Volume-6 , Issue-7 , Jul - 2018 Go Back

To enhance and strengthen the security features of computer`s information. As for as term Computer security is concern; it is the process of collecting information about unauthorized access. Detection is a recognition process which helps us to determine if someone tried to enter the target system successfully or not. Although there are so many methodologies has been also developed to make secure the secret and private information but still there is occurrence of unauthorized access of information takes place and violate the existing meaning, features and functionalities. Such unauthorized users are called as Intruders. These are also called as attackers or crackers. An attacker may not care about our identity and their action effects often try to take control of the computer to launch attacks on the computer systems secretly. In this research work it is focused to develop such a strong intrusion detection system which can silently and efficiently capture the intrusions penetrating in individual host systems or any host of the network system dynamically. This is “A Real Time Approach to Strengthen Computer Security by Host cum Network Agent Based Intrusion Detection System (HCN-AIDS)”which will enhance efficiency as compared to earlier agent based intrusion detection system. It includes powerful agents equipped with strong unique functionalities like Network Agent, Mobile Agent, Intrusion Detection Agent, Rule agent etc. this research model is again becomes more important and useful because works in hybrid mode i.e. in real time data as well host based systems and generates efficient results.

Attacks, Crackers, Information, Detection, feature, Host, Intruder, Intrusion, Mobile Agent, Network Agent, security etc.

[1] A.M. Riyad, M.S. Irfan Ahmed and R.L. Raheemaa Khan “Multi agent based intrusion detection architecture for the IDS adaptation over time”, Second International Conference on Electrical, Computer and Communication Technologies (ICECCT),IEEE,2017
[2] Mohiyeddin Mozaffari and Behrouz Safarinejadian,”Mobile-agent-based distributed variational Bayesian algorithm for density estimation in sensor networks” IET Science, Measurement & Technology Volume: 11, 2017
[3] Chaimae Saadi ,Ensak-Morroco and Habiba Chaoui “Intrusion detection system based interaction on mobile agents and clust-density algorithm “IDS-AM-Clust”, International Colloquium on Information Science and Technology (CiSt),IEEE,2016
[4] Sara Chadli,Mohamed Emharraf and Mohammed Saber "The design of an IDS architecture for MANET based on multi-agent" International Colloquium on Information Science and Technology (CiSt),IEEE,2014
[5] Okan Can "Mobile agent based intrusion detection system”, 22nd Signal Processing and Communications Applications Conference (SIU), 2014
[6]Wang Yu, Cheng, Xiaohui and Wang Sheng ,“Anomaly Network Detection Model Based on Mobile Agent”, IEEE,Third International Conference on Measuring Technology and Mechatronics Automation, 2011
[7] Ionita, I.; Ionita, L. “An agent-based approach for building an intrusion detection system” Published in Networking in Education and Research, 2013 RoEduNet International Conference 12th Edition, 2013
[8] Jitendra S Rathore, Praneet Saurabh, Bhupendra Verma “AgentOuro: A Novelty Based Intrusion Detection and Prevention System” Computational Intelligence and Communication Networks (CICN), 2012 Fourth International Conference on 3-5 Nov. 2012
[9] Vasima Khan, Anomaly Based Intrusion Detection And Prevention System, IJERT, 2013
[10] Mukesh Sharma,Akhil Kaushik, Amit Sangwan Performance Analysis of Real Time Intrusion Detection and Prevention System using Snort.,IJERT, 2012
[11] Vaishali T.Deshmukh, Shubhangi Vaikole, Layered Crf A Model To Build More Accurate Intrusion Detection System, IJERT, 2012
[12] Bhavana G.Rathwa,Prof.Purnima Singh Genetic Algorithm Methodology for Intrusion Detection System, IJERT, 2012
[13] Bin Zeng , Lu Yao and ZhiChen Chen"A network intrusion detection system with the snooping agents",International Conference on Computer Application and System Modeling, 2010
[14] Cheung-Leung Lui , Tak-Chung Fu and Ting-Yee Cheung "Agent-based network intrusion detection system using data mining approaches”, Third International Conference on Information Technology and Applications (ICITA`05), 2005
[15] Qiang Xue , Lin-Lin Guo and Ji-Zhou Sun"The design of a distributed network intrusion detection system IA-NIDS", Proceedings of the 2003 International Conference on Machine Learning and Cybernetics, 2003
[16] Xiao-Yuan Yang , Xuan-Wu Zhou , Ping Wei and Li-Xian Wei"Hybrid NIDS based on biological immunology", Proceedings of 2004 International Conference on Machine Learning and Cybernetics, 2004
[17] Faizal, M.A., Mohd Zaki M., Shahrin Sahib, Robiah, Y., Siti Rahayu, S., and Asrul Hadi, Y. “Time Based Intrusion Detection on Fast Attack for Network Intrusion Detection System”, Second International Conference on Network Applications, Protocols and Services, IEEE, 2010

