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Effective response to identification and authentication of individuals in complex environment demands replacement of traditional authentication techniques. It should occur concurrently with the increased pace of the digital world and increasing population. Many unimodal template security systems have been published, but in one or the other way, they are associated with some technical flaws, which prevents them from claiming to be reliable models. After doing the critical review of many published articles and case studies, many design characteristics of template security systems like security level, reliability, privacy level, acceptability, performance, uniqueness and cost, were taken into consideration for analyzing the various available models. However, no model was found to be associated with all the design parameters, which could claim to be a highly secure and reliable model. On review basis, it was found that many design characteristics were underestimated, if taken into consideration for development and implementation, could revolutionize biometric based template security systems.

Biometrics, Feature Extraction, Unimodal systems, Multimodal systems, Template Security Scheme

[1] A. M. P. Canuto, F. Pintro, and M. C. Fairhurst, “An effective template protection method for face and voice cancellable identification,” vol. 11, pp. 157–166, 2014.
[2] Handbook of Biometrics Handbook of Biometrics. .
[3] Y. J. Chin, T. S. Ong, A. B. J. Teoh, and K. O. M. Goh, “Integrated biometrics template protection technique based on fingerprint and palmprint feature-level fusion,” Inf. FUSION, 2013.
[4] D. T. Meva, “Comparative Study of Different Fusion Techniques in Multimodal Biometric Authentication,” vol. 66, no. 19, pp. 16–19, 2013.
[5] S. R. S. Sree and N. Radha, “A Survey on Fusion Techniques for Multimodal Biometric Identification,” pp. 7493–7497, 2014.
[6] A. Selwal and S. K. Gupta, “Region Coded Hashing based Template Security Scheme for Multi-biometric System,” no. 3, 2016.
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[13] C. Rathgeb, J. Wagner, B. Tams, and C. Busch, “PREVENTING THE CROSS-MATCHING ATTACK IN BLOOM FILTER-BASED CANCELABLE BIOMETRICS da / sec - Biometrics and Internet Security Research Group , Hochschule Darmstadt , Germany Institute for Mathematical Stochastics , University of G ¨,” 2015.
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[15] B. Choudhury, P. Then, V. Raman, B. Issac, M. K. Haldar, and G. L. Co-, “Cancelable Iris Biometrics Based on Data Hiding Schemes,” pp. 1–6, 2016.
[16] R. Jeng and W. Chen, “Two Feature-Level Fusion Methods with Feature Scaling and Hashing for Multimodal Biometrics,” vol. 4602, no. March, 2016.
[17] A. Selwal, S. K. Gupta, and Surender, “Low overhead octet indexed template security scheme for multi-modal biometric system,” J. Intell. Fuzzy Syst., vol. 32, no. 5, pp. 3325–3337, 2017.
[18] J. Aravinth, S. Valarmathy, J. Aravinth, and S. Valarmathy, “modal biometric recognition and its application to remote biometrics authentication Multi classi fi er-based score level fusion of multi-modal biometric recognition and its application to remote biometrics authentication,” vol. 2199, no. December, 2016.
[19] S. Sojan and R. K. Kulkarni, “Mixing Fingerprint Features for Template Security,” no. 7, pp. 355–359, 2016.
[20] D. Jagadiswary and D. Saraswady, “Biometric Authentication using Fused Multimodal Biometric,” Procedia - Procedia Comput. Sci., vol. 85, no. Cms, pp. 109–116, 2016.
[21] M. Lim, S. Verma, G. Mai, and P. C. Yuen, “Learning discriminability-preserving histogram representation from unordered features for multibiometric feature-fused-template protection,” Pattern Recognit., vol. 60, pp. 706–719, 2016.
[22] A. Selwal and S. Kumar, “Fuzzy Analytic Hierarchy Process based Template Data Analysis of Multimodal Biometric Conceptual Designs,” Procedia - Procedia Comput. Sci., vol. 85, no. Cms, pp. 899–905, 2016.
[23] A. Selwal and S. Kumar, “Template security analysis of multimodal biometric frameworks based on fingerprint and hand geometry ଝ,” Perspect. Sci., vol. 8, pp. 705–708, 2016.
[24] Rathgeb C, Busch C, “Cancelable Multi-Biometrics: Mixing Iris-Codes based on Adaptive Bloom Filters,” Computers & Security (2014), doi: 10.1016/j.cose.2013.12.005.

