WIRELESS sensor networks (WSNs) can be readily deployed in various environments to collect information in an autonomous manner, and thus can support abundant applications such as habitat monitoring, moving target tracking, and fire detection. WSNs are generally event-based systems, and consist of one or more sinks which is responsible for gathering specific data by sending […]
IBSDDS:Access control and security schemes for Distributed Network
CLOUD computing provides users with a convenient mechanism to manage their personal files with the notion called database-as-a-service (DAS). In DAS schemes, a user can outsource his encrypted files to untrusted proxy servers. Proxy servers can perform some functions on the outsourced ciphertexts without knowing anything about the original files. This technique has not been […]
Task Scheduling and Software Project Planning Using ACO
The rapid development of the software industry, software companies are now facing a highly competitive market. To succeed, companies have to make efficient project plans to reduce the cost of software construction It is in medium to large-scale projects, the problem of project planning is very complex and challenging. For scheduling and staffing management, similarly […]
A Coalitional Game Approach Hybrid Wireless Networks in Cooperative packet Delivery
WIRELESS communications and networking technology is the key to supporting a variety of applications such as the safety and emergency notification and infotainment applications a coalitional game framework for carry-and-forward-based cooperative packet delivery to mobile nodes in a hybrid wireless network. The mobile nodes are rational to form coalitions to maximize their individual payoffs. A […]
Predictive ACKs: Reducing Latency and Operational Cost in Cloud Computing
PACK (Predictive ACKs), traffic redundancy elimination (TRE) system, designed for cloud computing customers. In this paper, we present a novel receiver-based end-to-end TRE solution that relies on the power of predictions to eliminate redundant traffic between the cloud and its end-users. In this solution, each receiver observes the incoming stream and tries to match its […]
Real-time nature of Twitter for event detection
Twitter has received much attention recently. In this paper, we investigated the real-time nature of Twitter, devoting particular attention to event detection. An important characteristic of Twitter is its real-time nature. We investigate the real-time interaction of events such as earthquakes in Twitter and propose an algorithm to monitor tweets and to detect a target […]
Differentially-private data release for vertically partitioned Data between two parties
In this paper, we address the problem of private data publishing, where different attributes for the same set of individuals are held by two parties. In particular, we present an algorithm for differentially private data release for vertically-partitioned data between two parties in the semi-honest adversary model. To achieve thiss, we first present a two-party […]
executing computations on untrusted machines in a trustworthy manner
We present sTile, a technique for building software systems that distribute large computations onto the cloud while providing guarantees that the cloud nodes cannot learn the computation’s private data. sTile is based on a nature-inspired, theoretical model of self-assembly. While sTile’s computational model is Turing universal, in this paper, we present a prototype implementation that […]
Data Extraction and Label Assignment for Web Databases
An increasing number of databases have become web accessible through HTML form-based search interfaces. The data units returned from the underlying database are usually encoded into the result pages dynamically for human browsing. For the encoded data units to be machine processable, which is essential for many applications such as deep web data collection and […]
MLT-PPDM: Multi-Level Trust in Privacy Preserving Data Mining
In this paper, we address this challenge in enabling MLT-PPDM services. In particular, we focus on the additive perturbation approach where random Gaussian noise is added to the original data with arbitrary distribution, and provide a systematic solution. Through a one-to-one mapping, our solution allows a data owner to generate distinctly perturbed copies of its […]