Steganography gained importance in the past few years due to the increasing need for providing secrecy in an open environment like the internet.Steganography is the art of hiding the fact that communication is taking place, by hiding information in other information. Many different carrier file formats can be used, but digital images are the most popular because of their frequency on the internet Steganography is used to conceal the information so that no one can sense its existence.In most algorithm used to secure information both steganography and cryptography are used together to secure a part of information. Steganography has many technical challenges such as high hiding capacity and imperceptibility. In this paper,we try to optimize these two main requriments by proposing a novel technique for hiding data in digital images by combining the use of adaptive hiding capacity function that hides secret data in the integer wavelet coefficients of the cover image with the optimum pixel adjustment (OPA) algorithm.The coefficients used are selected according to a pseudorandom function generator to increase the security of the hidden data.The OPA algorithm is applied after embedding secret message to minimize the embedding error.The proposed system showed high hiding rates with reasonable imperceptibility compared to other steganographic system.
An Efficient Contrast Enhancement of Medical X-Ray Images -Adaptive Region Growing Approach
Dr. Krishna Mohanta, Dr.V.Khanaa,
: In digital image processing Medical Imaging is one of the most significant application areas. For visualizing and extracting more details from the given image processing of medical images is much more supportive. Several techniques are existing nowadays for enhancing the quality of medical image. Contrast Enhancement is one of the most functional methods for the enhancement of medical images. Various contrast enhancement techniques are in practice, some are as follows: Linear Stretch, Histogram Equalization, Convolution mask enhancement, Region based enhancement, Adaptive enhancement is already available. Based on characteristics of image choices can be done. On comparing my approach with the existing popular approaches of adaptive enhancement and linear stretching, it has been concluded that the proposed technique is giving much better results than the existing ones. Further, the technique is seed dependent so selection of seed is very important in this algorithm. A seed chosen in darker regions will give better results than the seed chosen in brighter region, because it is assumed that user will require enhancing the darker portions of the image. Furthermore, zooming window and edge growing method is used to visualize the edges more precisely which gives an added advantage is to doctors for better perception of X-ray. Keywords: Histogram Equalization, Adaptive, Convolution, Mask, X-Ray, Zooming, Edge Growing
The approaching 4G (fourth generation) mobile communication systems are projected to solve still-remaining problems of 3G (third generation) systems and to provide a wide variety of new services, from high-quality voice to high-definition video to high-data-rate wireless channels.The term 4G is usedbroadly to include several types of broadband wireless access communication systems, not only cellular telephone systems. One of the terms used to describe 4G is MAGIC—Mobile multimedia, anytime anywhere, Global mobility support, integrated wireless solution, and customized personal service. As a promise for the future, 4G systems, that is, cellular broadband wireless access systems have been attracting much interest in the mobile communication arena.The 4G systems not only will support the next generation of mobile service, but also will support the fixed wireless networks.This paper presents an overall vision of the 4G features, framework, and integration of mobile communication. The features of 4G systems might be summarized with one word—integration. The 4G systems are about seamlessly integrating terminals, networks, and applications to satisfy increasing user demands. The continuous expansion of mobile communication and wireless networks shows evidence of exceptional growth in the areas of mobile subscriber, wireless network access, mobile services, and applications.
MODERN APPROACHES FOR DETECTING DATA LEAKAGE PROBLEMS
B. Sruthi Patil Mrs. M. L. Prasanthi
In Organizations, detecting data leaker is facing many difficulties to find who cause for the data leakage. In previous approaches there are many techniques to find the leaker using fake objects and how much data leaked. In this paper, we present S-Random, S-Optimal, E-Random and E-Optimal techniques to find the (leaker). In this, we assigning the data with addition of fake objects through that, if the data is leaked then fake objecthelp to find the particular by using E-Random and S-Random techniques.It improves the efficiency for finding the leaker.