S. K. Tiwari, D. S. Pandey, V. Namdeo, "A Real Time Approach to Strengthen Computer Security By Host Cum Network Agent Based Intrusion Detection System (HCN-AIDS)," International Journal of Computer Sciences and Engineering, Vol.6, Issue.7, pp.204-210, 2018.

With the inventions and improvement in the technology, billions of devices continuously produce or generate data. On this basis, we have designed the technique, through which data was extracted or collected from different sources. The data from the respective source was standardized and utilized to respective situations to act upon. The proposed system uses Hyper Text Transfer Protocol (HTTP) and Message Queue Telemetry Transport (MQTT) as base protocols for communication across network. The performance of both the protocols were compared for respective action and situation across varied load conditions. Thus, based on the output, the protocol would selected for different cases.

HTTP, INTERNET OF THINGS (IOT), MQTT

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[4] Umer Ahsen,Abdul bais ,A Review on Big Data analysis and the Internet of Things,IEEE ,13th International conference on Mobile Ad Hoc and sensor Systems(MASS) ,pp 325-330,2016
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Isroset-Journal (IJSRCSE),Vol.5, Issue.3, pp.62-67,Jun-2017

[8] D. Bhattacharya, and M. Mitra, Analytics on Big Fast Data Using Real Time Stream Data Processing Architecture. EMC Proven Professional Knowledge Sharing, 2013.
[9] S.K. Dash, J.P. Sahoo, S. Mohapatra, and S.P. Pati, Sensor-Cloud: Assimilation of Wireless Sensor Network and the Cloud. In: Meghanathan, N., Chaki, N. and Nagamalai, D., Eds., Advances in Computer Science and Information Technology. Networks and Communications, S pringer, Berlin, 2012, 455-464. http://dx.doi.org/10.1007/978-3-642-27299-8_48
[10] A. Alamri, W.S. Ansari, M.M. Hassan, M.S. Hossain, A. Alelaiwi, and M.A. Hossain,) A Survey on Sensor-Cloud: Architecture, Applications, and Approaches. International Journal of Distributed Sensor Networks, 9, 2013, Article ID: 917923. http://dx.doi.org/10.1155/2013/917923
[11] A.S. Rozik, M.A. Tolba, El-Dosuky, Design and Implementation of the Sense Egypt Platform for Real-time Analysis of IOT Data Streams.Advances in Internet of Things,2016,6,65-91. http://www.scrip.org/journal/ait
[12] D. Bhattacharya, and M. Mitra, Analytics on Big Fast Data Using Real Time Stream Data Processing Architecture. EMC Proven Professional Knowledge Sharing, 2013.
[13] D.L. Hall, and J. Llinas, An Introduction to Multisensor Data Fusion. Proceedings of the IEEE, 85, 1997, 6-23. http://dx.doi.org/10.1109/5.554205
[14] F. Ganz, P. Barnaghi, and F. Carrez, Information Abstraction for Heterogeneous Real World Internet Data. IEEE Sensors Journal, 13, 2013, 3793-3805. http://dx.doi.org/10.1109/JSEN.2013.2271562
[15] M. Eid, R. Liscano, and A. El Saddik, (A Universal Ontology for Sensor Networks Data. IEEE International Conference on Computational Intelligence for Measurement Systems and Applications, Ostuni,27-29 June 2007, 59-62. http://dx.doi.org/10.1109/cimsa.2007.4362539
[16]P.Manickam,V.MuthuGaneshan,M.Girija ,Comprehenssive approach in Studying the behaviour of Contiki RPL Protocol in Diverse Data Transmission Ranges,International Journal on Scientific Research in Network Security and Communication.

Sumanashree Y. S, Suresha, "Protocol Analysis in Internet of Things for deployment strategies," International Journal of Computer Sciences and Engineering, Vol.6, Issue.7, pp.211-217, 2018.

