Cloud computing compromises of 3 important terminologies in the world of computing – infrastructure, storage and application. Cloud computing is replacing the usual network architecture with its performance and availability. The drawback that is noted with cloud computing is ‘Security’. The security issues in cloud haven’t got a permanent solution so far. In this paper, we discuss a solution to eavesdropping and man in middle attack by introducing message authentication code (MAC) method. The cloud architecture used here is P2P in nature, ie no master server exist. The peer to peer approach enables the fault tolerance property when a server failure occurs.
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Wireless communication systems of next generation are featured with heterogeneity where multiple wireless technologies exist together. At the intersection of coverage areas of these multiple technologies, receiver can access multiple interfaces simultaneously for better performance and prompts for bandwidth aggregation. This paper proposes to design and implement a logical link for attaining bandwidth aggregation through concurrent multi path transfer of data with the aim of achieving increased transmission throughput as well as resource sharing. In the proposed work, a multipath environment is set up where a proxy server performs forwarding of data packets along concurrent multi paths. Reordering of the
received data packets is performed at client before delivering to the application.
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This paper presents hyperspectral image classification using genetic algorithm after visualization using image fusion technique. Hyperspectral remote sensors collect image data for a large number of narrow, adjacent spectral bands. Every pixel in hyperspectralimage involves a continuous spectrum that is used to classify theobjects with great detail and precision. In this paper, first 2-DEmpirical mode decomposition method is used to remove anynoisy components in each band of the hyperspectral data. Afterfiltering, band selection method is performed to select specificbands from the hyperspectral data, in-order to reduce redundancybetween bands and to eliminate bands with less information. After band selection, image fusion is performed on the selected hyperspectral bands to selectively merge the maximum possible features from the images to form a single image. This fused image is classified using genetic algorithm. Two different indices, such as K-means Index (KMI) and Jm measure are used as objective functions. This method increases classification accuracy of hyperspectral image.
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Wireless Sensor Networks are known for the sensor nodes sensing the data and disseminate the data into its network. The disseminated data finally reach the sink node. The huge volume of data needs a real time handling at the station where Sink node is installed. The paper shows the use of a middleware software required for handling and storing the data into a predefined format. This paper also shows how to show the data in real-time using its presentation in form of instantaneous graphs. A warning system is also presented in the paper if the the value of data goes above or below threshold level.
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A large portion of the business new companies and set up business areas approach outsider showcasing operators to broaden their organizations. In this situation ordinarily advertising specialists or agents can utilize alternate entrepreneur’s urgent data for their unlawful increases. So a central issue emerges for the reliability of the dealers in these kind business game plans. So a need of an unequivocally coupled business element framework is required in disseminated worldview to limit the business relationship in the middle of proprietors and intermediaries. Numerous frameworks are existed in the business sector where they manage maybe a couple parts of the security issues in the framework. So a proposed framework put advances a thought of giving 3600 security to the merchant – less distributer and supporter framework utilizing solid two level key era framework which is fueled by opposite circle figure cryptographic system. Notwithstanding our past work [1], this paper contributes (1) utilization of profile based key era framework (2) utilization of time based key era framework (3) utilization of two level key era brushing 1 and 2 (4) Powerful encryption method utilizing reverse circle figure encryption (5)
fine grained key administration framework (6 ) Enriched occasion appropriation utilizing Gaussian model. This paper shows a way to deal with give security in the distribute/subscribe framework by utilizing the certifications of the client and it utilizes representative less system for the scattering of the message. Here we are giving character based encryption [1] to the security reason and message can be decoded by just those endorsers who are having accreditations with the message. In this framework clients are partitioned into two classes .The client can be Publisher of the framework (who is giving data to the framework as messages or occasions) and second is endorser (who is devouring data gave by the distributer as indicated by their memberships). This paper presents instrument for giving validation, Confidentiality and Scalability.