SECURITY ISSUES AND RESOURCE PLANNING IN CLOUD COMPUTING
Dr Dwivedi S K Dr Kushwaha D S Maurya Ankit
With the rapid development of Internet, Cloud Computing has a vast area of the application such as security services, enhance efficiency of system by utilizing resources in cost effective manner. Cloud computing is simply a service that is sold and delivered on demand over the internet. Firstly, models of cloud computing discussed in this paper are: Service Model and Deployment model. Well-known service providers and vendors for these services of cloud computing are investigated. Secondly, the cloudlet relationship architecture and the resources management for them are described. Latter the security and privacy issues of cloud computing are discussed. Finally, the paper will be concluded on the benefits and applications of cloud com
REALIZATION OF ARTIFICIAL NEURAL NETWORK IN POWER SYSTEM & MICRO-GRIDS: A REVIEW
Mr. S.K.Mishra, Sumit Mishra , Ruchi Misha
Environmental concerns and rising energy consumption has offered new opportunities for public use of renewable energy sources. In the current power and energy scenario, distributed generation (DG) has created a lot of interest across the globe due to the growing concerns about environmental pollution and global warming caused by greenhouse gas emissions. Renewable DGs such as wind generators and solar photovoltaic are well recognized now-a-days as sources of clean energy. Instability in power system has always been a serious problem in electricity networks accounting for the disruption, poor power quality and affecting the cost and productivity of power utilities and the consumers. One of the most exciting and potentially profitable recent developments is increasing usage of artificial intelligence techniques. The intention of this paper is to give an overview of using neural network (NN) techniques in power systems. The number of ANN applications has increased drastically in the last few years, fired by both theoretical and application successes in a variety of disciplines including power system. In case of Micro Grid, without control strategy the system would be pushed back leading system towards instability can be avoided implementing ANN. Micro grid advantages can be cited as follows: The need for additional suppliers felt due to the rapid growth of load and fossil fuels reduction. Establishing new power generating sources will reduce environmental pollution and global warming. Distributed generation (DG) sources make it easy to combined heat and power (CHP) which increases its efficiency by reducing losses. The resources are suitable for consumers with low capacity. DG Resource, can back up and thus improves power quality and network reliability due to both possible performances, Islanding and Grid Connected. Also The artificial neural network used in short-time load forecasting can grasp interior rule in factors and complete complex mathematic mapping. Therefore, it is worldwide applied effectively for power system short-term load forecastin
EFFICIENCYIMPROVEMENT OF PELTON WHEEL ANDCROSS-FLOW TURBINES IN MICRO-HYDRO POWER PLANTS: CASE STUDY
Loice Gudukeya, Ignatio Madanhire,
This research study investigated hydro power plant efficiency with view to improve on the power output while keeping the overall project cost per kilowatt produced within acceptable range. It reviews the commonly used Pelton and Cross-flow turbines which are employed in the region for such small plants. Turbine parameters such as surface texture, material used and fabrication processes are dealt with the view to increase the efficiency by 20 to 25 percent for the micro hydro-power plants.
INTEGRATED BLOCK BASED METHOD USES UNIQUENESS MATRIX FOR EFFECTIVE WATERMARKING
Rosline Nesa kumara. Dr. Maruthuperumal.S
The present paper extends the concepts of Torus Automorphism (TA) and Arnold Cat Map (ACM). The proposed Integrated Block based method uses Uniqueness Matrix (IBUM) for effective watermarking and a scrambled watermark is embedded robustly and imperceptibly. The proposed IBUM method efficiently made use of the earlier concepts TA and ACM effectively. TA disarranges the original image equally and randomly by maintaining high security over other methods. TA is a kinds of a dynamic system. After applying TA, the disarranged image is divided into 4×4 non overlapped blocks. On this, ACM is applied to shuffle the blocks. Then each 4×4 block is further divided into four 2×2 sub blocks and maintains hierarchical relationship. Each 2×2 sub block of the image represents a square matrix. Using Uniqueness Matrix (UM) the binary watermark is embedded in to the 2×2 sub blocks. This made the proposed system more secure and robust against several attacks. Based on TA and ACM the image is divided in to sub blocks with hierarchical nature. The characteristics of block based TA and ACM made the proposed system an excellent system, robust to many attacks, made complex in nature and impossible to predict over a long time. The proposed IBUM is tested with various attacks and compared with various existing image authentication and copyright protection methods. The comparisons and results indicate the efficacy of the proposed method over the existing methods.
