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Conventional cryptography is a method of transforming message into an unreadable format called as cipher text. This cipher text can easily be shared over the network without fear but anyone can get message easily by applying key on cipher text. Sharing and delivering secret images over the network is also known as a visual secret sharing (VSS) scheme. However main drawback of VSS scheme is that it is experience from high transmission risk due to the shares are like noise. As the shares are like noise which in turn lead to cause the attackers attention. To solve this problem mechanism is developed called Natural image based visual secret sharing (NVSS). This paper is motivated by need of novel mechanism to transfer the secret images over network. In proposed work for regeneration of secret image a generated noisy share, natural images and seed (needed for random functions used) are required at the receiving end. Though generated share is noisy and its contents are not recognizable, overall structure may be visible in some cases. So data hiding is should be performed on generated share to hide that structure (texture) in noisy share.

A Wireless Networks are more accessible to different types of attack than wired Network. One such attack is Wormhole Attack, in which traffic is forwarded and replayed from one location to another through the Wormhole tunnel without negotiating any cryptographic techniques over the network. Thus, it is challenging to defend against this attack. In this paper we review WSN concept and Wormhole Attack. Then we discuss classification of wormhole Attack and also mention few of the initiatives to detect the Wormhole Attack.

Due to rapid growth of internet, online shopping for products is an essential part of everyone’s daily life most of the time credit card is used to pay online for products. It is an easy way to shopping, people can get your desired product on your computer screen or on smart phone. For online purchase use of credit card increases dramatically but still there is some loop holes in system of online shopping which causes online frauds or credit card frauds. There are many techniques like ANIDS Distributed Data mining WSDL, Parallel granular neural networks, Hidden Markov Model, Clustering and Bayes classification, Cost model are used. These techniques use data mining to detect frauds by the use of datasets like KDD99, KDD cup, NSL KDD. In this paper a study on different techniques and evaluate each technique on the best parameters.

over Internet protocol (VoIP), which is a communication protocol existing over a network. The IP network can makes it possible for users to make telephone calls using the VoIP technology. Use of VoIP and Internet telephony has increased significantly in the recent years. These new phone services are based on the transmission of voice over packet switched IP networks. VoIP can be realized on any data network that uses IP, like the Internet, Intranets and Local Area Networks (LAN). VoIP customers use their Internet connection to connect to the Internet as well as to make phone calls. VoIP is the real-time transfer of voice signals using the Internet Protocol (IP) over the Internet or a private network. In simpler terms, your voice is converted to digital signal by VoIP that travels over the internet. The key factors that entice enterprises to switch to VoIP are its flexibility and cost efficiency. Some security problems may arise due to the widespread deployment of VoIP. Voice over IP (VoIP) has the potential to provide interactive communication services like video and voice conferencing. VoIP helps to transfer data which are difficult to transfer over circuit-switched wired and wireless networks.

Data Storage Security is matter of concern especially in the field of Cloud Computing where large amount of data is being stored on daily basis over the internet. But the real world is facing some or other challenging issues regarding the same. An ubiquitous and an on-demand access with an interoperable network of your various computing resources and sharing necessary information is the need of this Internet dependent Earth, which has led the generation of Cloud and the virtual world related to it. As the number of users and data over the net are getting increased second by second there is a need of system or method which could hold this with all its privacy, integrity and confidentiality. But the vulnerabilities over Cloud data are weakening the expected progress of the field. Many complex encryption and decryption techniques are being introduced but the new risks get generated. The organisation at every level is concerned with privacy of the data and various attacks which don’t enable them to use the Cloud’s benefits and its susceptibility over the data holds the technology to grow. Some trustworthy and dependable Cloud storage will be a good option with the specific authentication as well as proper agreements and auditing protocols defines earlier itself will motivate the people to be secure and tension free while storing the data over the Cloud. General Terms Cloud Computing, Data storage security.

Steganography is the process to hide a secret message such that it is very difficult to detect the presence of secret message presence. On other way, the existence of secret message is hidden. A covert channel may refer to the actual medium that is used to communicate the information such as a message, image as well as file. This project uses steganography within the source address fields of Internet Protocol Version 6 (IPv6) packets to create a covert channel through which clandestine messages can be passed from one party to another. A fully functional computer program was designed and written that transparently embeds messages into the source address fields of packets and across IPv6 networks, embedded messages are by these packets. This demonstrates the covert channel possibility within a default Internet protocol. For a malicious purpose such as stealing encryption passwords as well as keys or other secrets from remote hosts in a sequence not easily detectable this channel is used, but it may be used for a noble cause such as secretly passing messages under the watchful eyes of an oppressive regime. The covert channel demonstration in itself the overall information security of society is increased by bringing awareness to the existence of such a steganographic medium.

