Papers by vishwajit gaikwad
Attack Detection in Cloud Virtual Environment and Prevention Using Honeypot
2018 International Conference on Inventive Research in Computing Applications (ICIRCA), 2018
Due to increase in problems like space allocation, web hosting, hardware failure which results in... more Due to increase in problems like space allocation, web hosting, hardware failure which results in the loss of data. This problem can be solved by new technologies in cloud computing. With the passing of time and the advancements in technology, the usage of cloud storage has increased tremendously which has resulted in the increase of the threats on cloud. Attackers can easily find vulnerabilities present in the system and exploit the data that it holds by using a port scanner. In such a way the DDOS (Distributed Denial of Service) attack will compromise the machine. In such type of attacks, multi-step exploitation, low frequency vulnerability scanning, compromises other machines to develop zombie systems. Lastly, the attacks that are caused by those compromised machines are the problem seen in such type of attacks. To detect and prevent an attack on the system, a network intrusion detection selection is done on them with the help of honeypots. Honeypots lure attackers away from the main system preventing it from the attack and protecting its integrity. A Nice-A agent continuously monitors the network. The VM Profillerwill update the database forsuch attacks taking place on open ports in the network. This attack type is analysed by attack analyser. After recognizing the type of attack, it gives notification to network controller and suggest the countermeasure to be taken. The attack is further directed to honeypot. A security mechanism honeypot which detects and deflects an unauthorized user trying to access the information system. Honeypot thus tracks the attacker IP and its signature attack.
1-3Student, Dept. of Computer Engineering, Terna Engineering College, Navi Mumbai, India. 4Profes... more 1-3Student, Dept. of Computer Engineering, Terna Engineering College, Navi Mumbai, India. 4Professor, Dept. of Computer Engineering, Terna Engineering College, Navi Mumbai, India. ---------------------------------------------------------------------***---------------------------------------------------------------------Abstract The field of prosthetics has showed a significant improvement over last few years, due to advancement in technologies. However, they have certain problems either with being really expensive, does not provide full motor functions, may require surgical approach or does not look like an arm. This project describes how the Brain waves can be used to control a prosthetic arm using Brain Computer Interface (BCI). The BCI system consist of Electroencephalogram (EEG) sensors placed on the headset to capture the brain waves, which will be extracted using Thinkgear library in MATLAB. The Brain signal act as command signals and transmitted to microcontroller. This comma...
Image segmentation is a very emerging and important area due to a large number of real life appli... more Image segmentation is a very emerging and important area due to a large number of real life applications. Bag-of-features (BoFs) model is the one of the most successful algorithm used for the image classification. BoF methods are based on order-less collections of quantized local image descriptors; they discard spatial information and are therefore conceptually and computationally simpler than many alternative methods.Bag-of-features algorithm is used for the feature extraction from the image. BoFs model has several advantages like,scalability,simplicity, and generality. But BoFs have some disadvantages too and some of them are Time and Accuracy of the image classification process. In this paper Bag-of-features model is extended by using spatial pooling to improve the time and accuracy of the image classification model. In proposed method first the system is trained by creating the database of the image feature for the evaluation process and then the evolution of the features is don...
International Journal for Research in Applied Science and Engineering Technology, 2021
I. INTRODUCTION Today's world has evolved a lot with respect to the aspects of digital images and... more I. INTRODUCTION Today's world has evolved a lot with respect to the aspects of digital images and their processing. In order to perform processing on images, the need of a software that will give access to the operations for image processing hassle free, wherein it is expected for a system framework to work smoothly, quickly and require less space in PC and laptops, also should not require additional software to process. Image processing involves processing or altering an existing image in a desired manner and also helps in obtaining the image within the readable format. In general, The image processing operations include implementing Color Histogram of an image, image dilation, image erosion ,image cropping, image rotation, gray scale conversion, black and white filters, color to negative and so on. This paper basically deals with the study of different frameworks for image processing. In the plugin based system framework, a program framework can be created that will help user to develop an image on a PC or a laptop and using a plug-in, given operations can be performed on the image, which can be done using Dynamic Link Library (DLL), wherein a plugin manager plays role of searching and loading the desired .dll file of processing operation which the user had specified to perform on the input image [1]. Another image framework used for image processing is the Hadoop Image Processing Framework. This is primarily a software engineering platform, with the aim of concealing Hadoop's complexity while giving users the ability to use this program to process large images without becoming Hadoop crack engineers. The ease of use of the Java-based framework and semantics will further advance the process of large-scale application and testing. This framework is an excellent tool for novice Hadoop users, image software developers and computer vision analysts, allowing for rapid development of image software that can take advantage of