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Uncompressed multimedia (graphics, audio and video) data needs substantial storage capacity and transmission bandwidth. Although quick progress in mass-storage density, processor speeds, and digital contact arrangement presentation, demand for data storage capacity and data-transmission bandwidth endures to outstrip the skills of obtainable technologies. The present development of data intensive multimedia-based web requests has not merely
upheld the demand for extra effectual methods to storage and contact technology. Apart from the continuing knowledge on picture compression embodied by sequence of JPEG, MPEG and H.26x standards, new knowledge such as neural webs and genetic algorithms are being industrialized to discover the upcoming of picture coding. Prosperous requests of neural webs to frank propagation algorithm have nowadays come to be well instituted and supplementary aspects of neural web involvement in this technology. In this work a noval picture compression method has been grasped out to find and effectual multi-layered neural web and suitable and tested employing MATLAB for a examination case of image.
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This paper provides highly reliable security mechanism in onlineprocess. This paper is fully concentrating on User Authentication.If we are allowing authenticated users only to access the processmeans most of the security problem will be solved .This paperincreases the amount of authentication checking process .This paper introduces authentication verification process in two levels (L1,L2). In the authentication Level 1, it uses Imagen Values. Users are generating these Imagen key values by selecting hotspot positions on images. Authentication Level 2 uses two Alpha Numeric codes namely, TCG, ITC. These codes are highly secured and reliable because, these code values are created using users direct interference. On the success of authentication Level1 only ITC will be generated by using TCG and with the user’s Biometrische key values. This ITC is valid only for particular time span. Using ITC Authentication Level 2 is verified.
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In Local Area Network like hub, Switches, Bridges different devices are using to connect the network. The problems with the Hub are to broadcast all information to all computers. The bridge has less number of ports. The Switch overcomes this issue by using MAC Table and it also has large number of ports. We anticipated that the switch can provide about 90 percent security features by which we can secure our environment but the percent get reduced to 10 percent or less. We have a lot of vulnerabilities which we
need to overcome to secure our environment.
The various Organizations are dealing with different issues of network vulnerabilitites. With a significant percentage of network attacks originating inside the corporate firewall, exploring this soft underbelly of data networking is critical for any secure network design. So, It is important to find out different vulnerabilities of network and eliminate upto acceptable level.
Security issues are addressed include ARP spoofing, MAC flooding, VLAN hopping, DHCP attacks, and Spanning Tree Protocol concerns. Common myths about Ethernet switch security are confirmed or debunked, and specific security lockdown recommendations are given. Attack mitigation options include the Port Security, DHCP snooping, Dynamic ARP Inspection (DAI) functionality and following the VLAN Security recommendations.
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Cloud data locations square measure horrendously alluring for the preparing of enormous scale applications inferable from there to a great degree ascendible and offered framework. Data as a Service (DBaaS) model is utilized to oversee databases in cloud setting. Secure DBaaS standard gives data classification to Cloud storage. Secure DBaaS is expected to allow different and independent buyers to append to the cloud while not middle of the
road server. Documents, data structures and data square measure scrambled before exchange to the cloud. Various cryptography systems square measure won’t to change over plain content into scrambled data. Table names and their section names likewise are encoded inside of the cloud data security topic. The framework bolsters topographically disseminated buyers to join on to A scrambled cloud data. amid this paper we tend to quadrangular measure proposing new plan that incorporate Cloud storage administration with data protection and have a component of flogging co-happening operations on scrambled data and together with the geologically disseminated buyers to connect on to these cloud data that is encoded and that they conjointly given to execute their operations over the cloud data. This configuration takes out the merchants (Intermediate intermediaries) it confines the quantifiability, versatility, availability. High delicate data square measure encoded by RSA cryptography and normal data square
measure scrambled abuse AES system so overhead on the system will be decreased.ecurity, DHCP snooping, Dynamic ARP Inspection (DAI) functionality and following the VLAN Security recommendations.
