K. Mishra, "Privacy-Preserving k- Secure Sum Protocol," in the International Journal of Computer
Science and Information Security, USA, Vol. 6 No.2, 2009, pp. 184-188.
[5] R. Sheikh, B. Kumar and D. K. Mishra, "A Distributed k-Secure Sum Protocol for Secure Multi-party Computation," submitted to a
journal, 2009.
[6] O. Goldreich, S. Micali, and A. Wigderson, "How to play any mental game," in STOC '87: Proceedings of the nineteenth annual
ACM conference on Theory of computing, New York, NY, US : ACM, 1987, pp. 218-229.
[7] B.Chor and N.Gilbao. "Computationally Private Information Retrieval (Extended Abstract)," In proceedings of 29th annual ACM
Symposium on Theory of Computing, El Paso, TX USA, May 1997.
[8] B. Chor, E. Kushilevitz, O. Goldreich,and M. Sudan, "Private Information Retrieval ," In proceedings of the 36th Annual IEEE
Symposium on Foundations of Computer Science, Milwaukee WI, 1995,pp. 41-50.
[9] Y. Lindell and b. Pinkas, "Privacy preserving data mining," in advances in cryptography-Crypto2000, lecture notes in computer
science, Vol. 1880.
[10] R. Agrawal and R. Srikant. "Privacy-Preserving Data Mining," In proceedings of the 2000 ACM SIGMOD on management of data,
Dallas, TX USA, 2000, pp. 439-450.

Abstract: A mobile ad hoc network consists of individual mobile nodes communicating via wireless link. The node which refuses to share their own resources but gets benefit from other nodes, are called selfish or misbehaving nodes. The nodes in MANET are mobile with changing topologies. Performance of network may get affected due to these selfish nodes like scarcely available battery-based energy and node misbehaviors may exist. The 2ACK scheme is used to detect the misbehaving link. In this paper, improved 2ACK scheme detects misbehaving node. It sends two-hop acknowledgment packets in the opposite direction of the routing path. Improved 2ACK scheme reduces additional routing overhead by minimizing acknowledgment of the received data packets. It uses the Dynamic Source Routing (DSR) protocol. The proposed improved 2ACK scheme tries to reduce the overhead of Acknowledgments caused by 2ACK scheme.

Keywords - Dynamic source routing, Mobile Ad Hoc Networks (MANET), network security, Node misbehavior, routing misbehavior

[1] K. Liu, J. Deng, P. K. Varshney, and K. Balakrishnan, "An Acknowledgment-based Approach for the Detection of Routing
Misbehavior in MANETs," IEEE Transactions on Mobile Computing, vol. 6, no. 5, pp. 536-550, May 2007.Tavel, P. 2007 Modeling
and Simulation Design. AK Peters Ltd.
[2] Sunilkumar , S. Manvia, Lokesh B. Bhajantrib, and Vittalkumar K. Vaggac, "Routing Misbehavior Detection in MANETs Using
2ACK", journal of telecommunication and information technology 4/2010
[3] David B., Johnson David, A. Maltz, Josh Broch, "DSR: The Dynamic Source Routing Protocol for Multi-Hop Wireless Ad Hoc
Networks", Computer Science Department Carnegie Mellon University Pittsburgh, PA 15213-3891, http://www.monarch.cs.cmu.edu/
[4] S. Marti, T. Giuli, K. Lai, and M. Baker, "Mitigating Routing Misbehavior in Mobile Ad Hoc Networks",‖ Proc. MobiCom, Aug.
2000.
[5] G. F. Marias1, Y, P. Georgiadis1, D. Flitzanis2 and K. Mandalas2," Cooperation enforcement schemes for MANETs: A survey",
WIRELESS COMMUNICATIONS AND MOBILE COMPUTING,Wireless Communication. Mob. Computing. 2006; 6:319–332,
Published online in Wiley Inter Science.
[6] Chinmay K. Nayak 1, G K Abani kumar2, Parida3, Das4, "Detection of Routing misbehavior in MANET with 2ACK scheme ,Vol. 2, No. 1, Jan 2011
[7] R.Balakrishna1, M. Muralimohan Reddy2, U. Rajeswar Rao3, G.A.Ramachandra4, "Detection of Routing Misbehavior in MANET", using 2ACK ",IEEE International Advance Computing Conference (IACC 2009), Patiala, India, 6–7 March 2009
[8] Sheng Zhong , Jiang Chen , Yang Richard Yang , "Sprite: A Simple, Cheat-Proof, Credit-Based System for Mobile Ad-Hoc
Networks" 2003 IEEE
[9] Marco Conti, Enrico Gregori, and Gaia Maselli, "Towards Reliable Forwarding for Ad Hoc Networks", IST-2001-38113
MOBILEMAN project
[10] Kashyap Balakrishnan, Jing Deng, Pramod K. Varshney,"TWOACK: Preventing Selfishness in Mobile AdHoc Networks", IEEE
2005

