The core idea of IoT is the connectivity of real-world devices to the Internet, which allows them to expose their functionalities in APIs ways, communicate to other entities, and flow their data over internet. With the massive growth of connected IoT devices, the number of APIs have also increased. Thus, led up to overload information problem, which is making APIs selection more and more difficult for devices owners and users. Therefore, this paper propose web APIs recommendation framework in IoT environment based on social relationships. The main purpose is providing a novel Recommendation method, which enable to discover APIs and provide relevant suggestion for users. The proposed hybrid algorithm is combined content-based filtering and collaborative filtering techniques to improve the accuracy of rating prediction. Finally, experiments are conducted to evaluate the performance of recommendation.

In this paper, we propose a novel, secure, and intelligent IoT approach based on agent, we have implemented in the health care domain, where we developed an intelligent patient monitoring system for monitoring the patients heart rate automatically. Our system is more intelligent that can anticipate the critical condition before it even happens, send a message to the patient family, doctors, nurses, as well as hospital in-charge personal, and launch an alarm to be assisted by the nearest people in place. Also, our architecture ensures the authentication, authorization, and data sensing confidentiality. Hospitals and medical clinics can utilize our system to monitor their outpatients who are in danger of unpredictable health conditions. The approach presented in the paper can also be applied to other IoT domains.

The Internet of things (IoT) is the integration of information space and physical space, becoming more and more popular in several places. In this paper, we will present QoS service composition approach based on multi-population genetic algorithm based on Fog-IoT computing, IoT-cloud architecture problems led us to use the 5-layared architecture implemented on a Fog computing system especially the transport layer. Our work was focus on this transport layer where we divided it into four sub-layers (security, storage, pre-processing & monitoring), it allows us to have promising advantages. Secondly, we implemented a multi-population genetic algorithm (MPGA) based on a QoS model, we considered seven QoS dimensions, i.e. Cost, response time, reliability, reputation, location, security and availability. Experimental results show the excellent results of MPGA in terms of fitness value and execution time to handle our ambulance emergency study case.

In this paper, we have proposed a novel feature-based fragile watermarking scheme for image authentication. The proposed technique extracts Feature Points (FP) by performing the Harris corner detector and used them as germs to decomposes the host image in segments using Voronoi Diagram (VD). The authentication of each segment is guaranteed by using the Cyclic Redundancy Check code (CRC). Then, the CRC encoding procedure is applied to each segment to generate the watermark. Voronoi decomposition is employed because it has a good retrieval performance compared to similar geometrical decomposition algorithms. The security aspect of our proposed method is achieved by using the public key crypto-system RSA (Rivest–Shamir–Adleman) to encrypt the FP. Experimental results demonstrate the efficiency of our approach in terms of imperceptibility, the capability of detection of alterations, the capacity of embedding, and computation time. We have also prove the impact of VD decomposition on the quality of the watermarked image compared to block decomposition. The proposed method can be applicable in the case where the tamper detection is critical and only some regions of interest must be re-transmitted if they are corrupted, like in the case of medical images. An example of the application of our approach to medical image is briefly presented.

We present a new computational problem in this paper, namely the order of a group element problem which is based on the factorization problem, and we analyze its applications in cryptography. We present a new one-way function and from this function we propose a homomorphic probabilistic scheme for encryption. Our scheme, provably secure under the new computational problem in the standard model.

Role-Based Access Control (RBAC) is one of the most used models in designing and implementation of security policies, in large networking systems. Basic RBAC model does not consider temporal aspects which are so important in such policies. Temporal RBAC (TRBAC) is proposed to deal with these temporal aspects. Despite the elegance of these models, designing a security policy remains a challenge. Designers must ensure the consistency and the correctness of the policy. The use of formal methods provides techniques for proving that the designed policy is consistent. In this paper, we present a formal modelling/analysis approach of TRBAC policies. This approach uses Hierarchical Timed Coloured Petri Nets (HTCPN) formalism to model the TRBAC policy, and the CPN-tool to analyse the generated models. The timed aspect, in HTCPN, facilitates the consideration of temporal constraints introduced in TRBAC. The hierarchical aspect of HTCPN makes the model “manageable”, in spite of the complexity of TRBAC policy specification. The analysis phase allows the verification of many important properties about the TRBAC security policy.

Several contention-based MAC protocols for WSNs have been proposed. The control channel is accessed with carrier sense multiple access with collision avoidance (CSMA/CA) method. The complexity of this method and its criticality motivate the formal specification and verification of its basic algorithms. Most existing works do not deal with all possible aspects such as topology, number of nodes, node behaviour, and number of possible retransmissions. In this paper, we propose a stochastic generic model for the 802.11 MAC protocol for an arbitrary network topology which is independent of the number of sensors. In addition to the qualitative evaluation that proves the correctness of the model, we will make a quantitative evaluation using the statistical model checking to measure the probabilistic performance of the protocol.

