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Although cloud computing has become one of the basic utility in ICT era with several benefits like rapid elasticity, resource pooling broad network access, and on-demand self-service, it introduces dozens of dirty security threats too. An effective authentication protocol is the basis, topmost prioritized and emergence one for the secure cloud communications. As a result, in this article an effective trust-aware authentication framework is proposed based on n-party multi-linear key pairing functions, trust and reputation aggregation functions and time-based dynamic nonce generation. In addition to formulating an effective authentication protocol, we have analyzed the mutual authentication and formal security strength by using cryptographic GNY belief logic which will prove proposed protocol not only meets intended mutual authentication, but also justifies the security strength against the impersonation and ephemeral secret leakage attacks.

Mutual Authentication, Single Sign-On, Elliptic-Curve, Cloud Service Provider, Identity Provider, Trustee

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SaboutNagaraju, S.K.V. Jayakumar, "An Effective Trust-aware Authentication Framework for Cloud Computing Environment," International Journal of Computer Sciences and Engineering, Vol.6, Issue.12, pp.125-137, 2018.

Personal identification and/or authentication using finger vein pattern is becoming most reliable biometrics in many system securities because of its security, accuracy and convenience. The finger vein pattern based biometrics uses human’s vascular/vein pattern for their unique identification based on the fact that every individual has distinct veins pattern in their fingers. Finger vein pattern biometric trait is robust against the forgery and does not affect due to external factors since it is inherent and hidden under the skin. Therefore, finger vein pattern based biometrics has gained lot of attention of many researchers. This research paper present an approach designed for personal identification using local and global combined features of finger vein pattern. The finger vein pattern local features are extracted using Local Line Binary Pattern and global texture features are extracted using Discrete Wavelet Packet Transform jointly. Feature level fusion method is adopted for constructing the combined feature vector. Then, Support Vector Machine (SVM) based supervised learning algorithm is used for the feature matching and classification. Experiments are conducted using proposed approach on the finger vein image database of Shandong University, China. The experimental results show that proposed approach outperforms the other methods in terms of the recognition accuracy and performance.

Finger Vein Recognition, Local Binary Pattern, Line Binary Pattern, Discrete Wavelet Packet Transform, Support Vector Machine (SVM)

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Santosh P. Shrikhande, H. S. Fadewar, "Personal Identification using Local and Global Feature of Finger Vein Patterns using SVM Based Classification," International Journal of Computer Sciences and Engineering, Vol.6, Issue.12, pp.138-145, 2018.

A 4th order phase-locked loop model by considering two different filter configurations in the loop have been developed and behavioral simulation has been performed on MATLAB platform to study the impact of gamma-optimization parameter on it and also to study the stability of the system in terms of phase margin. We have also investigated the bandwidth and lock time of the system.

Bandwidth, gamma optimization parameter, lock time, phase margin, stability

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Munmee Borah, Tulshi Bezboruah, "A Study on γ - Optimization Parameter and Phase Margin of Fourth Order Phase-Locked Loop," International Journal of Computer Sciences and Engineering, Vol.6, Issue.12, pp.146-150, 2018.

In spite of having limited benefits, software clones mostly have negative impact on software quality, more specifically on software maintenance and thus diminishing software quality and raising the maintenance cost. Not all the clones are possible to remove, but, if possible clones need to be removed from the software system. To remove clones, we need to first detect this duplication in the code base. Literature lists various clone detection techniques that are used to detect duplication in software system. To have a better clone detection technique in future or to select from the available clone detection technique, these available techniques found in literature need to be analyzed. This paper attempts to comparatively analyze the clone detection techniques available in literature and thus will present a future scope as well as the recourse based on the analysis for selection of any particular technique.

Code Clone Detection, Clone Detection Techniques, Comparative Analysis

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Sarveshwar Bharti, Hardeep Singh, "Metaphorical Analysis of Software Clone Detection Techniques based on Dimensions and Metrics," International Journal of Computer Sciences and Engineering, Vol.6, Issue.12, pp.151-156, 2018.