Testing is necessary because we all make mistakes. Additionally, we are more likely to make errors when dealing with perplexing technical or business problems, complex business processes, code or infrastructure, changing technologies, or many system interactions. This is because our brains can only deal with a reasonable amount of complexity or change when asked to deal with more our brains may not process the information we have correctly. Some of these errors are not important, but some of them can be expensive and damaging, with loss of money, time or corporate reputation and may even cause injury or death. A key element to conduct successful software testing, are various testing tools. In addition to tool support for regressive testing, selection of appropriate tool also becomes equally important depending upon the cost involved in terms of skillset required and maintenance of test scripts.

Test Automation, Selenium IDE, Selenium Webdriver, Mutation Rate, Error Rate

[1] R. Chauhan, I. Singh, "Latest Research and Development on Software Testing Techniques and Tools", INPRESSCO International Journal of Current Engineering and Technology, 2014.
[2] S. P, D. N, "Automation of Software Testing in Agile Development - An Approach and Challenges with Distributed Database Systems", GJRA - GLOBAL JOURNAL FOR RESEARCH ANALYSIS, Vol. 3, pp.1-7, 2014.
[3] N. Bhateja, "A Study on Various Software Automation Testing Tools", International Journal of Advanced Research in Computer Science and Software Engineering, Vol. 5, pp.1-6, 2015.
[4]. S. Sharma, "Study And Analysis Of Automation Testing Techniques", Journal of Global Research in Computer Science, Vol. 3, pp.1-12, 2012.
[5] "Analysis of Automation and Manual Testing Using Software Testing Tool", IJIACS, Vol. 4, 2017, ISSN ISSN 2347 − 8616.
[6] S. Thummalapenta, S. Sinha, N. Singhania, "Automating Test Automation", IBM T. J. Watson Research Center IBM Research-India, Vol. 2017.
[7] “An Approach of Software Design Testing Based on UML Diagrams", International Journal of Advanced Research in Computer Science and Software Engineering, Vol. 4, pp.1-2, 2014.
[8] "A Unique Technique to Handle the Complexity and Improve the Effectiveness of Test Cases in Software Testing", Journal of Innovative Technology and Education, Vol. 2, 2015.
[9] M. Dande and N. Galla, "Automation Testing Frameworks for SharePoint application", International Journal of Computer Sciences and Engineering, Vol.3, Issue.11, pp.33-38, 2015.
[10] R. Sharma, R. Dadhich, "Implications of Software Testing Strategies at Initial Level of CMMI: An Analysis", International Journal of Computer Sciences and Engineering, Vol.6, Issue.5, pp.1055-1061, 2018.
[11] N. Kaur, J. Kaur, J. S. Budwal, "Application of ACO in Model Based Software Testing: A Review", International Journal of Computer Sciences and Engineering, Vol.6, Issue.3, pp.370-374, 2018.
[12] B. Saha, D. Mukherjee, "Analysis of Applications of Object Orientation to Software Engineering, Data Warehousing and [13] Teaching Methodologies", International Journal of Computer Sciences and Engineering, Vol.5, Issue.9, pp.244-248, 2017.
[14] N. Sudheer, V. Sarma, N. Ahmad, "Implementing Different Types and Variants for Software Testing Process and Techniques", International Journal of Computer Sciences and Engineering, Vol.5, Issue.4, pp.34-39, 2017.
[15] A. Verma, A. Khatana, S. Chaudhary, "A Comparative Study of Black Box Testing and White Box Testing", International Journal of Computer Sciences and Engineering, Vol.5, Issue.12, pp.301-304, 2017.
[16] N. Sudheer, S.H. Raju, "Different approach Analysis for Static Code in Software Development", International Journal of Computer Sciences and Engineering, Vol.4, Issue.9, pp.111-118, 2016.
[17] R. K. Sahoo, D. P. Mohapatra, M. R. Patra, "A Firefly Algorithm Based Approach for Automated Generation and Optimization of Test Cases", International Journal of Computer Sciences and Engineering, Vol.4, Issue.8, pp.54-58, 2016.
[18] N. Sudheer, V. Sharma and S. H. Raju, "A Process Web Application Testing Using TAO Tool Search Based Genetic Algorithm", International Journal of Computer Sciences and Engineering, Vol.4, Issue.7, pp.94-100, 2016.
[19] S. Kannan, T. Pushparaj, "A study on variations of Bottlenecks in Software Testing", International Journal of Computer Sciences and Engineering, Vol.2, Issue.5, pp.8-14, 2014.
[20] S. Bharti and S. N. Singh, "Improvised Agile SCRUM Using Test-Asa-Service", International Journal of Computer Sciences and Engineering, Vol.3, Issue.3, pp.166-171, 2015.