Abstract: (11Bold) : Session Initiation Protocol (SIP) is most extensively usable VoIP protocol which works on application layer. It uses Transmission Control Protocol or User Datagram Protocol which further uses Internetworking Protocol for establishing VoIP communication. None of these protocols including SIP provides absolute location information which provides caller's location in latitude and longitude. Location tracking is an essential feature which must be incorporated to enhance the security and to provide emergency call services. This paper presents basic understanding of SIP and its messages. It also describes few of the generic solutions for location tracking of VoIP and issues related to those solutions.

Keywords (11Bold) - VoIP, VoIP caller tracking, Session Initiation Protocol, VoIP caller identification

[1] Rakesh Arora,1999, VoIP protocols[online]. Available: http://www.cis.ohio state.edu/~jain/cis788-99/voip_protocols/index.html
[2] Hsien-Ming Hsu a, Yeali S. Sun a, Meng Chang Chen, Collaborative scheme for VoIP trace back, Science Direct, 2011
[3] Ram D, Sonia F, Henning S, Joao C, Issue and challenges in securing VoIP , Science Direct, 2009
[4] Zourzouvillys, T.; Rescorla, E., An Introduction to Standards-Based VoIP: SIP, RTP, and Friends, 2010,IEEE international
conference, Page(s): 69 - 73
[5] Ashtarifar, S.; Matrawy, A, Determining Host Location on the Internet: The Case of VoIP Emergency Calls, Communications
Workshops, 2009. ICC Workshops 2009. IEEE International Conference, , Page(s) 1-5,2009.
[6] Rakesh Arora,1999, VoIP protocols[online]. Available: http://www.cis.ohio state.edu/~jain/cis788-99/voip_protocols/index.html
[7] J. Rosenberg,H. Schulzrinne,G. Camarillo,A. Johnston, J. Peterson,R. Sparks, (June 2002)SIP: Session Initiation Protocol[Online].
Available: http://www.ietf.org/rfc/rfc3261.txt
[8] Jose c, Haitao T, Enhancing SIP with Spatial Location for Emergency Call Services, 2002, IEEE international conference, Page(s):
326 – 333
[9] V. Padamanabban and L. Subramanian, Determining the geographic location of Internet hosts, ACM SIGMETRICS Performance
Evaluation Review, vol. 29, no. 1, pp. 324–325, 2001
[10] David S. Benco, Sanjeev Mahajan, Baoling S. Sheen, Sandra Lynn True, 2008, Methods and apparatus for improved 911 support for VoIP service , US patent US0242660 A1

Abstract: Pharming is an advance phishing attack. It is also known as "phishing without a lure". A hacker's attempt to change/exploit the DNS settings of a server so that when you enter the address of a legitimate website, it redirects you to a fake/copy of the original site hosted somewhere else. It is a classy edition of phishing attacks – endeavor to take users' identification like username and password by redirecting them to a fake website using DNS-based techniques.

Keywords: Pharming, advance phishing, prevention against Pharming attack, detecting Pharming attack

