Security, Privacy & Incentive Provision for Mobile Crowd Sensing Systems

Security, Privacy & Incentive Provision for Mobile Crowd Sensing Systems Recent advances in sensing, computing, and networking have paved the way for the emerging paradigm of Mobile Crowd Sensing (MCS). The openness of such systems and the richness of data MCS users are expected to contribute to them raise significant concerns for their security, privacy preservation and resilience. Prior works addressed different aspects of the problem. But in order to reap the benefits of this new sensing paradigm, we need a holistic solution. That is, a secure and accountable MCS…

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A Secure and Efficient ID-Based Aggregate Signature Scheme for Wireless Sensor Networks

A Secure and Efficient ID-Based Aggregate Signature Scheme for Wireless Sensor Networks DOWNLOAD PROJECT SYNOPSIS – JAVA DOWNLOAD PROJECT SYNOPSIS – NS2 Affording secure and efficient big data aggregation methods is very attractive in the field of wireless sensor networks research. In real settings, the wireless sensor networks have been broadly applied, such as target tracking and environment remote monitoring. However, data can be easily compromised by a vast of attacks, such as data interception and data tampering, etc. Mainly focus on data integrity protection, give an identity-based aggregate signature…

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Privacy-Preserving Ride Sharing Scheme for Autonomous Vehicles in Big Data Era

Privacy-Preserving Ride Sharing Scheme for Autonomous Vehicles in Big Data Era DOWNLOAD PROJECT SYNOPSIS Ride sharing can reduce the number of vehicles in the streets by increasing the occupancy of vehicles, which can facilitate traffic and reduce crashes and the number of needed parking slots. Autonomous Vehicles (AVs) can make ride sharing convenient, popular, and also necessary because of the elimination of the driver effort and the expected high cost of the vehicles. However, the organization of ride sharing requires the users to disclose sensitive detailed information not only on…

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BLITHE: Behavior Rule Based Insider Threat Detection for Smart Grid

BLITHE: Behavior Rule Based Insider Threat Detection for Smart Grid DOWNLOAD PROJECT SYNOPSIS A behavior rule-based methodology is proposed for insider threat (BLITHE) detection of data monitor devices in smart grid, where the continuity and accuracy of operations are of vital importance. Based on the dc power flow model and state estimation model, three behavior rules are extracted to depict the behavior norms of each device, such that a device (trustee) that is being monitored on its behavior can be easily checked on the deviation from the behavior specification. Specifically,…

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Optimizing Cloud-Based Video Crowdsensing

Optimizing Cloud-Based Video Crowdsensing Wearable and mobile devices are widely used for crowdsensing, as they come with many sensors and are carried everywhere. Among the sensing data, videos annotated with temporal-spatial metadata contain huge amount of information, but consume too much precious storage space. The problem of optimizing cloud-based video crowdsensing in three steps is studied. First, we study the optimal transcoding problem on wearable and mobile cameras. An algorithm to optimally select the coding parameters is proposed to fit more videos at higher quality on wearable and mobile cameras.…

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Distributed Resource Management for Cognitive Ad Hoc Networks With Cooperative Relays

Distributed Resource Management for Cognitive Ad Hoc Networks With Cooperative Relays DOWNLOAD PROJECT SYNOPSIS It is well known that the data transport capacity of a wireless network can be increased by leveraging the spatial and frequency diversity of the wireless transmission medium. This has motivated the recent surge of research in cooperative and dynamic-spectrum-access (which we also refer to as cognitive spectrum access) networks. Still, as of today, a key open research challenge is to design distributed control strategies to dynamically jointly assign: 1) portions of the spectrum and 2)…

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Optimizing Video Request Routing in Mobile Networks with Built-in Content Caching

Optimizing Video Request Routing in Mobile Networks with Built-in Content Caching DOWNLOAD PROJECT SYNOPSIS Built-in content caching in mobile core networks can help improve quality of service, reduce operation expenses, simplify inter-network cooperation, and thus is a promising approach for more efficient networking architectures. In addition to the complexity of content placement as revealed in the literature, routing video requests remains a challenging issue. Two problems must be addressed: (i) how to distribute video requests among multiple internal servers (i.e., server selection); and (ii) how to route so-generated video flows…

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GeTrust: A guarantee-based trust model in Chord-based P2P networks

GeTrust: A guarantee-based trust model in Chord-based P2P networks DOWNLOAD PROJECT SYNOPSIS – JAVA DOWNLOAD PROJECT SYNOPSIS – NS2 More and more users are attracted by P2P networks characterized by decentralization, autonomy and anonymity. However, users unconstrained behavior makes it necessary to use a trust model when establishing trust relationships between peers. Most existing trust models are based on recommendations, which, however, suffer from the shortcomings of slow convergence and high complexity of trust computations, as well as huge overhead of network traffic. Inspired by the establishment of trust relationships…

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PROVEST: Provenance-based Trust Model for Delay Tolerant Networks

PROVEST: Provenance-based Trust Model for Delay Tolerant Networks DOWNLOAD PROJECT SYNOPSIS – JAVA DOWNLOAD PROJECT SYNOPSIS – NS2 Delay tolerant networks (DTNs) are often encountered in military network environments where end-to-end connectivity is not guaranteed due to frequent disconnection or delay. A provenance-based trust framework is proposed, namely PROVEST (PROVEnance-baSed Trust model) that aims to achieve accurate peer-to-peer trust assessment and maximize the delivery of correct messages received by destination nodes while minimizing message delay and communication cost under resource-constrained network environments. Provenance refers to the history of ownership of…

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Efficient and Exact Local Search for Random Walk Based Top-K Proximity Query in Large Graphs

Efficient and Exact Local Search for Random Walk Based Top-K Proximity Query in Large Graphs DOWNLOAD PROJECT SYNOPSIS Top- k proximity query in large graphs is a fundamental problem with a wide range of applications. Various random walk based measures have been proposed to measure the proximity between different nodes. Although these measures are effective, efficiently computing them on large graphs is a challenging task. An efficient and exact local search method is developed, FLoS (Fast Local Search), for top- k proximity query in large graphs. FLoS guarantees the exactness…

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