Shilpa Garg, Paramjeet Singh, Shaveta Rani, "Comparative Study of Selenium WebDriver and Selenium IDE (Integrated Development Environment)," International Journal of Computer Sciences and Engineering, Vol.6, Issue.7, pp.218-222, 2018.

The huge challenge in discovering relevance feature is to determine the quality of user searched documents. The user wants relevant features to search the text, document, image, etc. approximately. The techniques earlier used where term based and pattern based. Now days clustering methods like partition based, density based and hierarchical is used along with different feature selection method. The term-based approach is extracting terms from the training set for describing relevant features. Partitioned text mining solves the low-level support problem, but it suffers from a large number of noise patterns. Information content in documents is identified by frequent sequential patterns and sequential patterns in the text documents and the useful features for text mining are extracted from this. Extracted terms are classified into three type’s positive terms, general terms and negative terms. In order to deploy advanced features on low-level features, this article finds positive and negative patterns in text documents.

Text mining, text feature extraction, text classification

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[10] S. Purandare, “Relevance Feature Discovery In Text Documents”, International Journal of Computer Engineering, Vol.3, Issue.6, pp.98-101, 2016.
[11] Sujamol.S, Ariya T K Identifying and Analyzing Efficient Pattern Discovering Techniques for Text Mining ”, International Journal of Research in Computer and Communication Technology pp.102-105, 2014.
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R. R. Kamble, D. V. Kodavade, "Relevance Feature Search for Text Mining using FClustering Algorithm," International Journal of Computer Sciences and Engineering, Vol.6, Issue.7, pp.223-227, 2018.

Data communication performance of Mobile Ad-hoc Networks (MANETs) gets adversely affected by presence of malicious nodes. In this paper, model for random On/Off switching, referred as selfish or malicious nodes has been used, with OLSR protocol and a simple trust strategy has been proposed to decide the trust of next hop node. Residual energy level of forwarding node is also continuously monitored and accordingly confidence level associated with the node has been determined. Continuously varying trust parameter and confidence levels of all forwarding nodes have been incorporated in the Hello and Topology Control (TC) message formats of standard OLSR protocol. Further, OLSR protocol has been modified using Trust and Confidence values of nodes. The proposed protocol, termed as OLSRT-C, has been used to select the optimum path for data forwarding. Simulations carried out on typical MANET scenario show that the proposed OLSRT-C protocol successfully mitigates randomized Selfish Behavior (SB) attack significantly with marginal increase in the Average Energy Consumption per node.

MANETs, Selfish Behavior attack, OLSR, Trust-Confidence routing, PDR, Routing Overheads, Average Energy Consumption