The present medical scenario though it is very trustworthy and reliable because of the latest medical imaging modalities like MRI and CT etc., manual segmentation is prominently used in early malignancy detection, which is time-consuming. So there is a need for the automated method in terms of both accuracy and time requirement, which will provide better insight to the medical expert. Nowadays the machine learning plays an important role in this aspect since it learns through experience. The purpose of this paper is to demonstrate and make comparison of neural network with a traditional approach. We have used computational phantom data set to be considered as medical images and compare the performance of neural network with traditional segmentation by using dice similarity coefficient. The result concludes that even noise increases in medical images, the neural network approach gives high dsc value than traditional techniques.

Medical imaging, Sheep Logan phantom dataset, Fuzzy C-means, neural network

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B.J.Talati, N.D. Shah, "Automated Malignancy detection using neural network," International Journal of Computer Sciences and Engineering, Vol.6, Issue.12, pp.157-163, 2018.

Wireless communication involves a wide variety of technologies, services and applications, developed to satisfy the user’s specific needs in variety of deployment scenarios. The cellular phones are one of the examples of wireless communication application. Globally, the cellular networks have progressed from a simple first generation to fourth generation and probably will be progressing to fifth generation by the end of 2019. Though there is an appreciable progress in the high speed data with the generation, the problem in the voice call still persists, particularly when in motion, due to the continuous changes in the receiving signal. This article aims at improving the QoS by implementing the tele-traffic pattern proposed in earlier 90’s by Steele and Nofal to manage the hand-off mechanism in order to reduce the voice and data degradation during motion and simulating same using Network Simulator 2 for validation. The results of the experimental analysis show that the hand off degradation of voice and data is reduced by the implementation of the said tele-traffic pattern. Hence, proving the proposed energy detection technique on the Steele and Nofal traffic model to be best suited for the handoff situation.

Wireless communication, Handoff technique, Network Simulator 2, Analytical energy detection

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[29] J. Labovský, Z. Švandová, J. Markoš, and L. Jelemenský, "Mathematical model of a chemical reactor—useful tool for its safety analysis and design", Chemical Engineering Science, Vol. 62, Issue. 18–20, pp. 4915–4919, 2007.
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Shivi Saxena, Arun Kumar, "Analysis of Received Signal Strength under Handoff Condition using Network Simulator 2," International Journal of Computer Sciences and Engineering, Vol.6, Issue.12, pp.164-168, 2018.

This paper introduces a new method to improve visual search results and understand structured data. While many online resources teach basics of web development, few of them are designed to help novices learn the web development concepts and design patterns used by experts to implement complex visual features. Professional web pages embed these design patterns and could serve as rich learning materials, but their metadata are complex and difficult for novices to understand. This paper presents Metadata.py*, a Metadata inspection tool that helps novices use their visual intuition to make sense of professional web pages/sites. We introduce a new visual relevance testing technique to identify properties that have visual search results, which Metadata.py uses to hide visually irrelevant code and surface unintuitive relationships between properties. In user studies, Metadata.py helped novice developers replicate complex web features 75% faster than those using Chrome Developer Tool and allowed novices to recognize and explain unfamiliar concepts. These results show that visual inspection tools can support learning from complex professional web pages, even for novice developers. Metadata,py: Python Script using Beautiful Soup, a python library for pulling data out of HTML and XML files.