In today’s Era, message transmissions over the internet have protection problems of the digital data. Hence, protection of secret messages during transmission becomes a difficult subject. Digital watermarking is provide protection of digital information or identifying information against illegitimate exploitations and allocations. watermarking is a technology to guarantee and make possible data certification, security and copyright defense of the information. The intend of watermarking is to consist of hidden data in multimedia information to ensure security examination. It would be then probable to progress the surrounded message, even if the information was distorted by one or more non-dangerous attacks. In this paper, we present the various types of watermarking techniques and application region where water making technique required. Also a survey on the some new work is done in image watermarking field.

plays a vital role in research area in the field of data mining. Clustering is a process of partitioning a set of data in a meaningful sub classes called clusters. It helps users to understand the natural grouping or cluster from the data set. It is unsupervised classification that means it has no predefined classes. This paper presents a study of various partitioning techniques of clustering algorithms and their relative study by reflecting their advantages individually. Applications of cluster analysis are Economic Science, Document classification, Pattern Recognition, Image Processing, text mining. No single algorithm is efficient enough to crack problems from different fields. Hence, in this study some algorithms are presented which can be used according to one's requirement. In this paper, various well known partitioning based methods - k-means, k-medoids and Clarans - are compared. The study given here explores the behaviour of these three methods.

Steganography is the skill of hiding the existence of data in other transmission medium to attain secret communication. It does not restore cryptography but quite boost the security using its abstruse features. In this paper we have surveyed on a Steganography and cryptography techniques which provide highly secure skin tone data hiding. Biometric characteristic used to apply steganography is skin tone region of images. Here important data is implanted within skin region of image which will give an outstanding secure location for data hiding. For this skin tone detection is need to be performed. Different steps of data hiding can be applied by cropping an image interactively. Cropping of an image improved security than hiding data without cropping the whole image, so cropped region works as a key at decoding region. Cryptography algorithm is used to convert the secret messages to an unreadable form before embedding; which provides a strong backbone for data security. This survey paper focuses on illuminating the technique to secure data or message with authenticity and non repudiation. So with this object oriented steganogaphy we track skin tone objects in image with the higher security and satisfactory PSNR .Modern steganography’s goal is to keep its mere presence undetectable.

is an important aspect for all living things. It proves to be a lifesaving component in case of emergency requirement. There are number of web based blood banks which are available for communication between blood bank and hospitals. None of the online blood bank offers the direct contact between donor and blood bank. This is the major drawback of the existing system. Existing systems are time consuming; require more man power and it is costly. This paper introduces comparison between existing system and improved system. The new idea will improve the existing system and it will move from conventional desktop system to mobile system. This paper introduces new features of improved system over existing system in many aspects. In this paper firstly we are going to explain merits and demerits of existing system. Also this paper will provide brief introduction about improved system and its features and Scope.

Data mining is used to extract interested pattern or knowledge from large amount of data using many data mining technique. However it may also display sensitive information about individuals compromising the individual right to privacy When a collection of data is split among various parties. Now Each and Every party would wants to keep its sensitive information private during the mining process. Privacy preserving data mining is to develop data mining method without increases the risk of misuse of data. The main aim of privacy preserving data mining is to find the global mining results by preserving the individual sites private data/information. The various methods such as randomization, perturbation, heuristic and cryptography techniques. To Find privacy pre serving association rule mining in horizontally and vertically partitioned databases. In this paper, the analysis of different methods for PPARM is performed and their results are compared. Horizontally Partitioned databases, algorithm that combines advantage of both RSA public key cryptosystem and Homomorphic encryption scheme and algorithm that uses Paillier cryptosystem to compute global supports are used. This paper reviews the wide methods used for mining association rules over horizontally distributed dataset while preserving privacy.

amount information of moving objects on road network is being collected with the help of various recent technologies. The tracking of these moving objects on road networks is becoming important because of it's application in various areas. Classification has been used for classifying various kinds of data sets like graph, text documents. However, there is a lack of study on data like trajectories on road networks. Data mining techniques, especially, sequential pattern mining can be used to extract frequent spatio-temporal patterns. Again it needs to confine the length of sequential patterns to ensure high efficiency. After extracting frequent sequential patterns in trajectories, classification can be applied to classify patterns which provide useful information in applications such as city and transportation planning, road construction, design, and maintenance, marketing sector. In this paper, whole pattern matching query concept is adopted after the classification to find total traffic volume on given trajectory edge. At the same time, user can find number of vehicles moving in one as well as in both directions on that particular trajectory. Keywordssequential patterns, frequent pattern based classification, location based services, pattern matching.