[1] T. Clausen, P. Jacquet: “Optimized Link State Routing Protocol OLSR”, IETF RFC-3626, 2003
[2] J. Wang, Y. Liu, Y. Jiao: “Building a trusted route in a mobile ad hoc network considering Communication reliability and path length”, Journal of Network and Computer Applications, 34(2011), pp. 1138-1149, 2011
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[6] A. Rajaram, S. Palaniswami: “Malicious Node Detection System for Mobile Ad hoc Networks”, (IJCSIT) International Journal of Computer Science and Information Technologies, Vol.1, No.(2) , pp. 77-85, 2010
[7] K. A. Adoni, A. S. Tavildar: “Probabilistic Modelling and Estimation of Network Blocking Probability for Selfish Behavior Attack in Mobile Ad hoc Networks”, IJCSN International Journal of Computer Science and Network,Vol.5, No.(4), pp. 653-659, August 2016
[8] K. A. Adoni, M. S. Karyakarte, A. S. Tavildar.: “Security Framework for Black Hole Attack in Mobile Ad-hoc Networks”, ICEIT National Conference on ‘Advances in Mobile Communications, Networking and Computing’, New Delhi, India, April 16-17, 2015, pp. 84-87, 2015
[9] Surya Aarohi: “Modelling of Malicious Behavior due to Detour Attack in OLSR Protocol in MANET”, Recent Researches in Electrical Engineering, pp. 276-283, 2014
[10] N. Suganthi, S. Neelavathy Pari,: “Detecting Malicious Nodes in MANET using Rateless Codes for maximum content ", 2014 Sixth International Conference on Advanced Computing (ICoAC), Chennai, India, 17-19 December 2014, pp. 308-311, 2014
[11] Khaled Ahmed Abood Omer: “The Impact of Node Misbehavior on the performance of Routing Protocols in MANET”, International Journal of Computer Networks and Communications (IJCNC), Vol. 8, No.2, March 2016, pp. 103-112, 2016
[12] Umesh Kumar Singh, Jalaj Patidar and Kailash Chandra Phuleriya: “On Mechanism to Prevent Cooperative Black Hole Attack in Mobile Ad Hoc Networks”, International Journal of Scientific Research in Computer Science & Engineering, Volume 3, Issue 1, pp. 11-15, 2015.
[13] A.Vani: “Detection and Elimination of Wormhole Attacks in a MANET”, International Journal of Scientific Research in Computer Science & Engineering, Vol.5, Issue 5, pp-35-40, October (2017)
[14] Pradeep Kumar Sharma, Shivlal Mewada and Pratiksha Nigam: “Investigation Based Performance of Black anf Gray Hole Attack in Mobile Ad-Hoc Network”, International Journal of Scientific Research in Network Security and Communications, Volume-1, Issue-4, Oct. 2013
[15] S. Geetha, G. Geetha Ramani: “Trust Model based on Bayesian Statistical method for AOMDV in MANET”, Journal of Theoretical and Applied Information Technology, Vol. 69, No. 1, November 2014, pp. 172-181, 2014
[16] Zia Ullah, Muhammad Saleem Khan, Idrees Ahmed, Nadeem Javaid, Majid I. Khan,: “Fuzzy Based Trust Model for Detection of Selfish Nodes in MANET”, International Conference on Advanced Information Networking and Application, Crans Montana, Switzerland, 23-25 March 2016, pp. 965-972, 2016
[17] Janakiraman Sengathir and Rajendiran Manoharan: “A futuristic trust coefficient-based semi-Markov prediction model for mitigating selfish nodes in MANETs”, EURASIP Journal on Wireless Communications and Networking (2015) 2015:158, pp. 1-13, 2015
[18] Hui Xia, Zhiping Jia, Xin Li, Lei Ju, Edwin H.M. Sha: “Trust Prediction and trust based source routing in mobile ad hoc networks”, Ad Hoc Networks, 11(2013) pp. 2096-2114, 2013
[19] L. Odedra, A. Revar, M. H. Lunagaria: “Detection and Prevention of Selfish Attack in MANET using Dynamic Learning”, IOSR Journal of Computer Engineering (IOSR-JCE), Ver. V, May-Jun. 2016, Vol.18, No.(3), pp. 54-61, 2016
[20] M. Roy, C. Chowdhury, S. Neogy: “Developing Secured MANET using Trust”, Fourth ICACC International Conference on Advances in Computing and Communication, Cochin, India, 2014, pp. 183-186, 2014
[21] W. Gong, Z. You, D. Chen, et al.: “Trust Based Malicious Nodes Detection in MANET”, International Conference on E-business and Information Security, EBISS-2009, Wuhan, China, 2009
[22] G. Soni, K. Chandrawanshi: “A Novel Defence Scheme against Selfish Node Attack in MANET”, International Journal on Computational Sciences and Applications (IJCSA), June 2013, Vol.3, No.(3), pp. 51-63, 2013
[23] N. Kirubakaran, A. Kathirval: “Performance Improvement of Security Attacks in Wireless Mobile Ad Hoc Network”, Asian Journal of Information Technology, 2014, Vol.13, No.(2), pp. 68-76, 2014
[24] J. M. Singh, P. Josh Kumar, Ayyaswamy Kathirvel, N. Kirubakaran, P. Sivaraman, M. Subramanian: “A unified approach for detecting and eliminating selfish nodes in MANETs using TBUT”, EURASIP journal on Wireless Communication and Networking, 2015, 143, 2015
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[29] K. A. Adoni, R. D. Joshi: “Optimization of Energy consumption for OLSR routing protocol in MANE”, International Journal of Wireless and Mobile Networks, India, February 2012, Vol.4, No.(1), pp. 251-262, 2012
[30] F. Bai, A. Helmy: “A survey of Mobility Models in Wireless Adhoc Networks”, Study – Grant NSF Career Award 0134650, University of Southern California, USA

K. A. Adoni, A. S. Tavildar, K.K. Warhade, "Mitigating Randomized Selfish Behavior Attack Using Trust-Confidence Aware OLSR for Efficient Data Communications," International Journal of Computer Sciences and Engineering, Vol.6, Issue.7, pp.228-238, 2018.

Prevalent Resolver to Digital Converter (RDC) is frequently adopted using DSP techniques to reduce the hardware tread and improve system accuracy. However, in such implementations, both resolver and ADC channel imbalance introduce significant errors, practically in speed output of the type-II track loop algorithm. This paper discusses the design of digital filters based on the interpolation of pre-design filters for a DSP based on type-II track loop algorithm with square wave excitation. Such filters are tenth order high pass filter and tenth order peak filter, the projected DSP based RDC system is executed in MATLAB/SIMULINK the simulation results demonstrate the decrease the peak-to-peck error estimation of speed out response of the system.