IMPROVISED RECORD MATCHING SCHEME USING UNSUPERVISED LEARNING FROM WEB DATABASES
G.V.Rajya Lakshmi , Ch.Suhasini
In data mining, Duplicate detection is an important step in data integration and most state-of-the-art methods. Existing, record linkage techniques, SVM, OSVM, PEBL, Christen are record matching methods. According to the Web database scenario, records to match are greatly query-dependent, a pertained approach is not applicable as the set of records in each query’s results is a biased subset of the full data set. Even if applicable for each new query, depending on the results returned, the field weights should probably change too, which makes supervised-learning based methods even less applicable. In this paper, an unsupervised, online approach, UDD, was proposed for detecting duplicates over the query results of multiple Web databases along with similarity metric called simstring. For String Similarity calculation UDD uses any kind of similarity calculation method. Here,Simstring is a similarity or relevance metric which is used for efficient web mining is used. Two classifiers, WCSS and SVM, are used cooperatively in the convergence step of record matching to identify the duplicate pairs from all potential duplicate pairs iteratively.
: Ms. Néeraj Rathore prof. Umesh Barahdiya ,prof.pawan jain
PERFORMANCE EVALUATION OF MULTIPATHAODV ROUTING PROTOCOL
: Ms. Néeraj Rathore prof. Umesh Barahdiya ,prof.pawan jain
A mobile ad-hoc network is a Temporary wireless network that can be formed without the need for any pre-existing infrastructure in which each node can act as a router. One of the main challenges of mobile ad-hoc network (MANET) Is the design of robust routing algorithms that adapt to the frequently and randomly changing network topology. A variety of routing protocol has been proposed and several of them has been extensively simulated or implemented as well. In this paper, compare and evaluate the performance of two types of on-demand Reactive routing protocol for MANET.-Ad-hoc On demand Distance Vector (AODV) Routing Protocol. Which is unipath and multipath ad-hoc On Demand Distance Vector (MAODV) Routing Protocol. this paper investigates all these reactive routing protocols corresponding to Packet delivery fraction (PDF), Packet loss, Number of packet dropped, Average end-to-end delay. The NS-2 Simulation results showed that AODV has Always low compare to MAODV In both statics and dynamic network for each set of connection. All these case MAODV is a better efficiency analyzed varying to pause time, but worst in case of end-to-end delay
: COMPARATATIVE ANALYSIS OF CLOUD BACKUP IN ENTERPRISE AND SMALL MEDIUM BUSINESS
Jain Shikha, ,Chauhan Neeru,
Cloud computing users are growing at a rapid rate. The user data is loaded into the cloud. Therefore, the critical data protection is an important issue for any organization regardless of its size. Even though the organizations backup their data manually on a regular basis but the risks of a disaster can’t be avoided. The disasters can be natural or manmade which may lead to sudden and unrecoverable loss of data. This paper discuses the need of cloud backup and provides the detailed insight of the cloud backup solutions employed in the enterprise and small - medium business. In this paper, the technical analysis of the backup solutions is also done using certain parameters like technical support, technical help services etc.
Multi-hop wireless mesh networks (WMNs) experience frequent link failures caused by channel interference, dynamic obstacles, and/or applications’ bandwidth demands. These failures cause severe performance degradation in WMNs or require expensive manual network management for their real-time recovery. This paper presents an autonomous network reconfiguration system (ARS) that enables a multi-radio WMN to autonomously recover from local link failures to preserve network performance using a simplified approach. By using channel and radio diversities in WMNs, ARS generates necessary changes in local radio and channel assignments in order to recover from failures. Next, based on the thus-generated configuration changes, the system co-operatively reconfigures network settings among local mesh routers. The performance of ARS has been tested in a simulation platform (NS2) and comparison analysis is also done with the existing AODV protocol. An Enhanced ARS mechanism which suffers lesser delay than ARS mechanism is proposed and tested in a simulation platform
Surojit Sarkar, Satyajit Samaddar Dr.Pradip Kumar Saha Dr.Gautam Kumar Panda
MINIMIZING AIR GAP LENGTH AND LOSSES FOR OPTIMAL DESIGNOF THREE PHASE INDUCTION MOTOR BY GENETIC ALGORITHM
Surojit Sarkar, Satyajit Samaddar Dr.Pradip Kumar Saha Dr.Gautam Kumar Panda
A Design method for the optimization of three-phase Induction Motor has been presented in this paper. The optimal design has been compared with a normal design having the same ratings. The method for optimization selected here is Genetic Algorithm(GA). Four objective functions such as Air-Gap Length(Lg), Stator Copper Loss(SCL), Rotor Copper Loss(RCL), Stator Iron Loss(SIL) are considered here. The GA method is very useful to optimize the motor performance. There are a number of non-linear equations which reflects the motor performance over here. Matlab is a powerful software used here for this NLP technique optimization.