Mahapara Khurshid, Arvind Selwal, "On Biometrics Feature Extraction and Template Security Schemes", International Journal of Computer Sciences and Engineering, Vol.06, Issue.03, pp.1-7, 2018.

A country like India, where economy is strongly driven by agricultural products. If plants are suffering from any kind of disease, it may amount loss in both quantity and quality of the agricultural products. The disease diagnosis is one of the very challenging tasks for farmers. Usually, the disease or the symptoms of the disease such as spots or streaks are seen on the leaves or stem of a plant. Most of the diseases in plants are caused by bacteria, fungi, and viruses. In order to prevent such loss, it is vital to detect and diagnose the disease at the early stage. This paper presents a survey of various fruit disease detections using image processing techniques and neural networks. Various authors have proposed different techniques for fruit disease identification and classification. The techniques such as texture feature extraction using GLCM, color-based segmentation, artificial neural network and different classifiers are used. The focus of work is to carry out the analysis of different fruit disease detection techniques

Artificial Neural Networks, Supervised learning,Texture FeatureExtraction,FruitDiseases.

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[6] Z. Jian, “Support Vector Machine For Recognition Of Cucumber Leaf Diseases,” no. 1, pp. 264–266.
[7] A. N. Rathod et al., “LEAF DISEASE DETECTION USING IMAGE PROCESSING AND,” vol. 1, no. 6, pp. 1–10, 2014.
[8] P. Mohanaiah, P. Sathyanarayana, and L. Gurukumar, “Approach,” vol. 3, no. 5, pp. 1–5, 2013.
[9] J. Francis, V. J. Engineering, and V. Jyothi, “PEPPER PLANTS USING SOFT COMPUTING TECHNIQUES.”
[10] S. S. Sannakki, V. S. Rajpurohit, V. B. Nargund, and P. Kulkarni, “Diseases using Neural Networks ”,” pp. 3–7, 2013.
[11] S. D. Khirade, “Plant Disease Detection Using Image Processing,” pp. 1–4, 2015.
[12] G. Kambale and N. Bilgi, “A Survey Paper on Crop Disease Identification and Classification Using Pattern Recognition and Digital Image Processing Techniques,” no. Acbcda, pp. 14–17, 2017.
[13] A. Kadir, L. E. Nugroho, A. Susanto, and P. I. Santosa, “Leaf Classification Using Shape , Color , and Texture Features,” pp. 225–230, 2011.
[14] Meunkaewjinda. A, P.Kumsawat, K.Attakitmongcol and A.Sirikaew.2008 Grape leaf diseasefrom color imaginary using Hybrid intelligent system”, Proceedings of ECTICON
[15] D. Cao, “An improved k-medoids clustering algorithm,” pp. 132–135.
[16] “Automatic Recognition System Using Preferential Image Segmentation For Leaf And Flower Images,” vol. 1, no. 4, pp. 13–25, 2011.
[17] A. B. Blight, “Neural Network,” 2015.IEEE
[18] M. Zhang and M. Qinggang, “Citrus canker detection based on leaf images analysis,” 2nd Int. Conf. Inf. Sci. Eng. ICISE2010 - Proc., pp. 3584–3587, 2010.
[19] J. Pradeep, M. B. Tanveer, S. A. Makwana, and R. Sivakumar, “Er Er,” vol. 2, no. 4, pp. 161–168, 2013.
[20] “AN IMPLEMENTATION OF GRAPE PLANT DISEASE DETECTION,” no. 4, pp. 527–535, 2015.
[21] K. S. Neethu and P. Vijay, “Leaf Disease Detection and Selection of Fertilizers using Artificial Neural Network,” pp. 1852–1858, 2017.
[22] A. H. Kulkarni, H. M. Rai, K. A. Jahagirdar, and P. S. Upparamani, “A Leaf Recognition Technique for Plant Classification Using RBPNN and Zernike Moments,” vol. 2, no. 1, pp. 984–988, 2013.

Mahvish Jan, Arvind Selwal, "A Study of Fruit Disease Detection using Pattern Classifiers", International Journal of Computer Sciences and Engineering, Vol.06, Issue.03, pp.8-15, 2018.

