SensorCloud: Towards the Interdisciplinary Development of a Trustworthy Platform for Globally Interconnected Sensors and Actuators

Although Cloud Computing promises to lower IT costs and increase users' productivity in everyday life, the unattractive aspect of this new technology is that the user no longer owns all the devices which process personal data. To lower scepticism, the project SensorCloud investigates techniques to understand and compensate these adoption barriers in a scenario consisting of cloud applications that utilize sensors and actuators placed in private places. This work provides an interdisciplinary overview of the social and technical core research challenges for the trustworthy integration of sensor and actuator devices with the Cloud Computing paradigm. Most importantly, these challenges include i) ease of development, ii) security and privacy, and iii) social dimensions of a cloud-based system which integrates into private life. When these challenges are tackled in the development of future cloud systems, the attractiveness of new use cases in a sensor-enabled world will considerably be increased for users who currently do not trust the Cloud.Comment: 14 pages, 3 figures, published as technical report of the Department of Computer Science of RWTH Aachen Universit

SAMI: Service-Based Arbitrated Multi-Tier Infrastructure for Mobile Cloud Computing

Mobile Cloud Computing (MCC) is the state-ofthe- art mobile computing technology aims to alleviate resource poverty of mobile devices. Recently, several approaches and techniques have been proposed to augment mobile devices by leveraging cloud computing. However, long-WAN latency and trust are still two major issues in MCC that hinder its vision. In this paper, we analyze MCC and discuss its issues. We leverage Service Oriented Architecture (SOA) to propose an arbitrated multi-tier infrastructure model named SAMI for MCC. Our architecture consists of three major layers, namely SOA, arbitrator, and infrastructure. The main strength of this architecture is in its multi-tier infrastructure layer which leverages infrastructures from three main sources of Clouds, Mobile Network Operators (MNOs), and MNOs' authorized dealers. On top of the infrastructure layer, an arbitrator layer is designed to classify Services and allocate them the suitable resources based on several metrics such as resource requirement, latency and security. Utilizing SAMI facilitate development and deployment of service-based platform-neutral mobile applications.Comment: 6 full pages, accepted for publication in IEEE MobiCC'12 conference, MobiCC 2012:IEEE Workshop on Mobile Cloud Computing, Beijing, Chin

A view at desktop clouds

Cloud has emerged as a new computing paradigm that promises to move into computing-as-utility era. Desktop Cloud is a new type of Cloud computing. It merges two computing models: Cloud computing and volunteer computing. The aim of Desktop Cloud is to provide Cloud services out of infrastructure that is not made for this purpose in order to reduce running and maintenance costs. This paper discusses this new type of Cloud by comparing it with current Cloud and Desktop Grid models. It, also, presents several research challenges in Desktop Cloud that require further attention

Data centric trust evaluation and prediction framework for IOT

© 2017 ITU. Application of trust principals in internet of things (IoT) has allowed to provide more trustworthy services among the corresponding stakeholders. The most common method of assessing trust in IoT applications is to estimate trust level of the end entities (entity-centric) relative to the trustor. In these systems, trust level of the data is assumed to be the same as the trust level of the data source. However, most of the IoT based systems are data centric and operate in dynamic environments, which need immediate actions without waiting for a trust report from end entities. We address this challenge by extending our previous proposals on trust establishment for entities based on their reputation, experience and knowledge, to trust estimation of data items [1-3]. First, we present a hybrid trust framework for evaluating both data trust and entity trust, which will be enhanced as a standardization for future data driven society. The modules including data trust metric extraction, data trust aggregation, evaluation and prediction are elaborated inside the proposed framework. Finally, a possible design model is described to implement the proposed ideas

Trustee: A Trust Management System for Fog-enabled Cyber Physical Systems

In this paper, we propose a lightweight trust management system (TMS) for fog-enabled cyber physical systems (Fog-CPS). Trust computation is based on multi-factor and multi-dimensional parameters, and formulated as a statistical regression problem which is solved by employing random forest regression model. Additionally, as the Fog-CPS systems could be deployed in open and unprotected environments, the CPS devices and fog nodes are vulnerable to numerous attacks namely, collusion, self-promotion, badmouthing, ballot-stuffing, and opportunistic service. The compromised entities can impact the accuracy of trust computation model by increasing/decreasing the trust of other nodes. These challenges are addressed by designing a generic trust credibility model which can countermeasures the compromise of both CPS devices and fog nodes. The credibility of each newly computed trust value is evaluated and subsequently adjusted by correlating it with a standard deviation threshold. The standard deviation is quantified by computing the trust in two configurations of hostile environments and subsequently comparing it with the trust value in a legitimate/normal environment. Our results demonstrate that credibility model successfully countermeasures the malicious behaviour of all Fog-CPS entities i.e. CPS devices and fog nodes. The multi-factor trust assessment and credibility evaluation enable accurate and precise trust computation and guarantee a dependable Fog-CPS system