ANALYSIS OF CLUSTER BASED ROUTING IN WIRELESS SENSOR NETWORKS
K.Sundara Velrani,
The limited resources of the sensor nodes, designing energy-efficient routing mechanism to prolong the overall network lifetime between one of the most important technologies in wireless sensor networks(WSN). As an active branch of routing technology, cluster-based routing protocols have proven to be effective in network topology management, energy minimization, data aggregation and so on. This paper present a survey of state-of-the art routing techniques in WSNs. First outline the clustering architecture in WSNs, and classify the proposed approaches based on their objectives and design principles. Furthermore highlight the challenges in clustering WSNs, including rotating the role of cluster heads, optimization of cluster size and communication mode, followed by a comprehensive survey of routing techniques. Finally the paper concludes with possible future research areas.
Yoshit V. Gidh Mahesh S. Latey, Arpita roy, Kunal Shah, Savita Ingle
BRAILLE CALCULATOR
Yoshit V. Gidh Mahesh S. Latey, Arpita roy, Kunal Shah, Savita Ingle
“A thorough grounding in mathematics enhances educational and occupational opportunities for all people, whether sighted or visually impaired. In day-to-day routines, a practical understanding of mathematics allows a person to function more successfully and independently.” Access to, and doing mathematics, is one of the biggest obstacles for blind students in school and at the university. Our Braille Calculator will present new approaches to offering blind students better access to math, to provide new tools for doing math. In this report, the basic problems and solutions to the problem are discussed as a means of laying the groundwork for our Braille Calculator. Many aspects and concepts of mathematics are visual and spatial in nature. Students who are blind or visually impaired, and their teachers, now have standards which are closely aligned with those used for sighted students. Braille mathematics standards are essential to ensure that functionally blind students become literate in mathematics. However for complex engineering and statistical calculations even sighted students have to depend on Calculator. So we came up with an idea of Braille Calculator.
K. Semmangaiselv, T.Vamsidhar ,KothaHariChandana B. Krishna Priya*and E. Nalina,
AN EFFECTIVE SECURE ENVIRONMENT USING GRAPHICAL PASSWORD AUTHENTICATION SCHEME
K. Semmangaiselv, T.Vamsidhar ,KothaHariChandana B. Krishna Priya*and E. Nalina,
Authentication, authorization and auditing are the most important issues of security on data communication. In particular, authentication is the life of every individual essential closest friend. The user authentication security is dependent on the strength of user password. A secure password is usually random, strange, very long and difficult to remember. For most users, remember these irregular passwords are very difficult. To easily remember and security are two sides of one coin. In this paper, we propose a new graphical password authentication protocol to solve this problem. Graphical password authentication technology is the use of click on the image to replace input some characters. The graphical user interface can help user easy to create and remember their secure passwords. However, in the graphical password system based on images can provide an alternative password, but too many images will be a large database to store issue. All the information can be steganography to achieve our scheme to solve the problem of database storage. Furthermore, tabular steganography technique can achieve our scheme to solve the information eavesdropping problem during data transmission. Our modified graphical password system can help user easily and friendly to memorize their password and without loss of any security of authentication. User’s chosen input will be hidden into image using steganography technology, and will be transferred to server security without any hacker problem. And then, our authentication server only needs to store only a secret key for decryption instead of large password database.
In today’s era database plays an important role in every field like computer science, business, administration, medical, e-education etc. Due to this probability of database tampering is increased. So it is main responsibility of database developer to think about database security and try to detect tampering in database. In order to do this various database forensic analysis techniques are available. In this paper we are presenting overview of two of them. First is one way hashed key algorithm and second is tiled bitmap algorithm. Tampering of a database can be detected through the use of cryptographically-strong hash functions. Subsequently-applied forensic analysis algorithms can help determine when, what, and perhaps ultimately who and why. This paper presents a novel forensic analysis algorithm, the Tiled Bitmap Algorithm, which is more efficient than prior forensic analysis algorithms. It introduces the notion of a candidate set (all possible locations of detected tampering(s)) and provides a complete characterization of the candidate set and its cardinality.