Visual Search, SEO, Optimization

[1] M. L. Bernard. Examining the effects of hypertext shape on user performance. Usability News, 4(2), 2002.]]
[2] An Attribute-Assisted Reranking Model for Web Image Search, Isroset-Journal (IJSRCSE) Vol.4 , Issue.3 , pp.16-19, Jun-2016
[3] L. H. Armitage and P. G. B. Enser. Analysis of user need in image archives. Journal of Information Science, 23(4):287--299, 1997.]]
[4] P. Borland and P. Ingwersen. The development of a method for the evaluation of interactive information retrieval systems. Journal of Documentation, 53(3):225--250, 1997.]]
[5] R. C. Veltkamp and M. Tanase. Content-Based Image Retrieval Systems: A Survey. Technical Report UU-CS-2000-34, Dept. of Computing Science, Utrecht University, 2000.]].
[6] Greenberg, Jane, M. Pattuelli, B. Parsia, W. Robertson, Author-generated Dublin Core Metadata for Web Resources: A Baseline Study in an Organization, Journal of Digital Information, volume 2 issue 2 (November 2001)
[7] Heery, Rachel and Manjula Patel, Application Profiles: Mixing and Matching Metadata Schemas, Ariadne, Issue 25 (September 2000)

Saichethan Reddy, "Improving Visual Search Results," International Journal of Computer Sciences and Engineering, Vol.6, Issue.12, pp.169-171, 2018.

Natural dialog conversation between humans and machines is a flourishing topic of the modern world, now show off their presence across a range of daily use devices and digital assistants. This is tried to be achieved by using sub-field of Artificial Intelligence named Natural Language Processing. The task is to be practically implemented through a series of convenient and capable categories by some of the market leaders with their successful products named the Amazon ALEXA, Microsoft CORTANA, Google ASSISTANT, Apple SIRI to quote a few. A virtual assistant put to real world usage has to perfectly emulate a human dialogue, analyze the input given by a user, represent the same correctly, convert to its process able form and formulate a relevant and appropriate response. In this paper, we review a few market leading voice based chat bots, identifying their technical aspects along with their advantages and disadvantages during the practical usage.

Chat bots, NLP (Natural Language Processing), CI (Conversational Interfaces), ALEXA, SIRI, Google ASSISTANT, Microsoft CORTANA)

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[2] A. M. Rahman, A. A. Mamun and A. Islam, "Programming challenges of chatbot: Current and future prospective," 2017 IEEE Region 10 Humanitarian Technology Conference (R10-HTC), Dhaka, 2017, pp. 75-78. DOI: 10.1109/R10-HTC.2017.8288910
[3] Amanda Purington, Jessie G Taft, Shruthi Sannon, Natalya N Bazarova, Samuel Hardman Taylor, "Alexa is my new BFF": Social Roles, User Satisfaction, and Personification of the Amazon Echo CHI EA `17 Proceedings of the 2017 CHI Conference Extended Abstracts on Human Factors in Computing Systems, Pages 2853-2859 , DOI: 10.1145/3027063.3053246
[4] Zubairm, Paul; Bhat, Heenareyaz; Lone Tanveer, “CORTANA-INTELLIGENT PERSONAL DIGITAL ASSISTANT: A REVIEW”. International Journal of Advanced Research in Computer Science; Udaipur Vol. 8, Iss. 7, (Jul 2017). DOI: http://dx.doi.org/10.26483/ijarcs.v8i7.4225
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[7] Assefi, Mehdi & Liu, Guangchi & Wittie, Mike & Izurieta, Clemente. (2015). “Experimental Evaluation of Apple Siri and Google Speech Recognition”. October 2015, SEDE 2015, At San Diego, DOI: 10.1145/3027063.3053246
[8] V. Këpuska and G. Bohouta, "Next-generation of virtual personal assistants (Microsoft Cortana, Apple Siri, Amazon Alexa and Google Home)" 2018 IEEE 8th Annual Computing and Communication Workshop and Conference (CCWC), Las Vegas, NV, 2018, pp. 99-103. DOI: 10.1109/CCWC.2018.8301638
[9] H. Al-Zubaide and A. A. Issa, "OntBot: Ontology based chatbot", International Symposium on Innovations in Information and Communications Technology, Amman, 2011, pp. 7-12. DOI: 10.1109/ISIICT.2011.6149594

Anusha S, N Vignesh Karthik, Sampada K S, "Comparative Study on Voice Based Chat Bots," International Journal of Computer Sciences and Engineering, Vol.6, Issue.12, pp.172-175, 2018.

