This paper aims to address the assessment the similarity between documents or pieces of documents. For this purpose we have developed CASISS (CAlculation of SImilarity of Semi-Structured documents) method to quantify how two given texts are similar. The method can be employed in wide area of applications including content reuse detection which is a hot and challenging topic. It can be also used to increase the accuracy of the information retrieval process by taking into account not only the presence of query terms in the given document (Content Only search — CO) but also the topology (position continuity) of these terms (based on Content And Structure Search — CAS). Tracking the origin of the information in social media, copy right management, plagiarism detection, social media mining and monitoring, digital forensic are among other applications require tools such as CASISS to measure, with a high accuracy, the content overlap between two documents.

CASISS identify elements of semi-structured documents using elements descriptors. Each semi-structured document is pre-processed before the extraction of a set of elements descriptors, which characterize the content of the elements.

In this article, a novel sensitive encryption scheme to secure the digital images based on the Zaslavsky chaotic map is proposed. We employ the Zaslavsky chaotic map as a pseudo-random generator to produce the key encryption of the proposed image cryptosystem. The cipher structure has been chosen based on permutation-diffusion processes, where we adopt the classic permutation substitution network, which ensures both confusion and diffusion properties for the encrypted image. Our proposed algorithm has high sensitivity in plain image and the secret key. Moreover, the results show that the characteristics of our approach have excellent performance, with high scores (NPRC = 99.61%, UACI = 33.47%, entropy (CipherImage)  8, and correlation coefficient  0). Experimental results have been studied and analyzed in detail with various types of security analysis. These results demonstrate that our proposed cryptosystem has highly satisfactory security performance and can withstand various attacks compared to state-of-the-art methods.

Despite the significant advances achieved these recent last years in terms of technologies widespread use in medical education, clinical reasoning learning (CRL) remains an extremely hard task in which there are still many gray areas that should be enlightened to better understand it. Furthermore, while CRL is basically a collaborative task implying the participation of many students and tutors working simultaneously on a same case, it should be considered from a social perspective. The authors followed then a collaborative-based learning approach, which consists in designing a shared workspace to support collaboration and enable social clinical knowledge acquisition. They started with a deep analysis of the CRL process in order to understand the usual way under which students learn together and then, highlight the vital collaborative learning tasks that need to be supported. The resulting designed model allowed us to shift towards Collaborative CRL (CCRL).

Redundant data retransmission problem in wireless sensor networks (WSNs) can be eliminated using the data aggregation process which combines similar data to reduce the resource-consumption and consequently, saves energy during data transmission. In the recent days, many researchers have focused on securing this paradigm despite the constraints it imposes such as the limited resources. Most of the solutions proposed to secure the data aggregation process in WSNs are essentially based on the use of encryption keys to protect data during their transmission in the network. Indeed, the key generation and distribution mechanisms involve additional computation costs and consume more of energy. Considering this, in this paper, we propose a new security mechanism to secure data aggregation in WSNs called SDAW (secure data aggregation watermarking-based scheme in homogeneous WSNs). Our mechanism aims to secure the data aggregation process while saving energy. For this, the mechanism uses a lightweight fragile watermarking technique without encryption to insure the authentication and the integrity of the sensed data while saving the energy. The links between the sensor nodes and the aggregation nodes, and also the links between the aggregation nodes and the base station are secured by using the watermarking mechanism.

Data aggregation processes aim to reduce the amount of exchanged data in wireless sensor networks and consequently minimize the packet overhead and optimize energy efficiency. Securing the data aggregation process is a real challenge since the aggregation nodes must access the relayed data to apply the aggregation functions. The data aggregation security problem has been widely addressed in classical homogeneous wireless sensor networks, however, most of the proposed security protocols cannot guarantee a high level of security since the sensor node resources are limited. Heterogeneous wireless sensor networks have recently emerged as a new wireless sensor network category which expands the sensor nodes’ resources and capabilities. These new kinds of WSNs have opened new research opportunities where security represents a most attractive area. Indeed, robust and high security level algorithms can be used to secure the data aggregation at the heterogeneous aggregation nodes which is impossible in classical homogeneous WSNs. Contrary to the homogeneous sensor networks, the data aggregation security problem is still not sufficiently covered and the proposed data aggregation security protocols are numberless. To address this recent research area, this paper describes the data aggregation security problem in heterogeneous wireless sensor networks and surveys a few proposed security protocols. A classification and evaluation of the existing protocols is also introduced based on the adopted data aggregation security approach.