On one hand, there are many proposed intrusion detection systems (IDSs) in the literature. On the other hand, many studies try to deduce the important features that can best detect attacks. This paper presents a new and an easy-to-implement approach to intrusion detection, named distance sum-based k-nearest neighbors (DS-kNN), which is an improved version of k-NN classifier. Given a data sample to classify, DS-kNN computes the distance sum of the k-nearest neighbors of the data sample in each of the possible classes of the dataset. Then, the data sample is assigned to the class having the smallest sum. The experimental results show that the DS-kNN classifier performs better than the original k-NN algorithm in terms of accuracy, detection rate, false positive, and attacks classification. The authors mainly compare DS-kNN to CANN, but also to SVM, S-NDAE, and DBN. The obtained results also show that the approach is very competitive.

The design and the evaluation of communication protocols in WSNs is a crucial issue. Generally, researchers use simulation methods to evaluate them. However, formal modelling and analysis techniques are an efficient alternative to simulation methods. Indeed, these techniques allow performance evaluation and model verification. In this paper, a formal approach is proposed to modelling and to evaluating the Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA) MAC protocol with a star topology. Moreover, the proposed approach deals with some properties that are not stated in most existing works. The approach uses Hierarchical Timed Coloured Petri Nets (HTCPNs) formalism to model the protocol and exploits the CPN-Tools to analyse the generated models. HTCPNs provide timed aspect which facilitates the consideration of time constraints inherent to the CSMA/CA protocol.

The growth of Internet of Thing (IoT) implies the availability of a very large number of services which may be similar or the same, managing the Quality of Service (QoS) helps to differentiate one service from another. The service composition provides the ability to perform complex activities by combining the functionality of several services within a single process. Very few works have presented an adaptive service composition solution managing QoS attributes, moreover in the field of healthcare, which is one of the most difficult and delicate as it concerns the precious human life.In this paper, we will present an adaptive QoS-Aware Service Composition Approach (P-MPGA) based on multi-population genetic algorithm in Fog-IoT healthcare environment. To enhance Cloud-IoT architecture, we introduce a Fog-IoT 5-layared architecture. Secondly, we implement a QoS-Aware Multi-Population Genetic Algorithm (P-MPGA), we considered 12 QoS dimensions, i.e., Availability (A), Cost (C), Documentation (D), Location (L), Memory Resources (M), Precision (P), Reliability (R), Response time (Rt), Reputation (Rp), Security (S), Service Classification (Sc), Success rate (Sr), Throughput (T). Our P-MPGA algorithm implements a smart selection method which allows us to select the right service. Also, P-MPGA implements a monitoring system that monitors services to manage dynamic change of IoT environments. Experimental results show the excellent results of P-MPGA in terms of execution time, average fitness values and execution time / best fitness value ratio despite the increase in population. P-MPGA can quickly achieve a composite service satisfying user’s QoS needs, which makes it suitable for a large scale IoT environment

Designing a good MAC protocol remains a challenge. Such a protocol has to guarantee access to the medium while reducing energy consumption. With the appearance of energy harvesting-wireless sensor networks (EH-WSNs), energy is no longer a problem but the challenge now is that each sensor remains in its energetically sustainable state as much as possible. This paper proposes a formal study of on demand MAC (ODMAC) one of the well-known protocols proposed for EH-WSNs. An analysis through statistical model checking is made where properties that guarantee the protocol's correctness are verified and a performance evaluation of important aspects is achieved.

With the explosive growth of Web of Things (WoT) and social web, it is becoming hard for device owners and users to find suitable web Application Programming Interface (API) that meet their needs among a large amount of web APIs. Socialaware and collaborative filtering-based recommender systems are widely applied to recommend personalized web APIs to users and to face the problem of information overload. However, most of the current solutions suffer from the dilemma of accuracydiversity where the prediction accuracy gains are typically accompanied by losses in the diversity of the recommended APIs due to the influence of popularity factor on the final score of APIs (e.g., high rated or high-invoked APIs). To address this problem, the purpose of this paper is developing an improved recommendation model called (Personalized Web API Recommendation) PWR, which enables to discover APIs and provide personalized suggestions for users without sacrificing the recommendation accuracy. To validate the performance of our model, seven variant algorithms of different approaches (popularity-based, userbased and item-based) are compared using MovieLens 20M dataset. The experiments show that our model improves the recommendation accuracy by 12% increase with the highest score among compared methods. Additionally it outperforms the compared models in diversity over all lengths of recommendation lists. It is envisaged that the proposed model is useful to accurately recommend personalized web API for users.

Nowadays, many platforms provide open educational resources to learners. So, they must browse and explore several suggested contents to better assimilate their courses. To facilitate the selecting task of these resources, the present paper proposes an intelligent tutoring system that can access teaching contents available on the web automatically and offers them to learners as additional information sources. In doing so, the authors highlight the description logic approach and its knowledge representation strength that underwrites the modulization, inference, and querying about a web ontology language, and enhanced traditional tutoring systems architecture using ontologies and description logic to enable them to access various data sources on the web. Finally, this article concludes that the combination of machine learning with the semantic web has provided a supportive study environment and enhanced the schooling conditions within open and distance learning.

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.

Electronic health records (EHRs) replaced the old paper-based systems to make patient data more accurate, reliable, and more accessible. Yet, the EHRs system requires high transmission cost, energy, and waste of time for both doctors and patients. Furthermore, EHRs security presents a serious issue threatening the patient’s privacy. Most of the third-party hosting systems have some issues related to the users’ privacy and data security. Hence, it is necessary to restrict the access control policies and develop efficient mechanisms for cloud-based EHRs data. In this paper, a sensitive and energetic access control (SE-AC) mechanism is proposed for managing the cloud-hosted EHRs and providing a fine-grained access control even in critical situations. The proposed mechanism ensures the confidentiality of the patient’s data, where only authorized individuals to have permission to be able to edit or review certain of the patient’s data. Each EHR data is encrypted by the managing authority before submitting to the cloud storage. The requesting user can get dynamically changing permissions based on authentication and context attributes. In addition, seven major aspects have been quantified to assess the operation of any access control that could be deployed in the Internet-of-Thing (IoT). The security analysis indicates that the SE-AC mechanism is secure and will prevent any unauthorized access. The results show exceptional compatibility and performance with different setups and configuration.