Resolver, RDC, type-II tracking loop algorithm, ADC channels, Adaptive digital filter design

[1] V. K. Agrawal, S. Sarma, and S. Udupa, “Software based Resolver-to-Digital Conversion using a DSP,” Industrial Electronics IEEE Transactions on, vol.55, no.1, pp.371-379, January 2008.
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T.Venu Gopal Reddy, Chandra Mohan Reddy Sivappagari, "Design of Resolver-To-Digital Converter for Motor Control Applications," International Journal of Computer Sciences and Engineering, Vol.6, Issue.7, pp.239-244, 2018.

Growth of Computer applications in most of the people and companies are wanted to work through computers. They mostly use computer to store and retrieve information. Data mining is organizing and retrieving information from large data set. Now a day’s dataset may be dynamic. Text Document clustering is a passion or an interested area of data mining. Many of the clustering method needed for a new one requires better clustering approaches. A new proposal is an improved KLOA with feature selection method for text mining that is Improved KLOA. K-means is one of the active algorithms for wider application of clustering technique. But it has some inconvenience to form a cluster in the initial point. A novel KLOA algorithm is refined and enhanced by k-means algorithm. This is used to pick the initial point and perform well when some think is rendered. To implement Feature selection method is to find subset and improve the process of cluster. Using Feature selection method is to improve the quality of cluster and find intrinsic properties of dataset. In this new article using wrapper technique of feature selection method is implemented and produces high quality of text clusters, with more accuracy and performance.

Clustering Technique, Data mining, Feature selection, Optimization, Text Clustering

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[19] A.K.Sharma and S.K.Patel, “Optimization of Dynamic Resource Scheduling algorithm in Grid Computing Environment”, Vol(6), Issues-3,2018
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Jagatheeshkumar. G, S. Selva Brunda, "An Improved K-Lion Optimization Algorithm With Feature Selection Methods for Text Document Cluster," International Journal of Computer Sciences and Engineering, Vol.6, Issue.7, pp.245-251, 2018.

The increase in average lifespan, growing population and sedentary lifestyle has increased the need for ubiquitous healthcare services. Wireless Body Area Network (WBAN) is one such approach which serves as a promising health monitoring service. Several sensors are implanted in or attached to human body to monitor the health status of the patients. The obtained physiological information from patient is transmitted to the doctor so that the patient will be constantly and remotely monitored. Thus, WBAN provides location flexibility to the patients. Nevertheless, security and privacy issues are one of the downsides in adopting WBAN to its full advantage. The medical records are private and confidential. Hence for a patient to trust WBAN, physiological information captured by the sensors need to be reliably transmitted to the doctors. Another issue is the limited battery life of sensors. It is crucial for WBANs to have a longer network lifetime to avoid constant recharging and replacement of nodes attached to a patient. This is possible by proposing energy efficient routing protocols for lowering energy consumption. These protocols should also reduce the network traffic by reducing the size of the data before transmission. The current work proposes an energy efficient approach for secure transmission of patient data to higher medical personnel. The proposed work extends the work of Rel-AODV protocol by considering compression model and cost based function having parameters of delay and residual energy. The results show that the proposed methodology is energy efficient and improves the overall QoS of the system.

WBAN, Wireless Body Area Networks, Routing Protocols, Cost Function, Energy efficiency, QoS