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Past frameworks for regular dialect questions over complex connected datasets require the client to enter a complete and all around shaped question, and present the answers as crude arrangements of substances. Utilizing a component based punctuation with a full formal semantics, we have built up a framework that can bolster rich autosuggest, and to convey progressively created examination for every outcome that it returns. Question Answering (QA) frameworks are turning into the rousing model for the eventual fate of internet searchers. While, as of late, datasets fundamental QA frameworks have been elevated from unstructured datasets to organized datasets with
semantically exceedingly improved metadata, question noting frameworks are as yet confronting genuine difficulties and are along these lines not living up to clients’ desires. This paper gives a comprehensive knowledge of difficulties known so far for building QA frameworks, with an exceptional spotlight on utilizing organized knowledge (i.e. learning diagrams). It in this way helps scientists to effectively spot holes to load with their future exploration motivation.
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For creating effective programming, testing is a critical part. In programming testing, giving info, executes it and check expected yield. Numerous strategies which naturally deliver inputs have been proposed throughout the years, and today can create test suites with high code scope. In programming testing a typical situation is that test information are produced and an analyzer physically includes test cases. It is a troublesome errand to create
test cases physically yet it is critical to deliver little illustrative test sets and this representativeness is normally measured utilizing code scope. Be that as it may, there is a central issue with the regular methodology of focusing on one scope objective at once. Scope objectives are not free, not similarly troublesome, and some
of the time infeasible—the aftereffect of test era is in this manner subject to the request of scope objectives and what number of them are achievable. For taking care of these issues, propose a novel worldview which is era of entire test suite in light of pursuit based testing. Rather than developing every experiment independently, advance all the experiments in a test suite in the meantime. Toward the end, the best coming about test suite is minimized.
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Waqf is the permanent dedication by a person professing Islam, of movable or immovable properties for any purpose recognized by the Islamic law as pious, religious or charitable. Waqf Management System of India is an integrated online workflow based Information System for the management of Waqf Properties
under the supervision of the various State/UT Waqf Boards in pursuance of the central Wakf Act, 1995 and Waqf (Amendments) Act, 2013. Before computerization, the Waqf properties were needed a proper study and documentations. A large number of Waqf properties were either unidentified or unregistered. Hence,
the Waqf properties were difficult to manage. Waqf properties are usually managed by Managers/Trustees (known as Mutawallis) since many-many years but current computerization process has improved the management method and also becomes more transparent.
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CAPTCHA system protects against automated scripts (or bots) by generating tests that humans can pass but computer programs cannot. Recent advancements in optical character recognition (OCR) techniques have led to successful attacks on text-based CAPTCHAs. To counter it, the design of these CAPTCHAs has become more complex, making it more challenging for humans to solve them successfully. Hence a new CAPTCHA system is proposed which works on the principle of facial expression detection. It exploits a real-time interaction from the user through front camera of laptop to get an input image. If the desired expression matches with input expression of the user, the CAPCTHA system gets unlocked. This makes the system more robust to bot attacks, also creating the user experience better due to its click only interface and language-independency as no text is involved.
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Road safety is an all-time global concern. Everyday a large number of human lives are lost due to accidents and delay in calling the rescue services. Also it is difficult to know about the occurrence of an accident and to obtain its location. Over the past years improvements have been made and with the advent of smart phones, it is now possible to get the location of accidents using GPS. Further form filling formalities and FIR filing is required in case of accidental events and in the case of fall. This causes delay in providing the victim with immediate medical help. Even though there are new enhancements in the area of accident and/or fall detection there is a need to focus on the integration part of all the above mentioned services for minimizing the delay in providing immediate help to the victim. This paper describes an efficient system which takes sensory input from an android application and notifies the emergency service providers like hospitals and police stations about such events immediately using the concept of Internet of Things (IoT).