The importance of automatic methods has increased greatly for paper currency recognition due to the development of modern banking services like automated teller machine (ATM) and automatic goods seller machines. For a machine, it is a challenge to recognize paper currency whether it is of 10, 20, 50, 100, 500 or 1000. Various method or algorithm has been applied to overcome this challenge and in most of systems neural network is used. For this, LBP algorithm is proposed in this paper. The proposed method has advantages of simplicity and high speed. The experimental results show that this method has a high recognition rate. The recognition ratio can achieve 100% in case of good quality images.

Kinesthetic, Auditory, Reading / Writing Preference Learning and Visual Learning are the 4 categories of learning types as per the widely used Fleming VAK / VARK model. Visual Learning represents concepts visually. By representing the information visually students are able to concentrate on meaning, acknowledge and group similar ideas easily making better use of visual memory. Visual learning improves student performance in the areas of Retention, Reading Comprehension, Student Achievement and Critical Learning skills. this system focuses on semi-automatically converting textual learning resources related to important world events into visual information. Few examples include Terrorist Activities in India, 26/11 Mumbai bomb blasts and Earth Quakes in India. This systems scrapes the unstructured text from textual learning resources, applies natural language processing to extract named entities in the text, uses location api's and innovative visualizations (e.g. Google Maps) to visualize the world event information in an intuitive manner. Human intervention is needed in case of incomplete information in the learning resource and verification of generated information. This system makes it easy to identify human intervention need via data health reports. General Terms Fleming VAK / VARK model, Visual Learning Data mining, NLP(Natural Language Processing), visualization, cloud.

In the last few years, many image processing techniques have been presented in order to perform different brain tumor detection tasks. These cover Content-Based Retrieval Technique, Component Labelling Algorithm, Fuzzy C-Mean Algorithm. There is fast growth of image processing available in last few years; image segmentation have work together to get extraction of meaningful data into useful information. Image processing is used to finding applicable and efficient information from data available. With this survey paper we focus on literature survey of segmentation based image processing model as contain efficient performance.

CONFLICT OF INTEREST: NONE DECLARED Defect tracking systems play an important role in the software development organizations as they can store historical information about defects. There are many research in defect tracking models and systems to enhance their capabilities to be more specifically tracking, and were adopted with new technology. Furthermore, there are different studies in classifying bugs in a step by step method to have clear perception and applicable method in detecting such bugs. This paper shows a new proposed defect tracking model for the purpose of classifying the inserted defects reports in a step by step method for more enhancement of the software quality.

The concept of Internet of Things requires the seamlessly connectivity of millions of heterogeneous devices. In today’s world, Implementation of IoT in Smart Homes is one of the major applications of Internet of Things. In this paper, we will discuss the different challenges and risk to implement IoT in Smart Homes of India. An Indian perspective is taken, because India is in very first stage for implementing the Smart Homes. This paper explains many challenges in Indian scenario like availability of Internet, Cost of devices, device maintenance issue etc. and proposes a framework of smart homes is also discussed here.

Almost all countries have imposed strict laws on the disclosure of Personally Identifiable Information(PII). However PII need to be published for many purposes like research. In such cases, we apply different types of methods like anonymization, encryption etc. This paper discuss about the different methods of anonymization of tabular microdata. The most popular method of data anonymization of tabular data is k-anonymity. However, it suffers from many attacks and hence l-diversity was proposed. The l-diversity anonymization also possessed various limitations and hence t-closeness was proposed. This paper summarize these anonymization techniques and their limitations.