Cloud-Computing refers to the technology that provides different services as per demand via different web-based tools. Cloud computing can be thought of as a pool of resources that delivers software, data, storage, servers, computing resources etc as a service. Virtualization is a technology that acts as a ground for cloud-computing. Virtualization is a technique that enables the division of devices or resources such as servers, operating devices, memory into multiple instances and each one behaves as a whole single machine independent of each other (called virtual machine). Virtualization creates these virtual versions of devices and resources with the help of a middleware. The machine on which a middleware runs one or more virtual machines (VM) is called the Host Machine. In the life cycle of a virtual machine there may exist a necessity to transfer a virtual machine from one host machine to another host machine due to different reasons like fault tolerance, load balancing, energy management, system-maintenance etc. and this is called virtual machine migration. The two main techniques of migrating a VM between different hosts are pre-copy and post copy. In virtual machine migration, the placement of virtual machine between hosts play a critical role as it puts a straight effect on the performance, power consumption and application of resources of the physical machine on which VM is placed. This research paper provides the survey and analyses of existing techniques of virtual machine migration and also throws some light on virtual machine placement schemes. Different virtual machine migration techniques are also compared in the paper. Finally, the proposed work and conclusion are highlighted.

Cloud-Computing, virtualization, virtual machine migration, machine migration techniques, virtual machine placement schemes.

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[2] S. Al-haj and E. Al-shaer, , “A Formal Approach for Virtual Machine Migration Planning”, Cnsm 2013, pp. 51–58, 2013.
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[4] U. Deshpande and K. Keahey, “Traffic-sensitive Live Migration of Virtual Machines”,Futur. Gener. Comput. Syst., vol. 72, pp. 118–128, 2017.
[5] M. Masdari, S. S. Nabavi, and V. Ahmadi, “An overview of virtual machine placement schemes in cloud computing”, J. Netw. Comput. Appl., vol. 66, pp. 106–127, 2016.
[6] Y. Yu and Y. Gao, “Constraint programming-based virtual machines placement algorithm in datacentre”, IFIP Adv. Inf. Commun. Technol., vol. 385 AICT, pp. 295–304, 2012.
[7] Xiaoli, W. and L. Zhanghui. “An energy-aware VMs placement algorithm in Cloud Computing environment”, Intelligent System Design and Engineering Application (ISDEA), 2012 IEEE Second International Conference on, 2012.
[8] Gursharan Singh, Sunny Behal, Monal Taneja,“Advanced memory reusing mechanism for virtual machines in cloud computing”, 3rd International Conference on Recent Trends in Computing 2015 published by ELSEVIER, pp 91 - 103, July 2015 .
[9] Gahlawat, M . and P. Sharma, “Survey of virtual machine placement in federated Clouds”, in Advance Computing Conference (IACC), 2014 IEEE International, 2014 .
[10] Q. Zhang, L. Cheng, and R. Boutaba, “Cloud computing : State-of-the-art and research challenges”, pp. 7–18, 2010.
[11] Divya Kapil, Emmanuel Spill, Ramesh C .Joshi, “Live virtual machine migration techniques survey and research challenges”,IEEE, 2012 .
[12] M. R. Hines, U. Deshpande, and K. Gopalan , “Post-copy livemigration of virtual machines”, pp. 14–26 , 2009.
[13] Gulshan Soni, Mala Kalra, “Comparative study of live virtual machine migration techniques in cloud” , IJCA, vol 84, no. 14, December 2013.
[14] Abazari, F. and M. Analoui, “Exploring the effects of virtual machine placement on the transmission of infections in cloud”. in Telecommunications (IST), 2014 7th International Symposium , 2014.
[15] T. Hirofuchi, H. Nakada, S. Itoh, and S. Sekiguchi, “Reactive consolidation of virtual machines enabled by postcopy live migration”, pp. 11–18, 2011.
[16] B.Hayes , “Cloud ComputingBible” Wiley Publication.,2008.
[17] Z. Lei, E. Sun, S. Chen, J. Wu, and W. Shen, “A novel hybrid-copy algorithm for live migration of virtual machine”,‖ Futur. Internet, vol. 9, no. 3, p. 37, 2017.

Saima Fayaz Chashoo, Deepti Malhotra, "Virtual Machine Migration and Placement Schemes-limitations and challenges", International Journal of Computer Sciences and Engineering, Vol.06, Issue.03, pp.16-20, 2018.