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Image classification is a standout amongst the most difficult issues in computer research. The goal is to outline computerized image into one or a few marks. The information for preparing such complex models will comprise of preparing images having a place with various classes. The target will be to comprehend the different strategies to prepare the support vector machine to accomplish condition of the remote detecting images characterization demonstrations. We present profound taking in, a developing field of machine learning that goes for consequently learning highlight progressions and which has demonstrated late guarantees in vast scale computer research applications. The key knowledge is that intricate tactile inputs, for example, images with elements can be scholarly in an information driven way. Learning happens a every layer of the chain of command, utilizing a lot of information and restricting the tedious and problematic element designing stride of numerous customary computer frameworks. There are a few approaches to learn such components (in an administered, unsupervised and semi-regulated setting relying upon the measure of marked information), and there are a few models that can be utilized (probabilistic graphical models with progressive systems of inactive variables and various types of convolution neural systems). In this paper, we will clarify the fundamental thoughts behind these techniques, their qualities and shortcomings, and how they can be specific to vision applications.Full Paper

Object detection is a computer technology related to computer vision and image processing that deals with detecting instances of semantic objects of a certain class in digital images and videos. An attempt is made in this study to detect and extract objects in an image implemented on android platform. Color images are converted to binary images using the thresholding technique. Morphological opening and closing filters are used in sequence for object detection. Contour based learning techniques are adopted for drawing contours of the objects detected. In the process objects are extracted and stored in an array for further analysis.Full Paper

Image recognition has turned into a vital and imperative part in today’s specialized world. The different application world situations offer ascent to a key system of day by day life visual item acknowledgment. On-Premise Signs (OPSs), a prevalent type of business promoting for the most part as enlightening signage are broadly utilized as a part of our living. Content has been a viable apparatus for broadcasting data and trading thoughts. The acknowledgment of content from OPS helps a considerable measure for separating the required points of interest right then and there in regards to the OPS. For tending to the issue of genuine OPS learning and acknowledgment a productive methodology has been suggested that give the complete insights with respect to the classification to which business sort OPS have a place and geo-location subtle elements of the OPS image that has been caught by the brilliant cell phone in any point and under different conditions. This probabilistic structure will remove the key elements descriptors utilized for the acknowledgment and extraction of content. The content from OPS is obtained by utilizing content scene text recognition and extraction methods. This removed content is further handled for the characterization of the class of OPS by performing reasonable correlations with the OPS datasets. Alongside characterization it additionally gives the geo location of the image with full precision. It exploits the distributional data of each visual component as a dependable determination rule for building discriminative OPS
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The online social network, with 20 million installs per day, thirdparty applications are a major reason for the popularity of and dependence on Facebook. Unfortunately, hackers have realized the potential of using applications to spread malware and spam. The problem is more significant, as we have to be at least 13% of the applications in our collection are malicious. So far, the research community has focused on detecting malicious messages and campaigns. In this paper, we ask the question: given the Facebook application, we can determine whether it is malicious? Our key contribution to the development of a malt Facebook Rigorous application of evaluator-probably the first tool aimed at detecting malicious applications on Facebook. For the development of Frappe, we use the information gathered by observing the behavior of posting 111k Facebook application saw across 2.2 million users on Facebook. First, identify a set of functions that help us to distinguish Malicious applications from benign. For example, we find that the Malicious applications often share names with other applications, and they usually look for fewer licenses than benign applications. Secondly, using these features, we show that
smoothie can detect Malicious applications with 99.5% accuracy, with no false positives and low false negative rate (4.1%). Finally, we explore the ecosystem of malicious Facebook applications and identify the mechanisms that these applications use for propaganda. Interestingly, we find that many applications in connivance and support each other; in our collection, we find the 1584 application allows viral propagation 3,723 other applications through your messages. In the long term, we see a smoothie as a step towards the creation of an independent watchdog to assess the application and ranking, so to warn Facebook users before installing applications.