the breast cancer has been become one of the main reasons of death in women especially in the developed countries, there have been done many research for breast cancer diagnosis. Although researchers have recently proposed many methods by using intelligent approaches for diseases diagnosis, a few of them fulfill the need of high accuracy. In this paper, the most popular swarm intelligence algorithms PSO, ICA, FA and IWO are applied to diagnosis the breast cancer. The experimental results show that swarm intelligence approach can be applied for breast cancer diagnosis with high accuracy. Moreover, FA can diagnose the breast cancer more accurate than other swarm intelligence methods compared in this paper. KeywordsIntelligence, Diseases diagnosis, Breast cancer

is the most prominent & primary mode of Communication among human beings. Now-a-days Speech also has potential of being important mode of interaction with computers. This paper gives an overview of Automatic Speech Recognition System, Classification of Speech Recognition System and also includes overview of the steps followed for developing the Speech Recognition System in stages. This paper also helps in choosing the tool and technique along with their relative merits & demerits. A comparative study of different techniques is also included in this paper. KeywordsSpeech Recognition (ASR), ASR classification, Speech Analysis, Feature Extraction, Modelling Techniques, Language Modelling, Testing, ASR Tools.

Breast cancer is one of the ruinous diseases causing more number of deaths in women. Many efforts are being made to develop efficient techniques to identify the breast cancer at early stage. This paper implements weaver ant colony optimization (WACO) for classifying mammograms. The behavior of weaver ants' to bind the neurons between the layer to make the path to find the output of Neural Network(NN). The unique nest building behavior of Weaver ants' made a considerable remark, NN have proved to be one of the best methods for classification & WACO is used for optimized pathfinding. Each layer of NN is considered as one leaf and the leaves are divided into as many portions equal to the number of neurons,& let ants connect portion of leaf from one layer to another, makes the weight connection in the NN. The task is accomplished by using a NN with a back propagation technique (BPT). To determine the usefulness of WACO based Neural Network (NN)closed nests building behavior made us change the architecture of BPN. Weaver ants show indirect message between ants to find the shortest path between their nest and food sources. These ants ability is to construct nests by weaving together leaves using larval silk .Local Binary Pattern is a method which can be used extract the features for identifying the breast cancer abnormality by mammogram. Multilayer perceptron (MLP) and support vector machine for mammogram classification and mammogram images are preprocessed to reduce noise and detect the background of the mammogram to extract the required features. This paper implements WACO for classifying mammograms. Here we used MIAS database which describes the mammogram is in which stage benign or normal stage

study embodied in this paper, aims at making use of machine learning and computer vision algorithms in order to reliably identify the species of bacteria, from their microscopic images. The study has taken into consideration three of the most commonly occurring species of bacteria that are clinically important. The work shown further in this study can be extended to a larger number of bacteria species. The study makes use of the Speeded Up Robust Features or SURF algorithm for detecting image keypoints. The artificial intelligence classifier makes use of these keypoint vectors as its input variable. It is noteworthy that the images used are taken at the gram staining stage of bacterial identification, in order to minimize any biases in the dataset owing to a variance in staining technique, although the feature detector invariably grayscales the image prior to keypoint computation. The paper follows the study from the conception of the idea, to the formulating of the algorithm, the training and testing of the same.

Robotic Telepresence systems focus majorly on the concept of telecommunication and remote presence with independent mobility. Recently a number of Telepresence robots have been introduced in the market, each with some unique feature and show-off factor. While these systems promise good user experience, they are too expensive for the general public to use them. This paper proposes an innovative approach to build a commercial robotic Telepresence system called OATS. OATS stands for “Open Access Telepresence Systems”, which is an architecture primarily based on open source platforms like, WebRTC and MQTT. The uniqueness of the architecture is that, the Telepresence robot can use any mobile smartphone running an OATS client application, as the brain of the robot, reducing the need of expensive, onboard electronics and processing power. The smartphone connects to a robotic platform that enables the robot to move. Using this robot, a person can remotely interact using any smartphone or laptop. This OATS client connects to a server which provides services required for peer to peer videoconferencing and machine communication between the clients. A user can login to one of this Telepresence robot and pilot it in a remote area, from any part of the world. This architecture not only reduces the cost of the Telepresence robot, but the use of smartphone platform also opens up whole new possibilities for development of next generation of telepresence robots. In this paper, we briefly discuss the OATS architecture, its deployment strategies and its advantages over existing

As new devices and technologies are invented to access the internet, from computer desktops, laptops, mobile phones to smart TVs, there has been a great need to upgrade the techniques used in the field of website design, because these new devices come along with their own specific sizes and views. Although most devices & technologies try to be as compatible as possible with the common web design features, but there has been an absolute need for website designers to do a lit bit more to adapt to the fast growing race in internet devices and provide all their viewers with the best possible experience while accessing their websites. In this paper, different responsive website design techniques are presented that could adapt to different technologies and devices while at the same time focusing on cutting down the time and effort needed for a website designer or programmer to maintain and edit it. The code samples in this paper were implemented using the ASP.net programming language, but it can be implemented in other development languages and environments using the same concepts.

