To protect WSNs from the harmful attacks exploiting the replay of routing information, we have designed and implemented a robust trust-aware routing framework, TARF, to secure routing solutions in wireless sensor networks. The design of TARF centers on trustworthiness and energy efficiency. EnergyWatcher is responsible for recording the energy cost for each known neighbor, based […]
Dynamic Data Operation and Secure access control in cloud computing
The many advantages of cloud computing are increasingly attracting individuals and organizations to outsource their data from local to remote cloud servers. However, security and privacy concerns have arisen as obstacles to widespread adoption of clouds by users. While much cloud security research focuses on enforcing standard access control policies typical of centralized systems, such […]
Latency Equalization using greedy hub selection
In this paper, we design and implement network-based Latency EQualization (LEQ), which is a service that Internet service providers (ISPs) can provide for various interactive network applications. Our LEQ architecture provides a flexible routing framework that enables the network provider to implement different delay and delay difference optimization policies in order to meet the requirements […]
Selfish node detection in MANET
In this paper, we address the problem of selfishness in the context of replica allocation in a MANET, i.e., a selfish node may not share its own memory space to store replica for the benefit of other nodes. In this paper, we shall refer to such a problem as the selfish replica allocation. Simply, selfish […]
Co-distribution patterns Mining for Maximum crime datasets
Crime activities are geospatial phenomena and as such are geospatially, thematically and temporally correlated. We analyze crime datasets in conjunction with socio-economic and socio-demographic factors to discover co-distribution patterns that may contribute to the formulation of crime. We propose a graph based dataset representation that allows us to extract patterns from heterogeneous areal aggregated datasets […]
Class-dependent density-based feature Elimination
High-dimensional data sets are inherently sparse and hence, can be transformed to lower dimensions without losing too much information about the classes. In this paper we propose a new feature ranking algorithm, termed as, class-dependent density-based feature elimination, for binary data sets. CDFE uses a measure termed as, diff-criterion, to estimate the relevance of features. […]
Exploiting Excess Capacity to Improve Robustness of WDM Mesh Networks
Excess capacity (EC) is the unused capacity in a network. Excess capacity management techniques exploit the EC to improve the network performance. In this paper we propose EC management techniques that exploit EC to improve all the three performance metrics. EC management techniques differ in two respects: when connections are migrated from one protection scheme […]
CIA Framework for Data Sharing in Cloud
In this paper we propose a novel approach, namely Cloud Information Accountability (CIA) framework, based on the notion of information accountability. Our proposed CIA framework provides end-to-end accountability in a highly distributed fashion. One of the main innovative features of the CIA framework lies in its ability of maintaining lightweight and powerful accountability that combines […]
A framework for managing and deriving events under uncertainty conditions IEEE Projects 2012
In this work, we present a generic framework for representing events and rules with uncertainty. We present a mechanism to construct the probability space that captures the semantics and defines the probabilities of possible worlds using an abstraction based on a Bayesian network. In order to improve derivation efficiency we employ two mechanisms: The first […]
Community anomaly detection system
Collaborative information systems (CISs) allow groups of users to communicate and cooperate over common tasks. CIS are increasingly relied upon to manage sensitive information. In this paper, we introduce a framework to detect anomalous insiders from the access logs of a CIS by leveraging the relational nature of system users as well as the meta-information […]