Opportunistic Routing (OR) is the latest strategy of routing in wireless sensor networks in which the nearer node to the target is selected for transferring the data. OR may immensely enhance the performance parameters like efficiency, throughput, and reliability by selecting best next hop in Opportunistic Protocol. In OR, a candidate set is chosen which serves the purpose of a potential group of nodes for packet forwarding. This paper presents the literature review of various opportunistic routing protocols. The tabular representation of various OR protocols on the basis of End-to-End delay, energy Efficiency, packet duplication and forwarding list selection is depicted in this paper. The comparative analysis of various opportunistic routing protocols has been given in this paper.

Wireless Sensor Networks, Routing, Opportunistic Routing

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[13] X. Zhang and B. Li, “Optimized Multipath Network Coding in LossyWireless Networks,” Ieee J. Sel. Areas Commun., vol. 27, no. 5, pp. 622–634, 2009.
[14] E. Rozner, J. Seshadri, Y. A. M. Mehta, and L. Qiu, “{SOAR}: Simple Opportunistic Adaptive Routing Protocol for Wireless Mesh Networks,” IEEE Trans. Mob. Comput., vol. 8, no. 12, pp. 1622–1635, 2009.
[15] Y. Yuan, H. Yang, S. H. Y. Wong, S. Lu, and W. Arbaugh, “ROMER : Resilient Opportunistic Mesh Routing for Wireless Mesh Networks,” IEEE 1st Work. Wirel. mesh networks, 2005.

Sheikh Shahid Ali, Yashwant Singh, "On Opportunistic Routing in Wireless Sensor Networks", International Journal of Computer Sciences and Engineering, Vol.06, Issue.03, pp.21-25, 2018.

Security and privacy is a much-needed aspect of the connected world. If these functionalities are not deployed properly then every economic or societal institution dependent on them are vulnerable to get crashed and might even cause a damage of catastrophic scale. People would eventually stop trusting these technological platforms that are supposed to make their lives better. Although security is a paramount functionality in any connected infrastructure, there is no silver bullet to it, there has been extensive research in this field but no one has come up with an idea that can secure the distributed and heterogeneous IoT network efficiently. IoT demands an autonomous access control methodology requiring minimal or no user interaction. There are several existing models that are good and effective however they have several implementation issues. In this paper we have described our survey of the existing security models of IoT and presented a brief comparative analysis of the discussed models also some of the main requirements for designing such models is given.

IoT, Security, blockchain, access-control, models

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[8] N. Kshetri, “Can Blockchain Strengthen the Internet of Things?,” IT Prof., vol. 19, no. 4, pp. 68–72, 2017.
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Shahid Ul Haq, Yashwant Singh, "On IoT Security Models:Traditional and Block chain", International Journal of Computer Sciences and Engineering, Vol.06, Issue.03, pp.26-31, 2018.

Sorting is one of the basic problems that have been extensively studied. There are many sorting algorithms which are efficient in computation but cannot use cache efficiently. Efficient use of cache is an important factor for determining the performance of an algorithm. Cache-oblivious algorithms are designed that are both work and cache efficient. The aim of this paper is to evaluate the performance of cache-oblivious sorting algorithm called Lazy Funnelsort on multicore processors. The evaluation is made against the well known fast sorting algorithms: quick sort, merge sort on multicore processor machine. The experiments are conducted against different input sizes and number of processing cores and threads using Intel Cilk Plus, which is extension to C and C++ to express task and data parallelism. The performance of algorithms is examined in terms of execution time, speedup, efficiency and scalability. The results show that parallel implementation of Lazy Funnelsort is better than its sequential implementation and also scalable on multiple cores. Though it has been outperformed by quick sort and merges sort algorithms but shows moderate promise as a parallel algorithm.

Cache-oblivious, Funnelsort, Performance, Speedup, Efficiency, Cache-miss-ratio

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Riaz Ahmed, Lalitsen Sharma, "Performance Evaluation of Lazy-Funnelsort Algorithm on Multicore System", International Journal of Computer Sciences and Engineering, Vol.06, Issue.03, pp.32-37, 2018.

The present investigation was carried out to study the academic achievement of secondary school students with respect to gender and type of school. A sample of 240 secondary school students (120 male and 120 female) was drawn randomly from two districts (Anantnag and Kupwara) of Kashmir (J&K), India. Self-constructed Information Blank was used to locate the Internet-user secondary school students. The subjects’ previous academic marks secured in their final examination conducted by J&K BOSE have been taken a major yard-stick to assess the academicperformance. The data was subjected to statistical analysis by applying mean, standard deviation and t-test. A significant difference between male Internet-user and female Internet-user secondary school students was confirmed. The results further highlighted a significant difference on academic performance of internet users with respect to their type of school.