In this research paper,the authors are addressing the problem of algorithms for Wireless LAN for Secured Transmission. This research work also proposes an overview of some of the major attacks that Blue tooth has faced over the years along with some possible solutions. The main aim of this research work is to investigate security features of Bluetooth using Elliptic Curve Cryptography(ECC). The ECC is the latest and fastest encryption method which offers stronger security. As it is known that although a vast majority of devices currently now communicates using Bluetooth methodology, the blue tooth security expert provides automatic updates to its security protocol and user privacy protection techniques. Further protection of the device user’s personal information becomes the primary aim. The research work also explores the Bucket Brigade Attack on Bluetooth security using Elliptic Curve Cryptography (ECC). Also it is implied that Bucket Brigade Attack(BBA) is one of the amazing solution to the problem of key agreement or key swapping. Further the beauty of this scheme is when two parties who likes to communicate using symmetric key and an Elliptic Curve Cryptography(ECC) an Intruder(Hacker) enters in between a sender and a receiver. This paper is an attempt to implement the ECC after a survey over the current issues on security.

to the late overpowering development rate of large scale data, the advancement of handling faster processing algorithms with optimal execution has turned into a critical need of the time. In this paper, parallel Map-Reduce algorithm is proposed, that encourages concurrent participation of various computing hubs to develop a classifier on SEER breast cancer data set. Our algorithm can prompt supported models whose speculation execution is near the respective baseline classifier. By exploiting their own parallel architecture the algorithm increases noteworthy speedup. In addition, the algorithm don't require singular processing hubs to communicate with each other, to share their data or to share the knowledge got from their data and consequently, they are powerful in safeguarding privacy of computation also. This paper utilized the Map-Reduce framework to implement the algorithms and experimented onSEER breast cancer data sets to exhibit the execution as far as classification accuracy and speedup. Keywordscancer; Big dataanalytics, Classification; Parallel Computing; MapReduce, SEER.

This paper describes a sorting algorithm for Bengali texts which is one of the most vital tasks for Bengali Natural Language Processing. As Unicode is much more preferable than ASCII encoding, we need to use this representation for Bengali Language. But due to some distinct properties of Bengali Language, they cannot be sorted directly using the order in Unicode character scheme. A few works have been done on this topics – some of them are for ASCII encoding whether some are for Unicode. But still they have some drawbacks and still there is no standard to sort Bengali texts. In this paper, we have discussed about the previous approaches and proposing a revised and easier procedure to sort Unicode Bengali texts. We used a mapping to simplify the sorting process. The efficiency depends on the efficiency of the sorting algorithm. This method is able to sort any Unicode Bengali texts. It will also work for Unicode text of any language if we just change the mapping part. So the process is both keyboard and language independent. General Terms Theoretical Informatics

Wireless Sensor Networks consist of thousands of power constrained micro sensors whose main task is to sense and report the target phenomena to the base station. Hierarchical routing plays an important role for transmitting the aggregated data to the sink. Sensor nodes are organized into number of clusters and within each cluster, cluster head is responsible for collecting the data and to report that data to the Base Station. Machine learning algorithms play an important role while selecting the cluster head based on various QoS parameters. In this paper, a hierarchical protocol LEACH is chosen for analyzing the impact of machine learning algorithms – KMeans and modified K-Means clustering on energy consumption of nodes by varying the type of input parameters. This paper covers the brief introduction of 802.15.4 based Wireless Sensor Networks, power models, machine learning algorithms for sensor clustering and simulation environment using NetSim.