[1] S. Stamm, Z. Ramzan, et Jakobsson Markus, Drive-By Pharming, Proceedings of the 9th international conference on Information
and communications security, Zhengzhou, China: ACM, 2007, p. 495-506.
[2] G.Ollman,Jul.2005,The Pharming Guide[online]; Avalibale: http:// www. Ngssoftware. com / papers/ ThePharmingGuide.pdf.
[3] Microsoft Corporation, 2013, Domain Name System [online] ; Available :http://technet.microsoft.com/enus/
network/bb629410.aspx
[4] C. Jackson, A. Barth, A. Botz, W. Shao, et D. Boneh, Protecting browsers from DNS rebinding attacks, ACM, vol. 3, Issue 1,
Jan.2009.
[5] C. Karlof, U. Shankar, J. Tygar, et D. Wagner, Dynamic pharming attacks and locked same-origin policies for web browsers,
Proceedings of the 14th ACM conference on Computer and communications security, Alexandria, Viriginia, USA: ACM, 2007, p.
58-71.
[6] Y. Cao, W. Han, et Y. Le, Anti-phishing Based on Automated Individual White-List, Proceedings of the 4th ACM workshop on
Digital identity management, Alexandria, Viriginia, USA: ACM, 2008, p. 51-60.
[7] A.P.E. Rosiello, E. Kirda, C. Kruegel, et F. Ferrandi, A layoutsimilarity- based approach for detecting phishing pages, Nice, France:
IEEE, 2007, p. 454-463.
[8] Gastellier-Prevost, S.; Granadillo, G.G.; Laurent, M., A dual approach to detect pharming attacks at the client-side, IEEE 2011, p.1-
5.
[9] Chih Sheng Chen, Shr-An-Su,Yi-Chan Hung,Jun. 7,2011, Protecting computer users from online fraud, US patent number
US7,85,555 B1
[10] Chao-Yu Chen,Tse-Min Chen,Aug.14,2012,Autonomous system based Phishing and Pharming Detection,US patent number US
8,245,304 B1

Abstract: The stochastic optimization techniques were commonly used in solving several optimization problems. There are different types of these algorithms that were addressed in several previous works. In our previous work, we implemented a GA and PSO based stochastic optimization model for solving the job shop scheduling problem (JSSP). The impacts of these two kinds of initial condition on the performance of these two algorithms were studied using the convergence curve and the achieved makespan. In this work we will implement a simulated annealing (SA) based model for solving JSSP. We will compare the performance of SA based method with the two other methods which we presented in our earlier works.

Keywords: Jop Shop Scheduling, JSSP, GA, PSO, Gant-Chart, Simulated Annealing.

[1] Moraglio , H.M.M. Ten Eikelder, R. Tadei, "Genetic Local Search for Job Shop Scheduling Problem" , Technical Report, CSM-435
ISSN 1744-8050
[2] E.L. Lawler, J.K. Lenstra, A.H.G. Rinnooy Kan, D.B. Shmoys. - Sequencing and scheduling: Algorithms and complexity. - In:
S.C. Graves, A.H.G. Rinnoy Kan and P. Zipkin, editors, Handbooks in Operations Research and Management Science 4, North-
Holland, 1993.
[3] Dr. Daniel Tauritz, The abstract of the talk "Grand Challenges in Evolutionary Computing - Part II", Missouri S&T
[4] Hongbo Liu, Ajith Abraham,Zuwen Wang, "A Multi-swarm Approach to Multi-objective Flexible Job-shop Scheduling Problems", School
of Information Science and Technology, Dalian Maritime University, Dalian 116026, China, Fundamenta Informaticae,IOS Press, 2009
[5] José Fernando Gonçalves, Jorge José de Magalhães Mendes,Maurício G. C. Resende, "A Hybrid Genetic Algorithm for the Job Shop
Scheduling Problem", AT&T Labs Research Technical Report TD-5EAL6J, September 2002.
[6] Mahanim Binti Omar, "A Modified Multi-Step Crossover Fusion (Msxf) In Solving Some Deterministic Job Shop Scheduling Problem
(Jssp), A thesis work submitted to Universiti Sains Malaysia, 2008
[7] Xiangyang Wang, Jie Yang, Richard Jensenb Xiaojun Liu, , "Rough Set Feature Selection and Rule Induction for Prediction of
Malignancy Degree in Brain Glioma ",Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University, Shanghai,
China and Department of Computer Science, The University of Wales, Aberystwyth, UK
[8] Y. Shi, R. C. Eberhart, Parameter selection in particle swarm optimization, in Evolutionary Programming VII: Proc. EP98, pp. 591-600
(New York: Springer-Verlag, 1998).
[9] Takeshi Yamada and Ryohei Nakano, "Genetic Algorithms for Job-Shop Scheduling Problems", NTT Communication Science Labs,
JAPAN, Proceedings of Modern Heuristic for Decision Support, pp.67, UNICOM seminar, March 1997, London
[10] S. Jayasankari, Dr. A. Tamilarasi "Evaluation on GA based Model for Solving JSSP", International Journal of Computer Applications
Volume 43 - Number 7, Year of Publication: 2012, 10.5120/6113-8248.