Internet Usage, Academic Achievement, Secondary School Students

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S.A. Mir, A.A. Paray, "Internet Usage and Academic Performance: An Empirical Study of Secondary School Students in Kashmir", International Journal of Computer Sciences and Engineering, Vol.06, Issue.03, pp.38-41, 2018.

The whole concept of message dissemination in Vehicular Ad hoc Networks relies on the inter-vehicle cooperation. This helpful nature of vehicles has empowered vehicles to gather and trade traffic related messages continuously. In this manner, it is conceivable to utilize Vehicular Ad-hoc Networks for event discovery on urban roadways. Due to the uneven topology of urban roadways comprising of both major and auxiliary roadways, different protocols are designed. These protocols are designed to detect traffic related events on roadways. Some protocols might be efficient for a particular road but may fail for some other types of roads. Besides, the current scattering strategies for occasions related data do not have the essential control system, so the message(information) might be dispersed to different geographical areas. This paper presents the review of existing message dissemination and event detection protocols in VANET. A tabular representation of various protocols of message dissemination and event detection on parameters like radio propagation model, transmission range, standard and simulator have been given. The comparative analysis of these existing protocols is also presented in the same section.

Vehicular ad-hoc networks, message dissemination, event detection, radio propagation model, transmission range

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[17] W. Viriyasitavat, O. K. Tonguz, and F. Bai, “UV-CAST: An urban vehicular broadcast protocol,” IEEE Commun. Mag., vol. 49, no. 11, pp. 116–124, 2011.
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Towseef Ahmad Wani, Yashwant Singh, "On Message Dissemiaton and Event Detection in VANET", International Journal of Computer Sciences and Engineering, Vol.06, Issue.03, pp.42-45, 2018.

Steganography is the art of concealing secret information in some given information. Steganography hides the existence of the message unlike cryptography which keeps the contents of message secret. Image steganography is the branch of steganography where secret information is hidden inside an image. There are various techniques of image steganography i.e., spatial domain and frequency domain. In this paper, a review of image steganography techniques is presented using qualitative parameters like robustness, embedding capacity and quantitative parameters like PSNR, SNR, MSE are taken into consideration for analyzing the efficiency of various techniques of image steganography. The study reveals that transform domain techniques are more robust than spatial domain techniques even though are more complex than spatial domain techniques. Furthermore, it is observed that edge based data hiding in DCT domain has more embedding capacity and is more robust than spatial domain techniques.

Imagesteganography,DCTdomain,datahiding

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[19] T. Nadu, “Sobel edge detection technique implementation for image steganography analysis .,” pp. 1–7, 2017.
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[21] Ammad Ul Islam, Faiza Khalid, Mohsin Shah, Zakir Khan , Toqeer Mahmood3, Adnan Khan Usman Ali2, Muhammad Naeem” An Improved Image Steganography Technique based on MSB using Bit Differencing”,IEEE awe 978-1-5090-2000,2016.

Nadish Ayub, Arvind Selwal, "Image Steganography using Edge Based Data Hiding in Dct Domain: An Overview", International Journal of Computer Sciences and Engineering, Vol.06, Issue.03, pp.46-50, 2018.

There is an enormous amount of information available in the form of documents, articles, links, webpages, etc., which can`t be read completely until effectively summarized. Different procedures are effectively used to separate the imperative information from data to produce summary. This paper gives a brief description of text summarization and deep learning approach called Recurrent Neural Networks (RNNs). Recent advances in Deep RNN methods like Sequence to Sequence, Generative Adversarial Networks, etc. show remarkable results for text summarization. Long Short Term Memory (LSTM) and Gated Recurrent Unit (GRU) networks are discussed to overcome the problem of Vanishing or Exploding Gradient.

RNN, Sequence to Sequence, Vanishing gradient, LSTM, GRU, Deep Recurrent Generative Decoder, GANs

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Touseef Iqbal, Abhishek Singh Sambyal, Devanand, "A Review of Text Summarization using Gated Neural Networks", International Journal of Computer Sciences and Engineering, Vol.06, Issue.03, pp.51-55, 2018.