Energy efficient routing protocols have been the major topic of research these days. The main reason behind the wider research on the same is the limitation of mobile adhoc networks. The mobile adhoc network consist of nodes which have unlimited mobility level within the range, and most importantly limited battery capacity. These drawbacks of nodes harm the nodes itself and even the network‟s capacity they belong to. So as a result of this many routing protocols have been optimized and converted into energy efficient routing protocols. Out of the present protocols DSR is considered as the best protocol when conservation of energy is the need. This paper describes why DSR is considered as the best energy efficient algorithm. It also discusses the original DSR in brief and elaborating the strategies of optimization. This paper describes many variants of energy efficient DSR protocol. Each of the protocol uses different mechanism of optimization, but having the same global goal of effective energy utilization.

Now a day people are facing many health related problems. There is large amount of data that is not structured. The gathered information is raw and unstructured in the nature, so there is a need of converting it to meaningful services. In this paper such system is developed which will provide web service that will be available to any other person easily. Every person should get the healthcare services anywhere, every time even at their home also. For this purpose a platform is developed so that patient specially senior citizens can know their electro Cardiogram (ECG) or also can be said as heart rate, oxygen rate, temperature rate, through an android mobile application specially developed for the healthcare. This overall concept is developed under the Internet of Things as well as cloud computing environment. App which is developed named as ‘Patient Health Monitoring’. This paper gives an idea about Adriano kit which used in the project. This paper also gives an idea about the sensors which are used to measure above mentioned measures. A Bluetooth sensors is also used here for the connectivity. Server will be any network connection such as Wi-Fi.

paper presents a reliability prediction model that predicts the reliability of the developing software using fuzzy inference system. The focus of the study is on the reliability prediction prior to the coding phase so that the developers use this information for optimally performing resource planning and quality assessment of the software under development. Requirements and object-oriented design level product measures have participated for early reliability prediction. The paper has also utilized the strengths of fuzzy logic to deal with the uncertainties and vagueness involved in the early stage measures. The model has also been statistically validated through the data set obtained through twenty real software projects. The values of the Pearson's correlation coefficient along with the predictive accuracy measures are quite encouraging, and support that the developed model is a better and improved reliability prediction model.

Online multiplayer educational game is designed to support collaboration and assess different cognitive and social abilities among students. The educational games are developed to capture student responses or actions, both shared and unshared, within the game environment and extrinsic resources. This paper describes the implementation of new technology with better performance over existing HTML5 and Flash platform to develop such games, which have been developed as part of the ATC21STM research study by the University of Melbourne. CONSTRUCT2 has been used in preference to other available technologies in creating the games to deliver a reliable experience for students across all browsers, platforms, and devices. The multiplayer component of the games was maintained with the use of the AJAX and Web Socket application which allowed the communication protocol between the client and server to be established. Embedded Canvas on CONSTRUCT2 is used to create all animations and game objects. The paper will describe the issue such as multiplayer game design with new technology and optimization of collaborative game design using dynamic platform structure called „CONSTRUCT2‟ over HTML5 to facilitate the game flow and a positive user experience.

Health care applications have become boon for the healthcare industry. It needs correct segmentation connected with medical images regarding correct diagnosis. An efficient method assures good quality segmentation of medical images. Segmentation methods are classified as edge based, region based, clustering based, Level set methods (LSM) and Energy based methods. In this paper, a survey on all the effective methods those are capable for accurate segmentation is given, however quick process employing correct segments is still difficult. Some existing methods do correction and some badly pertain to deep irregularity in images. The wide range of the problems of computer vision may make good use of image segmentation. This paper studies and evaluate the different methods for segmentation techniques. This study is useful for determining the appropriate use of the image segmentation methods and for improving their accuracy and performance and also works on the main objective, which is designing new algorithms. The main goal is to make the image more simple and meaningful. After a brief description of each method an experimental comparison of some empirical (goodness and discrepancy) methods commonly used is then given to provide a rank of their evaluation abilities. This study is helpful for an appropriate use of existing segmentation methods and for improving their performance as well as for systematically designing new segmentation methods.

