Data analytics based on the produced data from the Internet of Things (IoT) devices is expected to improve the individuals’ quality of life. However, ensuring security and privacy in the IoT data aggregation process is a non-trivial task. Generally, the IoT data aggregation process is based on centralized servers. Yet, in the case of distributed approaches, it is difficult to coordinate several untrustworthy parties. Fortunately, the blockchain may provide decentralization while overcoming the trust problem. Consequently, blockchain-based IoT data aggregation may become a reasonable choice for the design of a privacy-preserving system. To this end, we propose PrivDA, a Privacy-preserving IoT Data Aggregation scheme based on the blockchain and homomorphic encryption technologies. In the proposed system, each data consumer can create a smart contract and publish both terms of service and requested IoT data. Thus, the smart contract puts together into one group potential data producers that can answer the consumer’s request and chooses one aggregator, the role of which is to compute the group requested result using homomorphic computations. Therefore, group-level aggregation obfuscates IoT data, which complicates sensitive information inference from a single IoT device. Finally, we deploy the proposal on a private Ethereum blockchain and give the performance evaluation.

Rapid growth of published Web services makes their discoveries more and more difficult. Many approaches are proposed to solve this discovery issue. Most of them are interested only Web service's description itself and neglect the user-centric aspect of the discovery process. User's involvement may be seen as contributing information, after using or testing a service, which marks the personal opinion on service's functionality, quality or invocation cost. This kind of contribution is perceived as a participative aspect inside the Web 2.0 environment and can enhance the Web service discovery process. We illustrate in this research work, a collaborative tagging-based environment for Web service discovery, allowing users to tag or annotate a Web service using keyword or free-text. Our system proposes consequently two types of query to search tagged Web services: keyword based and free-text. We put in place an advanced mode in the discovery by keyword which offers different ways to combine keywords together inside a query to make it more flexible and accurate. In both types of look-up (by keyword and by free-text), synonym relation between terms is processed in order to enhance the similarity computing between a query and the tagged Web services. The Web services found after a discovery process are ranked according to their tags' weight, in the case of discovery by keywords.

Efficient organisations need to ensure that their business processes are flexible so that these processes can easily accommodate changes in regulations and policies. Appropriate techniques to model and verify these processes are required. In this paper, we present a rule-based approach, which is built upon the event-condition-action model (ECA) and supported by a rule-based business process definition language (RbBPDL). In this approach, rules, which specify business processes, are represented using the event-condition-action-post-condition-event (ECAPE) model. This allows translating a process into a graph of rules that is used to check how flexible a business process is, and estimating this process's cost of changes. This cost is based on a rule change cost model (R2CM) that will be presented in this paper. In addition, the ECAPE model allows the translation of a process into a coloured Petri net, called ECAPE net, in order to verify process functioning prior to any deployment.

The increasing use of Web services as well as the growing interest lent to Cloud computing technology and its capacity of calculation, storage and Cloud services, impose today that the traditional mechanisms of discovery must be re-examined. This specificity of discovery over the cloud led us to propose a new approach based on mobile agents dedicated to Web services discovery. More accurately, we propose a new algorithm of comparison between the request of the client and the description of the Web services. Our system is composed of two areas of Cloud. The first deals with Key words based research and second supports the filtering of the found web services. This discovery is performed by an algorithm based on the calculation of similarities between the request and the description of the web services.