Mobile Adhoc Network (MANET) is a self-organized group of wireless nodes forming a tentative network. In MANET nodes would be randomly changing their positions due to its dynamic infrastructure-less property. Therefore it is more susceptible to Black-Hole & Gray-Hole attacks, which are considered as serious attacks to the network. So far several solutions have been developed for MANET but many of them are not efficient. The main purpose of this paper is to present a solution known as mechanism for detecting Black Hole Attack in Infrastructure-Less MANET (MDB-MAN). An Algorithm is developed to detect Black-Hole node based on reactive Adhoc on demand distance vector protocol (AODV), where routes are established on demand. Several times simulations were conducted on proposed model using Network Simulator and found that the Packet Delivery Ratio (PDR) and Throughput is almost similar at time instant 50 msec. as compared to original AODV protocol. The Packet Drop Ratio keeps on changing as time changes and it can be tolerable.

MANET, AODV, MDB-MAN, Black-Hole attack, Gray-Hole attack

[1] S. Jain, N. Hemrajan, S. Srivastava, “Simulation and Analysis of Performance Parameters for Black Hole and Flooding Attack in MANET Using AODV Protocol”, International Journal of Scientific & Technology Research Vol. 2, Issue. 7, pp. 66-69, July 2013.
[2] A. Patel and A. Jain, “A study of various Black Hole Attack techniques and IDS in MANET”, International Journal of Advanced Computer Technology, Vol. 4, Issue. 3, pp. 58-62, 2016.
[3] R. Garg, V. Mongia, “ Mitigation of Black Hole Attack in Mobile Ad-Hoc Network Using Artificial Intelligence Technique”, International Journal of Scientific Research in Computer Science, Engineering and Information Technology , Vol. 3, Issue. 1, pp. 1168-1174, 2018.
[4] S. Muqtar Ahmed and S. Abdul Sattar, “International Journal of Computer Science and Engineering”, Vol. 6, Issue. 11, pp. 77-82, 2018.
[5] M. Jahnke, J. T¨olle, S. Lettgen, M. Bussmann, and U. Weddige, “A Robust SNMP Based Infrastructure for Intrusion Detection and Response in Tactical MANETs”, Springer-Verlag Berlin Heidelberg, pp. 164–180, 2006.
[6] I. Saada, M. Z. Rashad, R. H. Sakr, “Implementing and Comparing LIDBPP (Local Intrusion Detection by Bluff Probe Packet)”, International Journal of Computer Science and Network Security, Vol.16 Issue.8, pp. 20-24, August 2016.
[7] A. A. Bhosle, T. P. Thosar and S. Mehatre, “Black-Holeand Wormhole Attack in Routing Protocol AODV in MAN”, International Journal of Computer Science, Engineering and Applications, Vol. 2, No.1, February 2012.
[8] P.C. TSOU, J. Ming CHANG, Y.Hsuan LIN, H.Chieh CHAO, J. Liang CHEN, “Developing a BDSR Scheme to Avoid Black Hole Attack Based on Proactive and Reactive Architecture in MANETs”, 13th International Conference on Advanced Communication Technology, ICAC-2011.
[9] P. N. Raj and P. B. Swadas, “DPRAODV: A dyanamic learning system against black hole attack in aodv based manet”, IJCSI International Journal of Computer Science Issues, vol. 2, pp. 54–59, 2009.
[10]. L. Himral, V. Vig, and N. Chand, "Preventing Aodv Routing Protocol From Black Hole Attack", International Journal of Engineering Science and Technology (IJEST), Vol .3, 2011.
[11]. H. M. Salmon, C. M. d. Farias, P. Loureiro, L. Pirmez, "Intrusion Detection System for Wireless Sensor Networks Using Danger Theory Immune-Inspired Techniques", International Journal of Wireless Information Networks, Vol. 20, Issue.1, pp. 39-66, 2013.
[12] S. K. Dhurandher, I. Woungang , R. Mathur , P. Khurana, “GAODV: A Modified AODV Against Single and Collaborative Black Hole Attacks in MANETs”, 27th International Conference on Advanced Information Networking and Applications Workshops, 2013.
[13] Rutvij, H.J., “MR-AODV: A solution to mitigate black hole and gray hole attacks in AODV based MANETs. Pro”, 3rd International Conference on Advanced Computing and Communication Technologies, CCT-2013.
[14] R. Murugan, A. Shanmugam, “Cluster Based Node Misbehaviour Detection, Isolation and Authentication Using Threshold Cryptography in Mobile Ad Hoc Networks”, International Journal of Computer Science and Security 3 Vol. 6; Issue. 3; Start page: 188, 2012.
[15] U. K. Singh, J. Patidar and K. C. 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. 11-16, 2015.
[16] P K. Sharma, S. Mewada and P. Nigam, “Investigation Based Performance of Black and Gray Hole Attack in Mobile Ad-Hoc Network”, International Journal of Scientific Research in Network Security and Communication, Vol.1, Issue. 4, pp. 8-11, 2013.