WSN today is an emerging field of research where different routing protocol takes part in order to compute the routing facility and data transfer in between various available nodes and medium. OLSR is one of the advantageous protocol while dealing with energy and efficient resource utilization scenario thus it is a growing area today. We have already discussed about the different available technique in our literature paper where the modification is still require when the nodes numbers are increased and energy level need to further optimized while communication in modified TC packets. TC packet leads to carry the information of weight and node information which means to TC packet modification scenario, thus the protocol is proposed MET OLSR technique which is in terms to store the state and weight of the nodes after each communication and thus it make available for next computation. In this paper we discuss about the proposed methodology MET OLSR and further we compute the comparison analysis in between existing OLSR and MET OLSR in terms of PDR and other relevant parameters.

first paper of this work, the design and the architecture of our proposed model framework, VANET Security as a Service (VSaaS), was discussed. In this second paper, the performance metrics measurements will be investigated through the NS2, SUMO and Trans simulations, to evaluate the security overhead of the secure Vehicle Information Messages (VIMs), which are sent by the vehicles to the cloud as a coarse-grained information. Moreover, our proposed model framework (VSaaS) will be discussed against the security requirements in the VANET.

assumes an essential part in today's electronic world. The developer utilizes diverse dialects to build up the product. Keeping in mind the end goal to create programming, it needs a few stages, for example, Analysis, Design, Implementation, Testing and Maintenance. Of these few stages, the investigation and outline get to be fundamental, since these are the most crucial component in the advancement of the product. Presently a-days, a large portion of the product is article stated, in light of the fact that the item arranged dialects give a simple approach to create and keep up the system. This item situated project is comprised of a few divisions based upon the reason. Every division performs some capacities subordinate upon the code. Every one of these divisions are then incorporated to give the single system. In the event that any blunder happened in any part of the project implies, it is important to change the influenced part of a system to expel the mistake. To keep away from this sort of pointless change with the long time term, the engineer must diagram and tests the underlying stage, for example, investigate and configuration. These sorts of tests on examination and outline for an article arranged project did by an innovation called the OOP (Object Oriented Paradigms). In this paper, an approach proposed for examination, the configuration to be completed in the improvement of the system, before begin to execute. These measurements developed by taking or gathering substantial volume of information keeping in mind the end goal to give the measurements reasonable to a wide range of Object-Oriented dialects, for example, Python, Ruby, .Net and R software for big data analysis. The proposed work gives the summing up procedure which termed as GenM (Generalized Measurement) strategy on the item situated programming. This is finished by executing the arrangement record for recognizing the mistake rate. Along these lines, this paper gives proficient systems to OOP.

Ad-hoc wireless networks are dynamic in nature. Ad-hoc networks are not depends on any predefined infrastructure. Whenever there is need of communication at that point these network can be deployed. In this paper we discuss Vampire attacks. All protocols susceptible for vampire attack. Vampire attacks are very easy to carry out throughout the network and difficult to detect. In this paper we discuss a method to mitigate vampire attacks. Then we compare new method with existing protocol and Beacon Vector routing. And we come to the conclusion that new protocol is better as it detect and prevent from vampire attack.

Smartphones have been characterized by their limited computational resources such as battery life, processor performance and storage capacity. The above mentioned limitations can be overcome by utilizing mobile cloud computing where the smartphone can utilize the sufficient cloud resources. A number of solutions have been suggested and developed to alleviate the issues with smartphone resource limitations however they are not efficient. This paper provides an overview on the existing algorithms for accessing resource hungry applications on the cloud clearly indicating their techniques and flaws. The paper also describes the directions for the future research. General Terms Algorithms for accessing resource hungry games stored on a cloud.

This paper showcases the different technologies available for making one’s home a smarter one. Lately the world has witnessed a great surge in the field of automation. With the increase in living standards of people the demand for smart homes has accentuated. So keeping in mind three main concepts of a smart home that is energy, safety and comfort, the paper brief’s about smart homes as an application of IOT and consequently discussing the challenges faced by IOT during the implementation of smart homes in India. The various wireless protocols being used also find an important place in manuscript.

Software Failure Modes and Effects Analysis (SFMEA) is a traditional system safety analysis technique which is widely used in the aerospace, automotive and other safety-critical intensive systems. However, traditional FMEA methods are difficult to identify and analyzing the failure modes which caused by the dynamic logical information between interfaces or functions, such as softwarehardware interaction. To intuitively assume the effects of module failures in a system, numerous approaches have been proposed. This work addresses the use of SFMEA by using an experiment for safety-critical embedded control systems. The work presented here provides a general example illustrating how SFMEA can be effectively applied to an 8-bit micro-controller (Chip 89S52) based computer control system having little or no hardware protection. This paper also describes Functional FMEA, interface FMEA, and detailed software FMEAs. The experimental results of SFMEA also found the hardware failures and memory faults. The safety analysis reveals several design deficiencies and physical faults for which modifications are needed. This paper also found that, when properly implemented SFMEA at the right point in the Software Development Life cycle, it makes requirements, design and code reviews more effective. It also identifies single point failures due to software.