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In this paper we propose to apply data mining techniques to Improve Student’s Overall Performance in Exams. The focus is on the educational Data Mining and Classification Techniques along with Attribute Evaluator Techniques. The classification algorithms Naïve Bayes, J48, Random forest, Multi-Layer Perceptron, are grouped with analysis was experimented using WEKA tool. The Evaluators are Chi Squared Attribute Eval, Filtered Attribute Eval, Gain Ratio Attribute Eval, Info Gain Attribute Eval, Relief Attribute Eval, One R Attribute Eval and Symmetrical Uncert Attribute Eval methods are used. Combination of such techniques helps us to predict Student’s performance accurately and quickly.
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Keyword query allows ordinary users to search large amounts of data, the ambiguity of keyword query makes it difficult to
respond effectively keyword queries, especially for queries short and vague key words. To resolve this problem a challenge, in this paper an approach that automatically diversify ca XML search keyword based on their different contexts in the XML data is proposed. Given a query keyword small and vague and XML data to be searched, first it is derived from the keyword search query candidates by a simple model feature selection. And then, we design a keyword search diversified XML model effective cation of measuring the quality of each candidate. After that, two efficient algorithms are proposed to calculate incrementally quelled top-k query candidates as diverse search intentions. Two criteria are targeted: the selected candidate’s consultation are most relevant to the query given before they have to cover the maximum number of different results. At last, a full assessment of the sets of real and synthetic data demonstrates the effectiveness of our model of diversification and efficiency of proposed algorithms.
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Normal human beings can communicate with each other with the help of various different languages, however, the people who can’t speak have different sign languages to communicate with others. But a major setback of sign language is that only people thosewho know sign language can communicate with them. They are not able to communicate with others. In our paper we proposed a system which will be able to convert the sign language into words or sentences or audio output.
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The vast advancements of upcoming new computing, communication and entertainment applications on wireless handsets, power demands are increasing rapidly day by day. Power consumption is the limiting factor for the functionality offered by portable devices that operate on batteries hence Power Saving Management (PSM) Mechanism has been widely used in WiFi devices for power saving. Each of this access points and clients has ZigBee (802.15.4) and a WiFi (802.11) interface by which regular and on demand wakeups are scheduled to minimize overall energy consumption. The proposal is to use a ZigBee assisted PSM (ZPSM) Mechanism for mobile devices to study the nature of delay and energy parameter. The sensor data is sent to each of the client through wifi or through zigbee module and received by the clients. It is observed that communication through wifi or zigbee provides more battery life than by using 3G in PSM Mechanism. This research elevates the behavior of the delay, time and data consumption with respect to battery life.
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Research on OCR of Hindi script is very difficult and challenging task due to its complex structural attributes. The major difficulty with handwritten text is the variability of writing styles, both between different writers and between separate examples from the same writer overtime. Handwritten character/Numeral recognition has received large attention in academics and production fields. This paper will act as guide and update for the readers, working in the hindi Optical Character Recognition area. An overview of various statistical and structural features used for recognition based on the various research papers is presented and reviewed.
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Most of the routing protocols focus on obtaining a workable route without considering network traffic condition for a mobile ad-hoc network (MANETs). Therefore, the quality of service (QoS) is not easily achieved by the real time or multimedia applications. Providing quality-of-service (QoS) in wireless ad-hoc networks is an intrinsically complex task due to node mobility, distributed channel access, and fading radio signal effects. To find a QoS constrained route from source to destination, it should be able to effectively determine the available resources throughout the route. The routing protocol is the most integral part of any type of QoS provisioning. In this paper, modification has been proposed in the existing MANET protocols to get the information about total path bandwidth for delay analysis. It uses modified technique for bandwidth estimation and for route maintenance. Resultof simulationshows that there is much improvement in Packet delivery ratio, overheads, delaysignificantly reduced and without any impact on overall end-to-end throughput.
