Available online Edge data centers are designed to meet the stringent QoE requirements of delay-sensitive and computationally intensive services in Content Delivery Network (CDN) and 5G networks. The primary purpose of this paper was to formulate and solve the problem of optimizing many control variables jointly: (i) what contents to store by taking into consideration edge capacity, and (ii) what contents to recommend to each Internet of Everything (IoE) item, based on identity and access management (IAM). In reactive caching policy, we proposed a new Two-Factor Authentication (2FA) scheme founded upon the Elliptic Curve Cryptography (ECC) and one-way hash function for access control. More interestingly, we use Non-negative Matrix Factorization (NMF), Fuzzy C-Means (FCM), Random Forest (RF) and Pearson Correlation (PC) to improve the accuracy and latency of traditional data filtering models. The intelligent recommendation engine we propose is designed to be implemented by cloud for caching and prefetching contents at the edge. The experimental results validate the theoretical guarantees of the proposed solution and its ability to achieve significant performance gains compared to common baseline models.

Sensor-supported systems have been adapted for various domains, such as healthcare, sports, and education. In this paper, we propose a conceptual reference model of sensor-supported learning systems dimensions based on a review of recent articles in this field. The reference model is based on the identification of different observable properties of learning systems, how sensors are used to support learning, and educational objectives. The proposed reference model can be used to represent the capabilities of current sensor-supported learning systems and provide a basis for the development of future systems.

For decades, the use of weights has proven its superior ability to improve dynamic local search weighting algorithms’ overall performance. This paper proposes a new mechanism where the initial clause’s weights are dynamically allocated based on the problem’s structure. The new mechanism starts by examining each clause in terms of its size and the extent of its link, and its proximity to other clauses. Based on our examination, we categorized the clauses into four categories: (1) clauses small in size and linked with a small neighborhood, (2) clauses small in size and linked with a large neighborhood, (3) clauses large in size and linked with a small neighborhood, and (4) clauses large in size and linked with a large neighborhood. Then, the initial weights are dynamically allocated according to each clause category. To examine the efficacy of the dynamic initial weight assignment, we conducted an extensive study of our new technique on many problems. The study concluded that the dynamic allocation of initial weights contributes significantly to improving the search process’s performance and quality. To further investigate the new mechanism’s effect, we compared the new mechanism with the state-of-the-art algorithms belonging to the same family in terms of using weights, and it was clear that the new mechanism outperformed the state-of-the-art clause weighting algorithms. We also show that the new mechanism could be generalized with minor changes to be utilized within the general-purpose stochastic local search state-of-the-art weighting algorithms.

Cloud computing is an easy-to-use, affordable solution to manage and analyze medical data. Therefore, this paradigm has gained wide acceptance in the healthcare sector as a cost-efficient way for a successful Electronic Medical Records (EMR) implementation. Cloud technology is, however, subject to increasing criticism because of the numerous security vulnerabilities. In this regard, we propose a framework to protect confidential data through the development of new security measures, including compression, secret share scheme and XOR operation. The primary objective of the proposal is to achieve the right balance between security and usability. To this aim, we divide an image into several blocks and then encrypt each piece separately with different cryptographic keys. To enhance privacy and performance, we suggest DepSky architecture to keep data on various storage nodes. Simulation experiments have been conducted to prove the effectiveness of the proposed methodology.

The growing volume of spam Emails has generated the need for a more precise anti-spam filter to detect unsolicited Emails.One of the most common representations used in spam filters is the Bag-of-Words (BOW).Although BOW is very effective in the classification of the emails, it has a number of weaknesses.In this paper, we present a hybrid approach to spam filtering based on the Neural Network model Paragraph Vector-Distributed Memory (PV-DM).We use PV-DM to build up a compact representation of the context of an email and also of its pertinent features.This methodology represents a more comprehensive filter for classifying Emails.Furthermore, we have conducted an empirical experiment using Enron spam and Ling spam datasets, the results of which indicate that our proposed filter outperforms the PV-DM and the BOW email classification methods.

The Internet of Things (IoT) extends internet connectivity to a wide range of smart devices. However, battery autonomy, computational capability and storage capacity are major technology challenges that hinder increased implementation and adoption. Although the integration of the Internet of Things (IoT) with Cloud Computing is considered as a highly promising solution in overcoming these bottlenecks, it raises security concerns, especially access control. Recently, a variety of access control models have been developed to help protect confidential information and restrict access to sensitive data. Because of its flexibility and scalability, the consensus is that the Attribute Based Access Control (ABAC) is the most appropriate model in a dynamic environment. In the context of IoT, the ABAC model has the ability to enforce data privacy and ensure a secure connection between IoT devices and cloud providers. One of the core components of the ABAC model is access policies, these are used to deny or allow user’ requests. To achieve that, an access policy language is required to implement policy rules in ABAC model. In this study, we propose a method based on EXtensible Access Control Markup Language (XACML) to prevent all unauthorized access to remote resources. This policy language is a particularly efficient and appropriate technique within a context of IoT due to its compatibility with heterogonous platforms. 