[1] S.Movassaghi, M. Abolhasan, J. Lipman, D. Smith, A. Jamalipour, “ Wireless body area networks: A survey”, IEEE Communications Surveys & Tutorials, Vol. 16, Issue.3, pp.1658-1686, 2014.
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[3] S.S. Javadi, M.A.Razzaque, “Security and privacy in wireless body area networks for health care applications”, In Wireless networks and security, Springer, pp. 165-187, 2013.
[4] J.I.Bangash, A.H.Abdullah, M.H.Anisi, A.W.Khan, “A survey of routing protocols in wireless body sensor networks”, Sensors, Vol. 14, Issue.1, pp.1322-1357, 2014.
[5] Pallvi, S.K.Gupta, R.K.Bedi, “An Improved Energy Efficient TDMA based MAC Protocol for WBAN”, International Journal of Computer Sciences and Engineering, Vol.6, Issue.3, pp.34-39, 2018.
[6] S. Singla, K. Sharma, “A Review Paper on Wireless Body Area Network for Health Care Applications, International Journal of Computer Science and Mobile Computing, Vol.5, Issue.10, pp. 1-10, 2016.
[7] R. Kumar, A.K. Jain, “Simulation Survey of RSA and Its Variants”, International Journal of Computer Sciences and Engineering, Vol. 5, Issue.7, pp.67-70, 2017.
[8] S. Boopathiraja, P. Kalavathi, , S. Chokkalingam, “A Hybrid Lossless Encoding Method for Compressing Multispectral Images using LZW and Arithmetic Coding”, International Journal of Computer Sciences and Engineering, Vol. 6, Issue. 4, pp.313-318, 2018.
[9] Z.A.Khan, S.Sivakumar, W.Phillips, N.Aslam, “A new patient monitoring framework and Energy-aware Peering Routing Protocol (EPR) for Body Area Network communication”, Journal of Ambient Intelligence and Humanized Computing, Vol. 5, Issue. 3, pp.409-423, 2014.
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[16] A.Negi, A.Goyal, “Optimizing Fully Homomorphic Encryption Algorithm using RSA and Diffie- Hellman Approach in Cloud Computing”, International Journal of Computer Sciences and Engineering, Vol.6, Issue.5, pp.215-220, 2018.

R.Singla, N.Kaur, "Compressed and Secure Energy Efficient Routing Protocol for WBAN," International Journal of Computer Sciences and Engineering, Vol.6, Issue.7, pp.252-258, 2018.

One of the fundamental feature of web search engine is keyword suggestion. After submitting a keyword query, the user may not be satisfied with the results, so the keyword suggestion module of the search engine recommends a set of alternative keyword queries that are most likely to refine the user’s need. The suggested keywords are semantic relevance to keyword query. Spatial vicinity of user can be also consider to get suggestion in effective manner. In this paper, we develop location-aware keyword query suggestion framework considering the document distance and rating. The system uses keyword document graph for capturing semantic relevance between keyword queries and spatial distance of document and query issuers’ location. The keyword document graph is browsed in random walk with restart fashion, for calculating the highest score for better keyword query suggestion. The baseline algorithm and partition-based algorithm uses RWR to compute top-m suggestions and based upon users selected keyword query the documents are ranked using bayesian ranking method.

Keyword query suggestion, Spatial objects, Document proximity

[1] Shuyao Qi, Dingming Wu, and Nikos Mamoulis “Location Aware Keyword Query Suggestion Based on Document Proximity,” IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, VOL. 28, NO. 1, JANUARY 2016.
[2] J. Fan, G. Li, L. Zhou, S. Chen, and J. Hu, “SEAL: Spatio-textual similarity search,” Proc. VLDB Endowment, vol. 5, no. 9, pp. 824– 835, 2012.
[3] D. Wu, G. Cong, and C. S. Jensen, “A framework for efficient spatial web object retrieval,” VLDB J., vol. 21, no. 6, pp. 797–822, 2012.
[4] H. Tong, C. Faloutsos, and J.-Y. Pan, “Fast random walk with restart and its applications,” in Proc. 6th Int. Conf. Data Mining, pp. 613–622, 2006.
[5] Y. Fujiwara, M. Nakatsuji, M. Onizuka, and M. Kitsuregawa, “Fast and exact top-k search for random walk with restart,” Proc. VLDB Endowment, vol. 5, no. 5, pp. 442–453, Jan. 2012.
[6] Y. Liu, R. Song, Y. Chen, J.-Y. Nie, and J.-R. Wen, “Adaptive query suggestion for difficult queries,” in Proc. 35th Int. ACM SIGIR Conf. Res. Develop. Inf. Retrieval, pp. 15–24, 2012.
[7] L. Li, G. Xu, Z. Yang, P. Dolog, Y. Zhang, and M. Kitsuregawa, “An efficient approach to suggesting topically related web queries using hidden topic model,” World Wide Web, vol. 16, pp. 273–297, 2013.
[8] R. Baeza-Yates, C. Hurtado, and M. Mendoza, “Query recommendation using query logs in search engines,” in Extending Database Technology, pp.588–596, 2004.
[9] H. Cao, D. Jiang, J. Pei, Q. He, Z. Liao, E. Chen, and H. Li, “Context-aware query suggestion by mining click-through and session data,” in Proc. 14th ACM SIGKDD Int. Conf. Knowl. Discovery Data Mining, pp. 875–883, 2008.
[10] P. Berkhin, “Bookmark-coloring algorithm for personalized pagerank computing,” Internet Math., vol. 3, pp. 41–62, 2006.
[11] N. Craswell and M. Szummer, “Random walks on the click graph,” in Proc. 30th Annu. Int. ACM SIGIR Conf. Res. Develop. Inf. Retrieval , pp. 239–246, 2007.
[12] Q. Mei, D. Zhou, and K. Church, “Query suggestion using hitting time,” in Proc. 17th ACM Conf. Inf. Knowl. Manage., pp. 469–478, 2008.
[13] P. Boldi, F. Bonchi, C. Castillo, D. Donato, A. Gionis, and S. Vigna, “The query-flow graph: Model and applications,” in Proc. 17th ACM Conf. Inf. Knowl. Manage., pp. 609–618, 2008.
[14] Y. Song, D. Zhou, and L.-w. He, “Query suggestion by constructing term-transition graphs,” in Proc. 5th ACM Int. Conf. Web Search Data Mining, pp. 353–362, 2012.
[15] M. P. Kato, T. Sakai, and K. Tanaka, “When do people use query suggestion Inf. Retr.,” vol. 16, no. 6, pp. 725–746, 2013.
[16] T. Miyanishi and T. Sakai, “Time-aware structured query suggestion,” in Proc. 36th Int. ACM SIGIR Conf. Res. Develop. Inf. Retrieval, pp. 809–812, 2013.
[17] Akshay A. Bhujugade, Dattatraya V. Kodavade “A Survey on Keyword Interrogation Implication on Document Vicinity Based on Location,” International Journal of Computer Engineering In Research Trends, Volume 4, Issue 11, pp. 514-518, November - 2017.