Syed Muqtar Ahmed, Syed Abdul Sattar, "Mechanism for Detecting Black Hole Attack in Infrastructure-Less MANET (MDB-MAN)," International Journal of Computer Sciences and Engineering, Vol.6, Issue.12, pp.176-181, 2018.

Ovarian Cancer represents the main challenge among the gynecologic malignancies and early stage detection is of primary significance, because recently more than 2-3 of the patients present with development infection. Ovarian Cancer disease and treatment has measureable belongings on the superiority of patients of life with OC (ovarian cancer). In this study reviews existing related on eminence of life in users with OC to establish the significance of the topic. The main issues in the detecting process areas are the cancer detection on ultra sound image is not easy to identify on the foundation of gathering or image segmentation and the research work accuracy rate is 90 percent to 95 percent of Normal SVM existing systems. It can be refitted. The quality of the scan in ultrasound images are not appropriate for the system because the view of images is difficult to classify in terms of various segments or data clusters. In research work, implement Otsu technique is reliable and efficient method, used world-widely. It’s an all-around limiting strategy with dark estimation of picture. Otsu technique is a simplified, reliable and efficient method, used world-widely. It’s an all-around limiting strategy with dark estimation of picture. The classification and clustering is used k-SVM to train the cancer images in the each stage dataset and test the cancer detection and enhance the quality of the cancer image (MRI images). To compute the metric of performance like Accuracy Rate, Specificity and Sensitivity and compared with prior approaches i.e. accuracy and other performance metrics.

OC (Ovarian Cancer), DWT (Discrete Wavelet Transformation), SVM (Support Vector Machine), DCT (Discrete Cosine Transformation), ED (Edge Detection).

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[6] Jimenez-del-Toro, Oscar, et al. "Cloud-based evaluation of anatomical structure segmentation and landmark detection algorithms: VISCERAL anatomy benchmarks." IEEE Transactions on Medical Imaging (2016).
[7] Charles Patrick Davis, PhD. 2018. "Cancer Causes, Types, Treatment, Symptoms & Signs". Medicinenet. https://www.medicinenet.com/cancer/article.htm.
[8] Tsai, Meng-Hsiun, Ching-Hao Lai, Shin-Jr Lu, and Shun-Feng Su. "Performance comparisons between unsupervised clustering techniques for microarray data analysis on ovarian cancer." In Systems, Man and Cybernetics, 2006. SMC`06. IEEE International Conference on, vol. 5, pp. 3685-3690. IEEE, 2006
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A. Sidhant, L. Sehgal, "Ovarian Cancer Detection Using K-Svm Algorithm," International Journal of Computer Sciences and Engineering, Vol.6, Issue.12, pp.182-188, 2018.