STUDY OF MAINTAINING CONFIDENTIALITY DURING CHANGE OF INFORMATION
Mradula singh, Rajesh Kumar Chakrawart,
In this modern era, collection of information and its maintenance is a very tough job. Whenever information is gathered for some important work, there arises a need for confidentiality. People ignore some basic points which should be kept in mind while data is collected, executed and exchanged. These points are mentioned in this paper and if taken in consideration they can help you to maintain privacy of your data.
IMPROVED PARTITION CLUSTERING ALGORITHM (K-MEANS) BASED ON GENETICS (USING SINGLE CROSSOVER)
Param Deep Singh, Mrs. Nidhi Jian
While K-means is one of the most well known methods to partition data set into clusters, it still has a problem when clusters are of different size and different density. K-means converges to one of many local minima. Many methods have been proposed to overcome these limitations of K-means, but most of these methods do not overcome the limitation of both different density and size in the same time. The previous methods success to overcome one of them while fails with the others. In this paper we have used genetic algorithm with k-means to improve its efficiency.
: A NOVEL APPROACH TO DETECT THE SHORTEST PATH FOR SECURE DATA AGGREGATION USING FUZZY LOGIC IN WIRELESS SENSOR NETWORKS
: A.BabuKaruppiah, S.Kannadhasan
Wireless Sensor Networks have numerous nodes with limited energy in a particular area. It is one of the major issues is increasing the network life time. Secure data aggregation is a challenging task in Wireless Sensor Network. This issue needs to be overcome using efficient technique. An energy efficient scheme needs to be proposed to detect the shortest path for data transmission using fuzzy logic. The Sensor Nodes death frustrates and the problem gets aggravated if the cluster node fails. When a cluster node fails because of energy depletion an alternative cluster needs to be chosen for that particular region. In periodical time each sensor node in the cluster should possess the next cluster head re-election based on energy to avoid node failure. In this paper a novel technique is proposed using Fuzzy to find the shortest path for data aggregation based data transmitted technique It is shown that the proposed technique has improved the throughput with reduced packed drop and also less energy consumption in these networks. Our Technique is evaluated through NS2 Network Simulator.
AN ENERGY EFFICIENT WORMHOLE DETECTION TECHNIQUE BY TRAFFIC ANALYSIS IN WIRELESS SENSOR NETWORKS
A.BabuKaruppiah, G.Sri Vidhya, S.Rajaram
Wireless Sensor Networks consists of large number of sensor nodes meant to collect relevant information about sensing the network. It gains low cost and low power to send a data. In WSN, there are various attacks happening against security threats. Upon this, ‘Wormhole Attack’ is the fatal attack to abolish the network performance in the network layer. Wormhole attack creates a tunnel inside the network or between networks and thereby records packets from one end and replays to other end of the network. Upon many passive attacks, Wormhole Attack is problematic to detect in the network. And in WSN, power consumption plays a vital role.The existing algorithms use probe messages and nonce information to check the validity of the node that consumes lot of energy for detection of wormhole attack. In this paper, a simple novel technique is proposed to detect the malicious wormhole node. The proposed methodology, to detect a wormhole considers the sudden change in traffic in each node as the metric. This is accomplished by setting counter values in sensor nodes.In this paper, wormhole attack is noticed by improving power consumption for each and every sensor node and it is well proven that power disbursed is less than other existing approaches. Main advantage is easy to find wormhole using simple methodology and external hardware is not necessary.
is paper illustrate about cloud computing. Cloud computingis the use ofcomputingresources (hardware and software) that are delivered as a service over anetworks (typically theInternet). The name comes from the use of acloud-shaped symbol as an abstraction for the complex infrastructure it contains in system diagrams. Cloud computing entrusts remote services with a user's data, software and computation. Cloud computing relies on sharing of resources to achieve coherence andeconomies of scalesimilar to autility(like theelectricity grid) over a network.At the foundation of cloud computing is the broader concept ofconverged infrastructureandshared services.