Cloud computing is generally seen as the most practical and efficient way to build and deploy electronic medical records (EMR) due to advantages such as scalability and cost savings. However, existing solutions are not mature enough to protect patient data. Besides, traditional security countermeasures should be tailored to achieve the right balance between performance and security. In this respect, we propose a highly secure framework to boost remote image processing. Concretely, we rely on the segmentation method to break up the secret image into small portions; thereby optimising the overall execution time. Additionally, we propose a novel access control based on users' trust and user-managed access (UMA). More interestingly, the trust-aware model can reduce the heavy computational overhead of authorisation decisions in comparison to other checking methods. The implementation results prove the accuracy of this approach to meet the stringent security standards and performance requirements.

The integration of cloud computing and Internet of Things (IoT) offers a promising, rich platform for data collection and analysis in smart healthcare. In such a model, IoT devices collect data about patient health status through multiple intelligent sensors, whereas cloud offers scalable resources to quickly meet workload demands. Despite these remarkable improvements, the current architectures do not sufficiently address the security needs for patient medical records. In this perspective, and bearing in mind the specific characteristics of each technology, we propose a distributed security mechanism in a way that fits with IoT and cloud constraints. Our contribution to secure cloud-enabled IoT is twofold. First, we rely on OM-AM (Objective, Model, Architecture and Mechanism) for modeling and analysing the security and privacy requirements of smart healthcare. Second, we use blockchain architecture along with Attribute-Based Access Control (ABAC) model as a decentralized flexible system to support access control decisions. In particular, we rely on XACML (eXtensible Access Control Markup Language) to easily build and implement robust policies required for maintaining a secure IoT-based environment. The novelty of the proposed framework lies at smartly leveraging the recent technologies to keep health information confidential. In fact, putting blockchain and IoT together would undoubtedly create a totally new solution for remote patient monitoring. The simulation results show that the proposal is an efficient way of implementing ubiquitous and cognitive tools for smart healthcare systems.

A radical evolution of the current Internet into a Network of interconnected objects that not only senses information from the environment and interacts with the physical world, but also uses existing Internet standards to provide services for information transfer, analytics, applications and communications results in an enormous amount of vital applications. The pervasive nature of the information sources means that a great amount of data pertaining to possibly every aspect of human activity, both public and private, will be produced, transmitted, collected, stored and processed. Consequently, integrity and confidentiality of transmitted data, as well as the authentication of (and trust in) the services that offer the data, is crucial. Hence, security is a critical functionality for the Internet of Things (IoT). The enormous growth of mobile devices capability, critical automation industry fields and the widespread of wireless communication cast need for the seamless provision of mobile web services IoT environment. These are enriched by mobile cloud computing. However, it puts a challenge to its reliability, data authentication, power consumption and security issues. There is also need for auto- self-operated sensors for geo-sensing, agriculture, automatic cars, factories, roads, medicals application and more. IoT is still highly not reliable in points of integration between how its devices are connected; this means that there is poor utilization of the existing IP security protocols. Our solution is based on the use of existing security protocols between clients and the mobile hosts as well as a key management protocol between the individual mobile hosts implementing an out-of-band key exchange that is simple in practice, flexible and secure. We study the performance of this approach by evaluating a prototype implementation of our security framework. This paper at a preliminary manner, discusses the threats, hacks, misguided packets, over read sensor message. These packets are then translated by hardware and pushed through the web for a later on action or support. Our testing to a set of sensor triggered scenario and set up clearly indicates the security threats from a wireless connected small LAN environments and the overestimated sensor messages resulting from the initial set of the sensor readings, while we emphasize more on the security level of the web services serving the IoT connected device.