Automatic Text Summarization is an interesting topic for research. Still it is growing on. Increment of the data is exponentially growing on and it becomes too much difficult to find out the correct or relevant data in huge amount of data. So it becomes important for researchers to use it for efficient retrieval of information. Hence Text Summarization plays an important role for this problem. Summarization gives the short version for the text document which contains the main context of the document. Summarization can be classified into two categories: Extractive and Abstractive. This paper presents the extractive summary using lexical chaining approach. Lexical chains are created by using Knowledge based database i.e. Wordnet. This paper compares results with the traditional methods and gives better results.

The Internet is a widely used paradigm where sharing of multimedia content is a major task. Spam image (an image that contains obscure or irrelevant content) is often discovered in web data available in servers and worldwide search engines. Techniques for spam filtering and finding or detecting obscure content in multimedia data (such as .JPEG, .png format of images) are available in the literature. This paper reviews different existing techniques to deal with obscure images and presents an enhanced ReP-ETD (Repetitive Pre-processing technique for Embedded Text Detection) technique in order to detect the obscured content in image data. The technique proposed in this paper first preprocess the multimedia image data using a Linux image script and further on OCR (Optical Character Reader) is used for the spamming image detection and depth analysis. The main contribution of this paper is to discover and perform spam word extraction from the embedded obscured image.

With the rapid growth of cloud computing, computing resources are provisioned as metered on demand services over networks and can be easily allocated and released with minimal management effort which increases the security risks. This paper aims to provide an understanding of the different threats created by multi-tenancy and virtualization in a public IaaS cloud. This paper further analyze the performance of Xen hypervisor using Apache benchmark which is chosen as it gives a good idea how the hypervisor is able to handle increasing I/O stress in terms of CPU and memory storage as the number of virtual machines increases, ultimately giving an figurative approach on solving threats created by multitenancy and virtualization in a public IaaS cloud.

Now-a-days Machine learning approach is used to solve many problems where intelligence is involved. Lots of time consuming task are done by computers with the power of statistics. In this paper, a machine learning based candidate selection procedure is proposed and implemented for a particular field. A huge amount of activity is involved in the job recruitment procedure. To reduce the manual task a probabilistic machine learning approach is described in this paper. A popular machine learning approach named Naive Bayes Classifier is used to implement the method. Baseline criteria selection depends on the recruiters demand. The proposed system learns from training dataset and produces a short listed eligible list based on learning. The more perfectly one feed the system result will be more accurate. General Terms Candidate Selection, Job Recruitment.

The world is fast moving towards digitalization. In the age of super-fast computational capabilities, everything has to be made digitalized so as to make the computer understand and thereby process the given information. Optical character recognition is a method by which the computer is made to learn, understand and interpret the languages used and written by the human beings. It provides us a whole new way by which computer can interact with human beings, in their own languages. Hence OCR has been a topic of interest for researchers all around the globe in the past decade and research paper involving OCR is increasing day by day. It is seen that efficient algorithms have increased the speed and accuracy of character segmentation and recognition. A substantial amount of work has been done on foreign languages such as English , Chinese etc. but very few paper are there for Indian languages baring a few for Hindi and Bengali. Hence our research work was directed towards development of a novel algorithm for Devanagari character segmentation for Hindi. Hindi is one of the eighteen languages recognized by the Indian constituency. It is also one of the oldest languages and is spoken by millions of people in India. Segmentation and Recognition of this particular language is difficult because of the presence of complex connected characters and presence of shirorekha. A novel approach has been proposed for the segmentation of the connected character. General Terms Pattern recognition, image segmentation.

Web Application are used for providing information and function on World Wide web for various e-commerce organization, medical-care, business and Government sectors which further requires security and vulnerabilities. This paper describes the type of SQL Injection Attacks and discusses the technique, to avoid them. The type of SQL Injection Attack, procedure for preventing from SQL Injection Attacks and related work which was done for this has been considered and explained in this paper. An effective and efficient scheme is proposed to prevent SQL Injection Attack which is locating between web application and database. In such a way to use SQM and Sanitization Application are necessary to extend security or keep from attacker to abusing the database. Through two way evaluations, it is proved that our proposed scheme is more secure and can forcefully cover all bases of our web-based application.