: A FUZZY RULE BASED MULTI-TEXTURE IMAGE SEGMENTATION USING M-BAND WAVELET TRANSFORM
A. Devi Priya1, G. Veera Senthil Kumar,
is paper proposes feature based image segmentation by combining M-band wavelet transform with fuzzy rule. M-band wavelet transform decomposes an image in to MxM channels. A different combination of these band pass sections produces various scales and orientations in frequency plane, which yields a sixteen sub-band images. The texture features are obtained by subjecting band pass section to the non-linear transformation and by computing the measure of energy in a window around each pixel for the filtered images. Fuzzy rule is a key tool for expressing our piece of knowledge. Fuzzy rule is then constructed for the texture features. Performance of the proposed method is analysed using deviation error, and found that the algorithm produces good segmentation results by generating Fuzzy rules for M-band wavelet derived features
: FEATURE EXTRACTION AND CLASSIFICATION OF HIGH RESOLUTION SATELLITE IMAGES USING GLCM AND BACK PROPAGATION TECHNIQUE
Gowri Ariputhiran, S. Gandhimathi Usha
Remote sensing data provides much essential and critical information for monitoring many applications such as image fusion, change detection and land cover classification. This paper proposed about the classification and extraction of spatial features in urban areas for high resolution multispectral satellite image. Spectral information is the foundation of remotely sensed image classification. Initially, Preprocessing is done for multispectral satellite image using Gaussian filter. Then the features are extracted from the filtered image using Gray Level Co-occurrence Matrix (GLCM).Finally, Extracted features are classified using Back Propagation Artificial Neural Network (BPANN) and the performance is analyzed based on its accuracy, error rate and sensitivity.
IMPULSE NOISE REDUCTION USING COMBINED FUZZY AND NON LOCAL MEANS APPROACH
B.L.Benisha Bennet, P.Karthikeyan, Dr.S.Vasuki
Impulse noise reduction is an active area of research in image processing. In this paper we propose a two phase scheme to detect and correct the impulse noise. In the first phase a fuzzy detection is being used, to identify pixels that are likely to be contaminated by impulse noise. In the second phase the noisy corrupted image is being subjected to a non local means filter which efficiently filter out the noisy pixels. Extensive experiments are performed to show that the proposed technique gives high performance compared to other models particularly with high noise densities. The experimental result is based on well known global as well as local quantitative measure like peak-signal-to-noise-ratio (PSNR).
: MIN-HEAP BASED ENERGY EFFICIENT LOAD BALANCED CLUSTERING TECHNIQUE FOR WIRELESS SENSOR NETWORK
A.Babu Karuppiah, P.Suresh,
Clustering is one of the key mechanisms for load balancing. Clustering Algorithm is an efficient technique to improve life time and scalability of a Wireless Sensor Network. In this paper, an Energy Efficient Load Balanced Clustering Technique is proposed which is used to find energy efficiency as well as load balancing. Energy Efficient Load Balanced Clustering Technique is a min heap based Clustering algorithm. Efficiency of WSNs is measured by the total distance between nodes to the base station and data amount that has been transferred. Cluster–Head which is totally responsible for the creating cluster and cluster nodes may affect the performance of the cluster. The result show that the proposed algorithm is efficient in terms of load balancing, energy efficiency, and the number of sensor nodes that die during the network period.
Anomaly detection has traditionally dealt with record or transaction type data sets. But in many real domains, data naturally occurs as sequences, and therefore the desire of studying anomaly detection techniques in sequential data sets. The problem of detecting anomalies in sequence data sets is related to but different from the traditional anomaly detection problem, because the nature of data and anomalies are different than those found in record data sets. While there are many surveys and comparative evaluations for traditional anomaly detection, similar studies are not done for sequence anomaly detection. We investigate a broad spectrum of anomaly detection techniques for symbolic sequences, proposed in diverse application domains. Our hypothesis is that symbolic sequences from different domains have distinct characteristics in terms of the nature of sequences as well as the nature of anomalies which makes it important to investigate how different techniques behave for different types of sequence data. Such a study is critical to understand the relative strengths and weaknesses of different techniques. Our paper is one such attempt where we have comparatively evaluated 7 anomaly detection techniques on 10 public data sets, collected from three diverse application domains. To gain further understanding in the performance of the techniques, we present a novel way to generate sequence data with desired characteristics. The results on the artificially generated data sets help us in experimentally verifying our hypothesis regarding different techniques.