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Gene expression data very often contain missing values. In regards to this, effective missing value estimation methods are needful though many algorithms for gene expression data analysis require a complete matrix of gene array values. In this paper, local least square imputation and weighted k-nearest neighbors(KNN) imputation are proposed to estimate missing values in the gene expression data. The proposed local least squares(LLS) imputation method gives a target gene which has missing values through a linear combination of very similar genes. The similar genes are selected by k-nearest neighbors or k coherent genes that have bigger values of Pearson Correlation coefficients. In our experiments, the proposed KNN imputation and LLS imputation method applied in e-coli bacteria dataset producing the percentages of missing values in the data.
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Machine translation, communal contraption translation for signal tongues stays an alert research area. Signal speech contraption translation presents exceptional trials to the finished contraption translation process. In this report” tagging and classifier is generated for English text” system is presented. This system is design for being used in “English text to Indian sign language” translation for a particular domain. Part of speech tagging is one of the most learned task in NLP. Being a extremely vital procedure in the span, there are countless instruments and implementation models that hold out this task, obtaining extremely good accuracy above a colossal number of tongues. the scrutiny of present POStagger consequence displays the countless of the error arise from the sparseness of morpho-syntactic or lexico-symentic data. After statistical models grasp the best POS tagging benefits, eveneighth knowledge- poor linguistic data, the request of correction law in a post processing pace might rise the precision of tagging. Here a law established error correction method is counseled to find and correct errors by user described rules. Thus, growing frank grammars alongside correction laws can aid us to present a post processing of the tagged text. Later correcting POS tagging subsequent pace is to produce a parse tree. So the parser seizes the output of the pos tagger as its input, and generates the parse tree. Full Paper

Mobile ad-hoc network is self-organizing wireless network composed of different nodes communicate with each other without having established infrastructure. It generally works by broadcasting the information and used air as medium. Its nature of broadcasting and transmission medium also help attacker to disrupt network. Many kind of attack can be done on such Mobile Ad Hoc Network. The emphasis of this paper is to study wormhole attack, some detection method and different techniques to prevent network from these attack. This analysis able to provide in establishing a method to reduce the drawbacks like reliability, message overhead, delay and clock synchronization and to become more faster.
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Communication through the mobile network is need of the hour. Thus localization becomes important issue discussed in this paper. Algorithms are many which can be range free and range based. The DVHOP algorithm with random key is used to solve the localization problem. The localization is required since node when on the go will require to disseminate data then position determinism is paramount which is achieved with the help of localization. Distance could be of any range when mobile nodes are considered hence range free algorithm is considered. Security aspect of the data is paramount. Since node capture attack
is common. Ways to detect and prevent the attack in terms of Random key is suggested. The result obtained will be in terms of the localization error which is given both in terms of localization with and without Node capture attack and random key.
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The onset of an epidemic leads to a chaotic situation as there is no understanding of the pattern of spread of the disease. Hence an effective use of combination of statistical tests and visualized data can help predict patterns and trends in medical data which can save valuable time. Statistical values can help understand dependence of factors on occurrence of the disease. Whereas visual reports based on age, gender, co-morbid conditions of disease can help understand pattern of spread and also help in early control of an epidemic outbreak. If these reports could be monitored regularly during the outbreak medical aid, funding and precautionary measures can be taken accordingly focusing on adversely affected areas. A combined model of rightly chosen statistical tests and a combination of visualization reports is developed using R programming and Tableau respectively. Results and effectiveness of tests have been discussed based on implementation done on swine flu data of regions of Maharashtra, India during 2009 epidemic outbreak. Implementation and study has been done using chi square test and visuals generated by Tableau.
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Agile methods are widely employed to develop high-quality software, but theoretical analyses argue that agile methods are inadequate for security-critical projects. However, most agiledeveloped software today needs to satisfy baseline security
requirements, so that we need to focus on how to achieve this level for typical agile projects. Software grows up through its life cycle, so software development methodologies should pay special attention to security aspects of the product. This paper
addresses the major concern of security requirements of projects using an agile approach. It provides an integrated framework
developed in Java which uses a lightweight method to enhance the security features by integrating security activities from Security engineering processes without compromising the agility in the agile approach.
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