Nowadays, the distributed computing plays an important role in the data mining process. To make systems scalable it is important to develop mechanisms that distribute the workload among several sites in a flexible way. Moreover, the acronym ERP refers to the systems and software packages used by organisations to manage day-by-day business activities. ERP systems are designed for the defined schema that usually has a common database. In this paper, we present a collaborative multi-agent based system for association rules mining from distributed databases. In our proposed approach, we combine the multi-agent system with association rules as a data mining technique to build a model that can execute the association rules mining in a parallel and distributed way from the centralised ERP database. The autonomous agents used to provide a generic and scalable platform. This will help business decision-makers to take the right decisions and provide a perfect response time using multi-agent system. The platform has been compared with the classic association rules algorithms and has proved to be more efficient and more scalable.

The consensus is a central problem of fault-tolerant distributed computing. Unfortunately, solving such a problem is impossible in asynchronous distributed systems prone to process failures. To circumvent this impossibility (known as FLP impossibility result) in a deterministic way, on top of asynchronous distributed systems enriched with additional assumptions, several protocols have been proposed. Actually, to solve the Byzantine Consensus problem, with a deterministic manner, in systems where at most t processes may exhibit a Byzantine behavior, two approaches have been investigated. The first relies on the addition of synchrony, called Timer-Based, while the second, called Time-Free, is based on the pattern of message exchange. This paper shows that both types of assumptions are not antagonist and can be combined to solve authenticated Byzantine consensus. The combined assumption considers a correct process pi, called ⋄〈t + 1〉-BW, and a set X of t+1 correct processes (including pi itself) such that, eventually, for each query broadcasted by a correct process pj of X, pj receives a response from pi ∈ X among the (n – t) first responses to that query or both links connecting pi and pj are timely. Based on this combination, a simple hybrid authenticated Byzantine consensus protocol benefiting from the best of both worlds is proposed. As a matter of fact, although numerous hybrid protocols have been designed for the consensus problem in the crash model, this is, to our knowledge, the first hybrid deterministic solution to the Byzantine consensus problem.

Nowadays, the coronavirus pandemic has and is still causing large numbers of deaths and infected people. Although governments all over the world have taken severe measurements to slow down the virus spreading (e.g., travel restrictions, suspending all sportive, social, and economic activities, quarantines, social distancing, etc.), a lot of persons have died and a lot more are still in danger. Indeed, a recently conducted study [1] has reported that 79% of the confirmed infections in China were caused by undocumented patients who had no symptoms. In the same context, in numerous other countries, since coronavirus takes several days before the emergence of symptoms, it has also been reported that the known number of infections is not representative of the real number of infected people (the actual number is expected to be much higher). That is to say, asymptomatic patients are the main factor behind the large quick spreading of coronavirus and are also the major reason that caused governments to lose control over this critical situation. To contribute to remedying this global pandemic, in this article, we propose an IoT ^a investigation system that was specifically designed to spot both undocumented patients and infectious places. The goal is to help the authorities to disinfect high-contamination sites and confine persons even if they have no apparent symptoms. The proposed system also allows determining all persons who had close contact with infected or suspected patients. Consequently, rapid isolation of suspicious cases and more efficient control over any pandemic propagation can be achieved.

Information security is one of the important issues in the information age, image encryption algorithms have been increasingly studied to guarantee the secure image transmission over the internet and through wireless networks. In this article, we propose a new approach for image encryption based on polar decomposition and orthogonal matrices. This scheme offers good confusion and diffusion qualities. The proposed algorithm is shown to be secure against important cryptanalytic attacks (statistical attacks, sensitivity dependence, differential attacks, brute force attacks...), theoretical analysis and computer simulations both confirm that it has a high security level.

Recent researches of image encryption algorithms have been increasingly based on chaotic systems. This paper, a new image encryption scheme which employs. The idea is to associate the Hénon attractor and the logistics map, for the construction of a new secret key cryptosystem. We generate values through of the logistics map that will be added to the pixels of the plaintext image. This result modulo 256 will be permuted to another position of the encrypted image. The calculation of this permutation is deducted from the Hénon attractor, which is 2-dimensional, in order to have a significantly increasing the resistance to attacks. The proposed system has the advantage of bigger key space (about 180 bits); high security analysis such as key space analysis, statistical analysis and sensitivity analysis were carried out. The results demonstrate that the proposed system is highly efficient and a robust system.