The Internet of Things (IoT) allows multiple smart devices to communicate with each other with minimal human intervention. IoT is currently an increasingly popular area of research due to its rapid growth and use in many areas including health, transport, smart cities, smart homes and others. However, IOT face several security threats and challenges. The implementation of traditional security measures. To address these issues, it's necessary to ensure the security, confidentiality, integrity and availability of data in the IoT. The use of Intrusion Detection Systems (IDS) is one of the fundamental solutions available to tackle these challenges. In this study, our objective is to enhance the IoT security by proposing and implementing a new optimized intrusion detection system capable of improving detection accuracy and reducing the rate of false alerts. We define a hybrid technique that combines optimization with classification algorithms in machine learning as well as in deep learning. The main purpose of this hybrid approach is to boost accuracy, precision and performance of the IoT intrusion detection systems while reducing false alerts. To verify security and assess the validity of our proposal, we conduct experiments to validate its accuracy, precision, robustness and correctness.

With mobile cloud data storage, mobile users can offload personal and business data to the cloud for flexibility and save money. However, data outsourcing involves high levels of confidentiality and data protection risks. To address the aforementioned mobile cloud data storage problem, Attribute-Based Encryption (ABE) is proposed due to the flexibility of the encryption strategy and fine-grained access control. However, existing attribute-based multi-authority encryption schemes still require a trusted central authority to issue system parameters and generate secret user keys. In this article, we propose a multi-authority attribute-based access control system that ensures user anonymity, protects user identities from malicious permissions, and supports permission coexistence. Our system uses some location range restrictions with ABE as access policies, and subsequently grants authorization to users whose current location and time align with these policies. To verify security and assess the validity of our proposition, we employ the Scyther tool for verification and conduct experiments to validate its correctness.

Due to the rapid increase in mobile usage within cloud computing, a new computing paradigm has emerged which is called mobile cloud computing (MCC). In here, some new classes of privacy and security challenges are introduced. In this work, we purpose this survey to present the main privacy and security challenges in this domain, which have grown much interest among the research community. However, many researchers have proposed and identified corresponding security solutions to address these challenges.

Cloud Computing is the most promising paradigm in recent times. It offers a cost-efficient service to individual and industries. However, outsourcing sensitive data to entrusted Cloud servers presents a brake to Cloud migration. Consequently, improving the security of data access is the most critical task. As an efficient cryptographic technique, Ciphertext Policy Attribute Based Encryption(CP-ABE) develops and implements fine-grained, flexible and scalable access control model. However, existing CP-ABE based approaches suffer from some limitations namely revocation, data owner overhead and computational cost. In this paper, we propose a sliced revocable solution resolving the aforementioned issues abbreviated RS-CPABE. We applied splitting algorithm. We execute symmetric encryption with Advanced Encryption Standard (AES)in large data size and asymmetric encryption with CP-ABE in constant key length. We re-encrypt in case of revocation one single slice. To prove the proposed model, we expose security and performance evaluation.

Access Control models are required to secure Cloud Computing from unauthorized access. As an efficient cryptographic tool, Ciphertext Policy Attribute Based Encryption offers a fine-grained access to user assets. But, revocation operation presents a major brake in the implementation of this algorithm. However, existing approaches either cannot deal with this problem or have an important computation and/ or storage overheads. In this paper, we propose a sliced revocable solution resolving the aforementioned issues abbreviated MRS-CPABE. It is an efficient solution in case of lazy or complete revocation. We apply information dispersal algorithm and we introduce a match then decrypt process. To assess the perfromance of our solution, we perform a security evaluation with Scyther tool and a formal validation to prove that our proposal can withstand various known attacks. Then, we expose the experiments simulation results.

In metropolises, air pollution is constantly increasing due to multiple factors, including high vehicles mobility and manufactures emissions. Nowadays, the urban environment management and control are among the most important issues of network technologies. Compared to the old environmental monitoring methods, the new network technologies provide several advantages such as flexibility, low latency, and real time control. Therefore, to better control the environment, we present an Alternative Data Gathering strategy for the collection of air pollutants data. Our strategy is based on applying LoRa and LoRaWAN protocols as well as on using NS3 simulator. The experiments showed that our strategy reveals better results in term of the Packet Delivery Ratio.

Today, Cloud Computing architectures offer a cost-efficient services delivered for business, scientific and legal organizations. These structures are used as a guideline to understand the Cloud component, services, actors and interactions. However, few Cloud Computing architectures are proposed and used as references to build a Cloud infrastructure. Most of these models does not treat and burst security layers despite the fact that it presents the most important concerns in the Cloud. The aim of this paper is to propose a new end-to-end reference architecture based on a novel classification of security issues in Cloud Computing environment. To do so, we are going to explore the fundamental concepts of Cloud. We will study and propose a novel actor-based classification of security issues. We will model a Cloud reference architecture from security perspective and we will study in depth security and defense in the Cloud provider tier. We will add a management layer in order to refine our design. To the best of our knowledge, our proposal provides the first Cloud Computing reference architecture actor-based from both security and management perspectives in research field.

Next generation Networks (NGN) are required to support the seamless delivery of voice, video and data with high quality. One of the most important key features of NGN is Quality of Service (QoS), which has been a focal point of NGN research, development and standardization. In this work, we propose and demonstrate an efficient NGN QoS-Aware resource and admission control and management methodology which guarantees the QoS requirements. The advantages of the proposed method, in terms of QoS gains, are demonstrated through modeling of the main QoS parameters. Simulation results are derived to evaluate the performance of the proposed method in terms of supporting the QoS and improving the transport network scalability.

Satisfying the Quality of Service (QoS) requirements is one of the main objectives in the design and implementation of IP-based Next Generation Networks (NGN). This paper formalizes an efficient NGN resource-based call admission control (CAC) method which guarantees the QoS requirements expressed in terms of per-service traffic flow throughput, latency, jitter, loss and authorized waiting delay. The proposed method delivers high quality session-based services compliant with the available capacity over an NGN network based IP/MPLS transport infrastructure. The effects of the proposed method on the QoS provision are demonstrated through modeling of the main QoS parameters. Numerical simulations, which illustrate the proposed method benefits in terms of QoS guarantees and network scalability, are also presented.