ieee projects 2012

IEEE Projects | IEEE Projects 2012 | IEEE Projects 2011 | IEEE Project | Final year Projects | Real Time Projects | Ns2 Projects

We, Data Alcott Systems, guide on academic final year projects in technologies such as Java, J2EE, Dot Net, NS2, PHP, Matlab etc.

We are offering final year projects based on IEEE 2012-13 Papers in java, dotnet, Ns2

 

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IEEE Projects 2012

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IEEE 2010 Projects Titles & Abstracts

Application Real Time Project Java -Titles & Abstracts

Application Real Time Projects Dot Net – Titles & abstracts

IEEE Projects Tiles & Abstract

 

Data Mining/ Knowledge and Data Engineering

Outsourced Similarity Search on Metric Data Assets
IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, VOL. 24, NO. 2, FEBRUARY 2012

Technology Used: Java/J2EE
This paper considers a cloud computing setting in which similarity querying of metric data is outsourced to a service provider. The data is to be revealed only to trusted users, not to the service provider or anyone else. Users query the server for the most similar data objects to a query example. Outsourcing offers the data owner scalability and a low-initial investment. The need for privacy may be due to the data being sensitive (e.g., in medicine), valuable (e.g., in astronomy), or otherwise confidential. Given this setting, the paper presents techniques that transform the data prior to supplying it to the service provider for similarity queries on the transformed data. Our techniques provide interesting trade-offs between query cost and accuracy. They are then further extended to offer an intuitive privacy guarantee. Empirical studies with real data demonstrate that the techniques are capable of offering privacy while enabling efficient and accurate processing of similarity queries.

Publishing Search Logs—A Comparative Study of Privacy Guarantees
Knowledge and Data Engineering, March 2012

Technology Used: Java/J2EE
Search engine companies collect the “database of intentions,” the histories of their users’ search queries. These search logs are a gold mine for researchers. Search engine companies, however, are wary of publishing search logs in order not to disclose sensitive information. In this paper, we analyze algorithms for publishing frequent keywords, queries, and clicks of a search log. We first show how methods that achieve variants of k-anonymity are vulnerable to active attacks. We then demonstrate that the stronger guarantee ensured by ε-differential privacy unfortunately does not provide any utility for this problem. We then propose an algorithm ZEALOUS and show how to set its parameters to achieve (ε, δ)-probabilistic privacy. We also contrast our analysis of ZEALOUS with an analysis by Korolova et al. that achieves (ε’,δ’)-indistinguishability. Our paper concludes with a large experimental study using real applications where we compare ZEALOUS and previous work that achieves k-anonymity in search log publishing. Our results show that ZEALOUS yields comparable utility to k-anonymity while at the same time achieving much stronger privacy guarantees.

Dependable and Secure Computing

pCloud: A Distributed System for Practical PIR

Dependable and Secure Computing – January- February 2012

Technology Used: Java/J2EE

Cloud  Computing

Computational Private Information Retrieval (cPIR) protocols allow a client to retrieve one bit from a database, without the server inferring any information about the queried bit. These protocols are too costly in practice because they invoke complex arithmetic operations for every bit of the database. In this paper, we present pCloud, a distributed system that constitutes the first attempt toward practical cPIR. Our approach assumes a disk-based architecture that retrieves one page with a single query. Using a striping technique, we distribute the database to a number of cooperative peers, and leverage their computational resources to process cPIR queries in parallel. We implemented pCloud on the PlanetLab network, and experimented extensively with several system parameters. Our results indicate that pCloud reduces considerably the query response time compared to the traditional client/server model, and has a very low communication overhead. Additionally, it scales well with an increasing number of peers, achieving a linear speedup.

Packet-Hiding Methods for Preventing Selective Jamming Attacks

Dependable and Secure Computing – January- February 2012

Technology Used: Java

The open nature of the wireless medium leaves it vulnerable to intentional interference attacks, typically referred to as jamming. This intentional interference with wireless transmissions can be used as a launchpad for mounting Denial-of-Service attacks on wireless networks. Typically, jamming has been addressed under an external threat model. However, adversaries with internal knowledge of protocol specifications and network secrets can launch low-effort jamming attacks that are difficult to detect and counter. In this work, we address the problem of selective jamming attacks in wireless networks. In these attacks, the adversary is active only for a short period of time, selectively targeting messages of high importance. We illustrate the advantages of selective jamming in terms of network performance degradation and adversary effort by presenting two case studies; a selective attack on TCP and one on routing. We show that selective jamming attacks can be launched by performing real-time packet classification at the physical layer. To mitigate these attacks, we develop three schemes that prevent real-time packet classification by combining cryptographic primitives with physical-layer attributes. We analyze the security of our methods and evaluate their computational and communication overhead.

Detecting and Resolving Firewall Policy Anomalies

Dependable and Secure Computing, May-June 2012

Technology Used: Java
The advent of emerging computing technologies such as service-oriented architecture and cloud computing has enabled us to perform business services more efficiently and effectively. However, we still suffer from unintended security leakages by unauthorized actions in business services. Firewalls are the most widely deployed security mechanism to ensure the security of private networks in most businesses and institutions. The effectiveness of security protection provided by a firewall mainly depends on the quality of policy configured in the firewall. Unfortunately, designing and managing firewall policies are often error prone due to the complex nature of firewall configurations as well as the lack of systematic analysis mechanisms and tools. In this paper, we represent an innovative policy anomaly management framework for firewalls, adopting a rule-based segmentation technique to identify policy anomalies and derive effective anomaly resolutions. In particular, we articulate a grid-based representation technique, providing an intuitive cognitive sense about policy anomaly. We also discuss a proof-of-concept implementation of a visualization-based firewall policy analysis tool called Firewall Anomaly Management Environment (FAME). In addition, we demonstrate how efficiently our approach can discover and resolve anomalies in firewall policies through rigorous experiments.