The amount of digital records created on a daily basis in the health domain are expected to keep growing sharply. Surely, a medical image contains vital information used mainly to obtain early and accurate diagnosis and treatment. Moreover, the adoption of an electronic medical record system is the most effective method to increase collaboration among healthcare professionals in order to improve the quality of care and patient outcomes. Based on these considerations, sophisticated software and platforms are required to successfully store and process these digital records. In spite of the importance of this model, building and maintaining a local data center for hosting IT services would inevitably increase the cost of healthcare services. Fortunately, cloud computing has provided healthcare institutions with affordable and elastic services to overcome these obstacles. Indeed, this new paradigm allows healthcare organizations to take advantage of remote computational resources offered by an external party. In this respect, healthcare practitioners can access cloud services to store patients' data. These services are billed based on the actual usage of cloud resources. Nevertheless, the adoption of cloud storage in healthcare sector faces enormous challenges, particularly those related to security and privacy. Although there exist several solutions to secure data, they mostly rely on traditional cryptographic schemes, such as AES, RSA and DSA. However, these techniques are often time-consuming, and hence, not suitable for medical data. For this reason, the proposed mechanism utilizes Shamir's Secret Share (SSS) scheme to address the security problems in cloud storage. The choice of this approach is motivated by two main reasons. First, it does not usually require complex mathematical operations to encrypt data as compared to the other techniques. Second, it is an efficient solution for ensuring fault-tolerance in cloud computing. In this paper, we present the main concepts of our approach to properly handle data confidentiality in cloud storage. We then experimentally evaluate the proposed method to prove its correctness. The simulation results show that the proposed solution successfully reduces the security risks when storing medical data on remote cloud storage.

The SIP signaling performance has a vital role for the overall QoS of SIP-based VoIP applications over MANET. The SIP end-to-end performance metrics have been defined in RFC 6076 to provide a standardized method for the performance evaluation of the SIP signaling system over different platforms. However, to our best acknowledge, the benchmarked values for these metrics have not been proposed yet. Therefore, in this paper, a novel Cross-Layer performance enhancement approach is proposed, implemented, and evaluated to improve the performance of the SIP signaling system over OLSR-based MANET by applying significant dynamic modifications for the routing parameters. The SIP performance metrics seek to accurately reflect the SIP signaling state and the required actions for the routing parameters. The implementation of the Cross-Layer OLSR approach has been successful effectively in reducing the total delays in the SIP processes, enhancing the signaling performance, and increasing the utilization level in the system bandwidth and routing processes.

Internet of Things (IoT) has immense potential to change many of our daily activities, routines and behaviors. The pervasive nature of the information sources means that a great amount of data pertaining to possibly every aspect of human activity, both public and private, will be produced, transmitted, collected, stored and processed. Consequently, integrity and confidentiality of transmitted data as well as the authentication of (and trust in) the services that offer the data is crucial. Hence, security is a critical function - ality for the IoT. Enormous growth of mobile devices capability, critical automation of industry fields and the widespread of wireless communication cast need for seamless provision of mobile web services in the Internet of Things (IoT) environment. These are enriched by mobile cloud computing. However, it poses a challenge for its reliability, data authentication, power consumption and security issues. There is also a need for auto self-operated sensors for geo-sensing, agriculture, automatic cars, factories, roads, medi-cals application and more. IoT is still highly not reliable in points of integration between how its devices are connected, that is, there is poor utilization of the existing IP security protocols. In this chapter, we propose a deep penetration method for the IoT connected set of devices, along with the mobile cloud. An architecture and testing framework for providing mobile cloud computing in the IoT that is based on the object security, power utilization, latency measures and packet loss rate is explained. Our solution is based on

Many crucial dependable and secure services including atomic commitment, consensus and group membership, and middleware services (such as replica, communication and transaction services) use fault detectors. Through the use of fault detectors, the overlying service can be exempted from failure treatment and synchronization requirements. Fault detection is essential for proving that the services carried out are correct. In this paper, we first identify the necessary conditions to detect faults in a message passing system where multiple disjoint paths exist between each pair of endpoints. We then present the first fault detection protocol capable of detecting message meta-data modification in the presence of various message interferences in addition to other faults including omission faults, message replay and spurious messages using disjoint paths, where paths with faults are not known a priori. In addition, it authenticates message origins allowing Sybil attacks to be detected, identifies faulty paths, and classifies faults in the presence of multiple messages sent by various system processes. We establish the completeness and soundness properties of the proposed algorithm, i.e., it detects each considered fault and each detected fault is an actual fault, respectively. We also show that our algorithm does not yield a significant packet size and delay overheads. The algorithm shows the viability of the use of disjoint paths in fault detection.

Data Hungry mobile devices, critical automation industry fields cast need for ready and unique sensing and measurement processes. These are enabled by devices named Mobile Wireless Sensor Network (MWSN) that cuts across almost every field of our current lives. Also, it puts a challenge to the protocols to measure, deduct environmental pointers, from computing hardware set ups to delicate ecologies and natural resources to urban environments. The proliferation of these devices in a communicating-function network creates the Internet of Things (IoT)[1].

