Scientific Publications
Browse our catalog of peer-reviewed scientific articles
Research Categories
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Computer Science & Engineering
Core computing paradigms, algorithm design, software architectures, advanced computing theory, and hardware engineering.
Computer Networks
Network architectures, wireless ad-hoc protocols, vehicular networks (VANET), buffering, and communications.
Electronics Department
Circuits, semiconductor devices, flexible electronics, solar array modeling, signal processing, and photonics.
Civil Engg
Structural analysis, thermal stability of fluid layers, environmental infrastructure, and applied materials engineering.
Recent Publications (6)
SECURITY CONCERN ON CLOUD BASED ON ATTRIBUTES: AN SURVEY
The Cloud computing is the way of using a network of remote servers hosted on the Internet to store, process and manage data, rather than on to the local server. Security is the most important concern in the cloud computing because the user data is transferring through the insecure medium i.e. Internet. In this paper, we present an overview of existing issues related to the cloud security and algorithms for finegrained access control and data security in the cloud environment. All these algorithms are described more or less on their own. Cloud security is a very popular task. We also explain the fundamentals of sequential rule mining. We describe today’s approaches for cloud security. From the broad variety of efficient algorithms that have been developed we will compare the most important ones. We will systematize the algorithms and analyze their performance based on both their run time performance and theoretical considerations. Their strengths and weaknesses are also investigated. It turns out that the behavior of the algorithms is much more similar as to be expected.
Privacy in Location-Based Services using SP-Filtering in Hide and Seek Protocol with Obfuscation- Based Methods
Privacy in Location based services has always been a question in terms of Security and Privacy. And lately there has been some work done on Privacy part of Location Based Services (LBS). This Privacy known name as “Privacy aware Proximity based services.” In Privacy aware Proximity based services; two mobile users will check if they're in proximity to every alternative while not revealing their actual locations . This paper will describe the implementation of one such protocol which is used for preserving the privacy of user’s exact location called “Hide and Seek Protocol using SPfiltering Protocol”
Cloud Computing: Provide privacy and Security in Databaseas-a-Service
Cloud computing Environment provides the platform to share computing resources and provide different services like SaaS, PaaS and IaaS that will used by organization as private, public or Hybrid. Cloud computing basically known as Everythingas-a-service .Since cloud computing is used shared distributed resources over the world wide network (e.g., internet) in the open environment, thus it will create various security issues in cloud environment and their application. On our personal computer we have full control on data and processes but in cloud environment we used data and application services which are provided by some of other Cloud Service Providers (CSP) (e.g., AWS, Google docs, Go Grid etc.).We overcome these issues of security and privacy by using Radius server which is known as AAA server (Authentication, Authorization and Accounting). Using this we will secure our CSP main server that further link with Data Center which store database of various cloud users. We use client password to encrypt and decrypt their data when they access or store data in Cloud Data Center (CDC).
Analysis of Classification Techniques based on SVM for Face Recognition
SVM and ISVM are the most prominent technique for excellent learning and classification in the field of machine learning such as face detection and recognition, handwriting automatic identification and automatic text categorization, video tracking, Number plate recognition, Traffic Control etc. Nowadays, Face recognition is a challenging task in the field of computer vision. Motive of face recognition is to compare between the Given face database with the input face image and then declare a decision that identifies to whom the input image class belongs to or doesn’t belong to the face database.In this analysis we not only study and also compare the sophisticated classification technique i.e. SVM and ISVM for face recognition along with its pros and cons.
An Approach to for Improving the Efficiency of IDS System Using Honeypot
Increasing technology space has pressurized the orgainsational enviroment to safegraurd its network from outside as well as inside attack. Any malicious intrusion can dragdown a highly reputed organisation to the floors of defamation and even insolvency. Henceforth network security is one of the biggest challenge for organisation. Although traditional concepts of firewall and intrusion detction system is prevailing yet there is a need to secure the enviroment from the so called zero day attacks. Attackers every now and then generate exploits to penetrate the secure network enviroment and the existing known signatures are not able to detect such an attack. This paper brings forth the concept of deployment of honeypot so as to make the IDS system more effective and efficient for the zero day attack leading to least penetration to the network enviroment. This paper lays down a new network architecture so that the IDS system can be updated with the latest attack scenarios. The aforesaid objective is achived with the help of establishment of honeypot. Later tcpdump is used for he further analysis of payload so as to generate alert signautre in IDS(Snort v2.0).
A Novel Algorithm for Design Tree Classification with PCA
Classification technique is useful to categorize data into classes from the current dataset on the basis of a training set of data containing observations (or instances) whose category membership is known. The decision Tree classification algorithm doesn't work well separately for high dimensional data. To improve the efficiency, in our work, we apply principal component analysis and linear transformation together on the original data set for dimensionality reduction after that classification algorithm is applied for a better solution.