Services Computing

Bootstrapping Ontologies for Web Services
Services Computing,  Jan.-March 2012

Technology Used: Java/J2EE
Ontologies have become the de-facto modeling tool of choice, employed in many applications and prominently in the semantic web. Nevertheless, ontology construction remains a daunting task. Ontological bootstrapping, which aims at automatically generating concepts and their relations in a given domain, is a promising technique for ontology construction. Bootstrapping an ontology based on a set of predefined textual sources, such as web services, must address the problem of multiple, largely unrelated concepts. In this paper, we propose an ontology bootstrapping process for web services. We exploit the advantage that web services usually consist of both WSDL and free text descriptors. The WSDL descriptor is evaluated using two methods, namely Term Frequency/Inverse Document Frequency (TF/IDF) and web context generation. Our proposed ontology bootstrapping process integrates the results of both methods and applies a third method to validate the concepts using the service free text descriptor, thereby offering a more accurate definition of ontologies. We extensively validated our bootstrapping method using a large repository of real-world web services and verified the results against existing ontologies. The experimental results indicate high precision. Furthermore, the recall versus precision comparison of the results when each method is separately implemented presents the advantage of our integrated bootstrapping approach.

Towards Secure and Dependable Storage Services in Cloud Computing
Services Computing

Technology Used: Java/J2EE
As one of the emerging services in cloud paradigm, cloud storage enables users to remotely store their data into the cloud so as to enjoy the on-demand high quality applications and services from a shared pool of configurable computing resources. While cloud storage relieves users from the burden of local storage management and maintenance, it is also relinquishing users’ ultimate control over the fate of their data, which may put the correctness of outsourced data into risks. In order to regain the assurances of cloud data integrity and availability and enforce the quality of cloud storage service for users, we propose a highly efficient and flexible distributed storage verification scheme with two salient features, opposing to its predecessors. By utilizing the homomorphic token with distributed erasure-coded data, our scheme achieves the integration of storage correctness insurance and data error localization, i.e., the identification of misbehaving server(s). Unlike most prior works, the new scheme further supports secure and efficient dynamic operations on outsourced data, including: block modification, deletion and append. Extensive security and performance analysis shows the proposed scheme is highly efficient and resilient against Byzantine failure, malicious data modification attack, and even server colluding attacks.

Parallel Distributed Systems

BECAN: A Bandwidth-Efficient Cooperative Authentication Scheme for Filtering Injected False Data in Wireless Sensor Networks
Parallel And Distributed Systems, Vol. 23, No. 1, January 2012

Technology Used: Java
Injecting false data attack is a well known serious threat to wireless sensor network, for which an adversary reports bogus information to sink causing error decision at upper level and energy waste in en-route nodes. In this paper, we propose a novel bandwidth-efficient cooperative authentication (BECAN) scheme for filtering injected false data. Based on the random graph characteristics of sensor node deployment and the cooperative bit-compressed authentication technique, the proposed BECAN scheme can save energy by early detecting and filtering the majority of injected false data with minor extra overheads at the en-route nodes. In addition, only a very small fraction of injected false data needs to be checked by the sink, which thus largely reduces the burden of the sink. Both theoretical and simulation results are given to demonstrate the effectiveness of the proposed scheme in terms of high filtering probability and energy saving.

Cooperative Provable Data Possession for Integrity Verification in Multi-Cloud Storage
Parallel and Distributed Systems, Pre-Print

Technology Used: Java/J2EE
Provable data possession (PDP) is a technique for ensuring the integrity of data in storage outsourcing. In this paper, we address the construction of an efficient PDP scheme for distributed cloud storage to support the scalability of service and data migration, in which we consider the existence of multiple cloud service providers to cooperatively store and maintain the clients; data. We present a cooperative PDP (CPDP) scheme based on homomorphic verifiable response and hash index hierarchy. We prove the security of our scheme based on multi-prover zero-knowledge proof system, which can satisfy completeness, knowledge soundness, and zero-knowledge properties. In addition, we articulate performance optimization mechanisms for our scheme, and in particular present an efficient method for selecting optimal parameter values to minimize the computation costs of clients and storage service providers. Our experiments show that our solution introduces lower computation and communication overheads in comparison with non-cooperative approaches.

Multiple Exposure Fusion for High Dynamic Range Image Acquisition

Image Processing -January 2012

Technology Used: Dot Net

A multiple exposure fusion to enhance the dynamic range of an image is proposed. The construction of high dynamic range images (HDRIs) is performed by combining multiple images taken with different exposures and estimating the irradiance value for each pixel. This is a common process for HDRI acquisition. During this process, displacements of the images caused by object movements often yield motion blur and ghosting artifacts. To address the problem, this paper presents an efficient and accurate multiple exposure fusion technique for the HDRI acquisition. Our method simultaneously estimates displacements and occlusion and saturation regions by using maximum a posteriori estimation and constructs motion-blur-free HDRIs. We also propose a new weighting scheme for the multiple image fusion. We demonstrate that our HDRI acquisition algorithm is accurate, even for images with large motion.