large data stores, rich metadata and global access to current online image resources[2]. One more framework for image processing, Marvin Framework that deals with plugins in Java. Marvin is an expandable, concise and open source image processing tool developed in Java. The main purpose of this framework is to integrate efforts from researchers, software developers and end users to improve the use of image processing systems. It is a Pure Java cross-platform image processing framework that provides features for image and image processing, multi-image processing, GUI integration, extension with plug-ins, unit text automation among other things [3]. The framework provides features such as, using pictures and captured Video frames, process multiple images, integrate plugins with Graphical User Interface (GUI), analyze the functionality of the plugin, Expand features with plugins, Automatic unit testing [4]. II. RELATED WORK Some of the recent research works related to image processing is discussed as follows: A plugin framework for image processing was developed by Prof. Shyamsundar Magar et.al., in this they developed a system Framework which was intended to help users to enhance the images on low resolution PC, even computer by employing the application plugin which is a small software to append externally with the Framework by using DLL (Dynamic Link Library) which establishes a connection between the plugin code and existing system Framework. The proposed framework in this system was mainly focused on the usefulness of the image processing which supports various image processing operations like brightness, contrast, Grayscale effects and the operations like histogram, compressions intended to work for the basic implementation stage which will mainly work on gray-scale conversion [1]. The process used in this conversion from RGB to gray-scale image was implemented by eliminating the hue and saturation information, which retained the luminance that in turn can be utilized for various applications in eliminating signal noise in the medical field, aerospace research, engineering, and computer science. They used histogram for enhancing the image brightness. A case study was presented by White et.al. It represented classification as well as clustering of a collection of billions of standard images using MapReduce[2]. The image pre-processing technique used in a sliding-window approach for object recognition was described in the case study. Certain limitations of the MapReduce model were set out by Pereira et.
Continuous Query Processing in Location Based Services
The increasing development of mobile devices and wireless technology has motivated interest in mo... more The increasing development of mobile devices and wireless technology has motivated interest in mobile services in the new era of mobile computing. The wireless technology has made people more mobile. Almost everyone in the society has Internet access on the wireless network. Recently, mobile users has been subscribed to many locations based services (LBS), such as location-based games, locationsharing social networks, advertising, road-side assistance, tourist guide, etc. This raised the innovative research in mobile computing to design novel and scalable location-based system. The location based queries (LBQ) are fundamental to LBS. The LBQ are the key to access information from the database. The location based queries can be continuous queries. The continuous queries answers depend on the movement of mobile user. Several aspects have been proposed to process continuous queries in mobile networks. When somebody would like to visit a new location, then if the information is available at the tip of figure, it’s very helpful to assist proper information. The proposed system gives the information about the current places such as Hotels, Colleges, and Schools in LBS. The people who would like to visit a city can get faster information and manage their valuable time effectively and efficiently.
International Journal of Computer Applications, 2013
Image fusion has the very wider scope in medical sciences. Medical Images are obtained form diffe... more Image fusion has the very wider scope in medical sciences. Medical Images are obtained form different type of equipments and are of different modalities, each of them carries altogether different information. Especially study of brain images and its features is of greater interest for doctors since several centuries. Now because of radiology and evolution computers made this possible to look in to head online. This posed several challenges for software engineers to produce the good quality images or stream of images. Since medical images are from different modalities, which made it difficult to produce a single image from all these images. With the help of several image processing algorithms it is now possible to fuse the images. This gave rise to another challenge for producing efficient algorithm. This paper proposes the Redundant discrete wavelet transform (RDWT) based algorithm for image fusion, and compares with the other DWT based methods. These methods are assessed on the basis of statistical measures such as entropy, mean and standard deviation. According to the assessment made, it is found that the proposed method is giving better results. The Brain atlas based images are considered as input.
Spam is an unsolicited bulk mail or junk email. Due to increased communication within shorter dur... more Spam is an unsolicited bulk mail or junk email. Due to increased communication within shorter duration and for longer distance and fastest medium email is considered .In the recent years spam became as a big problem of Internet and electronic communication. So for overcoming these problems some techniques are developed to fight with them. In this paper the overview of existing e-mail spam filtering methods are compared. In this survey paper we focus on the classification, evaluation, and comparison of traditional methods. The methods discussed are Collaborative Spam Filtering Using E-Mail Networks, Support Vector Machines and Spam Filtering with Dynamically Updated URL Statistics. The methods are compared and performance is evaluated.
Uploads
Papers by vishwajit gaikwad