The implementation of the Session Initiation Protocol (SIP)-based Voice over Internet Protocol (VoIP) and multimedia over MANET is still a challenging issue. Many routing factors affect the performance of SIP signaling and the voice Quality of Service (QoS). Node mobility in MANET causes dynamic changes to route calculations, topology, hop numbers, and the connectivity status between the correspondent nodes. SIP-based VoIP depends on the caller's registration, call initiation, and call termination processes. Therefore, the SIP signaling performance has an important role for the overall QoS of SIP-based VoIP applications for both IPv4 and IPv6 MANET. Different methods have been proposed to evaluate and benchmark the performance of the SIP signaling system. However, the efficiency of these methods vary and depend on the identified performance metrics and the implementation platforms. This survey examines the implementation of the SIP signaling system for VoIP applications over MANET and highlights the available performance enhancement methods.

IoT is a simple idea of connecting all identified objects through wireless connection that they could communicate with each other [1]. Thus, it is a reality that allows connecting people, and also provides connectivity among those owned. This connectivity saves time, effort and enables things to be smart and work automatically. The goal is not just being connected in terms of computers, tablets and smart phones but it can be visualised as a world where everything is connected together with smart communication among them. In this paper, we discuss internet of things in the field of WPS (Wi-Fi Protected Setup), TCP (Transmission Control Protocol) and IEEE 802. Also, there are some tests that are evaluated between CoAP and HTTP which concludes that CoAP/UDP based protocols perform better for constrained networks compared to HTTP. In addition, there are some securities issues that are related to Internet of things are discussed in the paper.

Denial of Service (DoS) attacks have been amajor threat in the Internet and in other emerging networks including DelayTolerant Networks (DTNs). A DTN is characterized by limited bandwidth, longqueuing delays, low data rate, low power and intermittent connectivity. Most ofthe proposed DoS mitigation schemes for wired and wireless networks are highlyinteractive requiring several protocol rounds. They are also resourceconsuming, complex and assume intermittent connectivity. These features makethe applicability of proposed schemes unsuitable in a DTN scenario. An attackercan exploit the DTN message forwarding mechanism to inject fake bundles intothe network. The attacker’s overall objective is to deplete node and linkresources such as CPU processing cycles, battery power, memory and bandwidth.In this paper, we propose a proactive DoS-Resilient Authentication Mechanism(DoSRAM). The proposed mechanism uses three message authenticator variantscalled DTN-Cookies to minimize computational and communication costs. Theproposed mechanism has been verified through simulations using theOpportunistic Network Environment (ONE) simulator. Results show that DoSRAMoutperforms solutions which are based on RSA-Digital Signatures in terms ofthroughput, energy and bandwidth efficiency. DoSRAM can accurately detect andfilter out DoS traffic.

Providing Web services from the mobile cloud is a current research topic. The mobile cloud provides the computing resources and infrastructure to support the seamless provision of Web services in a lightweight manner. Security has become a major concern with the emergence of mobile cloud Web services. In this paper, we investigate the security aspects of a system for complex mobile Web service provisioning. We characterize the security requirements of the individual components and present a security framework to provide authentication and confidentiality between clients and mobile hosts. Our solution is based on the use of existing security protocols between clients and the mobile hosts as well as a key management protocol between the individual mobile hosts implementing an out-of-band key exchange that is simple in practice, flexible and secure. We examine the performance of this approach by evaluating a prototype implementation of our security framework.

This article presents a survey of previous studies in mobile web service provisioning. Providing web services from mobile devices is an evolving and significant technology that has lots of vital industrial, business and daily life applications. However, this technology has some shortcomings that create impediments towards achieving ideal provisioning or consuming of mobile web services. These shortcomings are due to limited mobile device resources and network resources. In order to solve the problem, a coherent understanding of all research challenges has to be introduced and analyzed. The survey categorizes these challenges into three main disciplines: Existing framework types for providing mobile web services, Different methods for publishing and discovering mobile web services and the mechanisms used by web service providers to compensate the lack of resources . The literature in each area is reviewed and followed by a synthesis of open research issues still to be tackled

In this paper, we discuss the performance of applying hybrid spiral dynamic bacterial chemotaxis (HSDBC) optimisation algorithm on an intelligent controller for a differential drive robot. A unicycle class of differential drive robot is utilised to serve as a basis application to evaluate the performance of the HSDBC algorithm. A hybrid fuzzy logic controller is developed and implemented for the unicycle robot to follow a predefined trajectory. Trajectories of various frictional profiles and levels were simulated to evaluate the performance of the robot at different operating conditions. Controller gains and scaling factors were optimised using HSDBC and the performance is evaluated in comparison to previously adopted optimisation algorithms. The HSDBC has proven its feasibility in achieving a faster convergence toward the optimal gains and resulted in a superior performance.