A.A. Bhujugade, D.V. Kodavade, "Keyword Interrogation Implication on Document Vicinity Based on Location and Rating," International Journal of Computer Sciences and Engineering, Vol.6, Issue.7, pp.259-165, 2018.

The metadata properties and the characteristic features of display structure of image/video files transferred/exchanged using Bluetooth, Wifi(Shareit) and WhatsApp among the android based smart phones have been analyzed. This metadata study involves the fundamentals of sharing image through Bluetooth, Wifi and the social networking application “WhatsApp”. From the findings of the study the originated source of image/video files could be identified or trace out, which could be very useful for forensic authentication of suspect image/video files as well as in police investigation of various types of the crime cases. Moreover, this research emphasizes the size, resolution and location of the image clicked and shared in different sharing media applications like Bluetooth, WiFi and WhatsApp. New technologies present both challenges and opportunities for the security professional, especially for areas such as digital forensics. It analyzes potential originated source with location of device as they may have used for the crime by criminals. The tests and analysis were performed with the aim of determining what metadata and information can be found on the device memory for sharing of images/video. The experiments and results show that the potential evidences and valuable data can be found on sharing of data in Android phones by forensic investigators.

WhatsApp, Android and Windows Operating Systems, Smartphone, Image & Shareit

[1] Cosimo Anglano , “Forensic analysis of WhatsApp Messenger on Android smartphones” Digital Investigation. Volume 11, Issue 3, pp 201-213, 2014.
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[3] Neha S. Thakur, “Forensic Analysis of WhatsApp on Android Smartphones,” University of New Orleans Theses and Dissertations pp.1706
[4] Kehinde Funmilayo Mefolere , “WhatsApp and Information Sharing: Prospect and Challenges”, International Journal of Social Science and Humanities Research, Vol. 4, (Issue 1), pp: (615-625), 2016,
[5] Shubham Sahu, “An Analysis of WhatsApp Forensics in Android Smartphones”, International Journal of Engineering Research, Volume No.3, (Issue No.5), pp: 349-350, 01 May 2014
[6] Umesh Kumar Singh, ShivlalMewada, Lokesh Laddhani & Kamal Bunkar, “An Overview & Study of Security Issues in Mobile Ado Networks”, International Journal of Computer Science and Information Security (IJCSIS) USA, Volume-9, No.4, pp (106-111), April 2011.ISSN: 1947-5500
[7] R. Nathiya, S.G. Santhi, “Energy Efficient Routing with Mobile Collector in Wireless Sensor Networks (WSNs)”, International Journal of Computer Sciences and Engineering, Vol.2, Issue.2, pp.36-43, 2014.

A. Pathania, D.P. Gangwar, A. Kumar, "Study of Meta Data Properties of Image and Video Files of Android Based Smart Phones," International Journal of Computer Sciences and Engineering, Vol.6, Issue.7, pp.266-270, 2018.