Bandu B. Meshram

Bio: Bandu B. Meshram is an academic researcher from Veermata Jijabai Technological Institute. The author has contributed to research in topics: Intrusion detection system & The Internet. The author has an hindex of 13, co-authored 81 publications receiving 733 citations. Previous affiliations of Bandu B. Meshram include University of Mumbai & K. J. Somaiya College of Engineering.

Intrusion detection system in cloud computing environment

Abstract: In recent years, with the growing popularity of cloud computing, security in cloud has become an important issue. As "Prevention is better than cure", detecting and blocking an attack is better than responding to an attack after a system has been compromised. This paper proposes architecture capable of detecting intrusions in a distributed cloud computing environment, and safeguarding it from possible security breaches. It deploys a separate instance of IDS for each user and uses a single controller to manage the instances. IDS in this architecture can use signature based as well as learning based method.

Content based video retrieval systems

Abstract: With the development of multimedia data types and available bandwidth there is huge demand of video retrieval systems, as users shift from text based retrieval systems to content based retrieval systems. Selection of extracted features play an important role in content based video retrieval regardless of video attributes being under consideration. These features are intended for selecting, indexing and ranking according to their potential interest to the user. Good features selection also allows the time and space costs of the retrieval process to be reduced. This survey reviews the interesting features that can be extracted from video data for indexing and retrieval along with similarity measurement methods. We also identify present research issues in area of content based video retrieval systems.

Content based video retrieval systems

Abstract: With the development of multimedia data types and available bandwidth there is huge demand of video retrieval systems, as users shift from text based retrieval systems to content based retrieval systems. Selection of extracted features play an important role in content based video retrieval regardless of video attributes being under consideration. These features are intended for selecting, indexing and ranking according to their potential interest to the user. Good features selection also allows the time and space costs of the retrieval process to be reduced. This survey reviews the interesting features that can be extracted from video data for indexing and retrieval along with similarity measurement methods. We also identify present research issues in area of content based video retrieval systems.

Modeling Rainfall Prediction Using Data Mining Method: A Bayesian Approach

Abstract: Weather forecasting has been one of the most scientifically and technologically challenging problem around the world. Weather data is one of the meteorological data that is rich with important information, which can be used for weather prediction We extract knowledge from weather historical data collected from Indian Meteorological Department (IMD) Pune. From the collected weather data comprising of 36 attributes, only 7 attributes are most relevant to rainfall prediction. We made data preprocessing and data transformation on raw weather data set, so that it shall be possible to work on Bayesian, the data mining, prediction model used for rainfall prediction. The model is trained using the training data set and has been tested for accuracy on available test data. The meteorological centers uses high performance computing and supercomputing power to run weather prediction model. To address the issue of compute intensive rainfall prediction model, we proposed and implemented data intensive model using data mining technique. Our model works with good accuracy and takes moderate compute resources to predict the rainfall. We have used Bayesian approach to prove our model for rainfall prediction, and found to be working well with good accuracy.

Content Based Image Indexing and Retrieval.

Abstract: In this paper, we present the efficient content based image retrieval systems which employ the color, texture and shape information of images to facilitate the retrieval process. For efficient feature extraction, we extract the color, texture and shape feature of images automatically using edge detection which is widely used in signal processing and image compression. For facilitated the speedy retrieval we are implements the antipole-tree algorithm for indexing the images.

Review: A survey of intrusion detection techniques in Cloud

Abstract: In this paper, we survey different intrusions affecting availability, confidentiality and integrity of Cloud resources and services. Proposals incorporating Intrusion Detection Systems (IDS) and Intrusion Prevention Systems (IPS) in Cloud are examined. We recommend IDS/IPS positioning in Cloud environment to achieve desired security in the next generation networks.

An international symposium

Abstract: s should clearly state the purpose, brief statement of procedure, results and conclusions. Please include your name, full address and topic on all submissions. At least one author of each abstract should register for the conference. All accepted abstracts will be published as symposium proceedings. Additionally, commended abstracts may be published in a journal after they are expanded to a manuscript followed by extensive reviewing. The language of the conference will be English.

Security issues in cloud environments: a survey

Abstract: In the last few years, the appealing features of cloud computing have been fueling the integration of cloud environments in the industry, which has been consequently motivating the research on related technologies by both the industry and the academia. The possibility of paying-as-you-go mixed with an on-demand elastic operation is changing the enterprise computing model, shifting on-premises infrastructures to off-premises data centers, accessed over the Internet and managed by cloud hosting providers. Regardless of its advantages, the transition to this computing paradigm raises security concerns, which are the subject of several studies. Besides of the issues derived from Web technologies and the Internet, clouds introduce new issues that should be cleared out first in order to further allow the number of cloud deployments to increase. This paper surveys the works on cloud security issues, making a comprehensive review of the literature on the subject. It addresses several key topics, namely vulnerabilities, threats, and attacks, proposing a taxonomy for their classification. It also contains a thorough review of the main concepts concerning the security state of cloud environments and discusses several open research topics.

Review: An intrusion detection and prevention system in cloud computing: A systematic review

Abstract: The distributed and open structure of cloud computing and services becomes an attractive target for potential cyber-attacks by intruders. The traditional Intrusion Detection and Prevention Systems (IDPS) are largely inefficient to be deployed in cloud computing environments due to their openness and specific essence. This paper surveys, explores and informs researchers about the latest developed IDPSs and alarm management techniques by providing a comprehensive taxonomy and investigating possible solutions to detect and prevent intrusions in cloud computing systems. Considering the desired characteristics of IDPS and cloud computing systems, a list of germane requirements is identified and four concepts of autonomic computing self-management, ontology, risk management, and fuzzy theory are leveraged to satisfy these requirements.

A survey on cloud computing security

Abstract: Over the internet, the cloud computing reveals a remarkable potential to provide on-demand services to consumers with greater flexibility in a cost effective manner. While moving towards the concept of on-demand service, resource pooling, shifting everything on the distributive environment, security is the major obstacle for this new dreamed vision of computing capability. This survey present a comprehensive overview of the security issues for different factors affecting cloud computing. Furthermore, a detailed discussion on several key topics regarding embedded system, application, storage system, clustering related issues and many more. This paper works on some public cloud and private cloud authorities as well as related security concerns. Additionally, it encompasses the requirements for better security management and suggests 3-tier security architecture. Open issues with discussion in which some new security concepts and recommendations are also provided.