Advising systems automate aspects of academic advising. Traditionally, advising systems focused on specialized tasks such as course selection. Recently, chatbot-based advising systems have emerged as they emulate scenario-based advising. Nevertheless, the design of most chatbot-based advising systems is not user-centric, potentially causing a lack of adoption. Further, there is a lack of studies reporting findings of usability evaluation of chatbot-based advising systems. In response, we contribute a chatbot-based academic advising system, MyAdvisor, that helps students with prescriptive academic inquiries. The system is based on real advising scenarios and designed with usability principles. The results show that students learn the system fast and find it helpful. This work contributes (1) scenario-based functional requirements and usability requirements of the chatbot-based advising system, (2) the application of usability heuristics in the design of the system, and (3) findings of empirically evaluating the system usability.

The Transport Layer Security (TLS) protocol aims to provide confidentiality and integrity of data. It is based on X.509 Certificates. Our previous research showed that popular Web Browsers exhibit non-standardized behaviour with respect to the certificate validation process[1]. This article extends that work by examining their handling of OCSP Stapling. We also examine several popular HTTPS interception products, including proxies and anti-virus tools, regarding their certificate validation processes. We analyse and compare their behaviour to that described in the relative standards.

Blockchain has improved rapidly due to its unique characteristics such as security, decentralization, reliability and data integrity. Blockchain technology is used in several areas, for instance, health, financial, and Education. This article is a systematic review and state of art. It concentrates on Blockchain technology usage in Education; it focuses on three main areas: 1. Educational applications based on Blockchain technology 2. Advantages of use Blockchain in Education among real case study 3. Drawbacks of implementing application based on Blockchain technology. Detailed analysis and discussion based on the results and findings are taken into consideration. Due to the Covid-19 pandemic in 2020, eLearning becomes vital for any educational institute in the world. Covid-19 consequences in the eLearning are discussed and analyzed in our study. In conclusion, we briefly describe our future work to present the new Blockchain model in Education.

In wireless sensor networks for the Internet of Things (WSN‐IoT), the topology deviates very frequently because of the node mobility. The topology maintenance overhead is high in flat‐based WSN‐IoTs. WSN clustering is suggested to not only reduce the message overhead in WSN‐IoT but also control the congestion and easy topology repairs. The partition of wireless mobile nodes (WMNs) into clusters is a multiobjective optimization problem in large‐size WSN. Different evolutionary algorithms (EAs) are applied to divide the WSN‐IoT into clusters but suffer from early convergence. In this paper, we propose WSN clustering based on the memetic algorithm (MemA) to decrease the probability of early convergence by utilizing local exploration techniques. Optimum clusters in WSN‐IoT can be obtained using MemA to dynamically balance the load among clusters. The objective of this research is to find a cluster head set (CH‐set) as early as possible once needed. The WMNs with high weight value are selected in lieu of new inhabitants in the subsequent generation. A crossover mechanism is applied to produce new‐fangled chromosomes as soon as the two maternities have been nominated. The local search procedure is initiated to enhance the worth of individuals. The suggested method is matched with state‐of‐the‐art methods like MobAC (Singh and Lohani, 2019), EPSO‐C (Pathak, 2020), and PBC‐CP (Vimalarani, et al. 2016). The proposed technique outperforms the state of the art clustering methods regarding control messages overhead, cluster count, reaffiliation rate, and cluster lifetime.

Robots are being used more and more in surgery due to the many benefits they bring (e.g. reduction of patient discomfort, precision, reliability). Remote robotic surgery is now expected to become a reality due to the emergence of 5G. Needle insertion is a crucial element of many robotic surgical procedures such as biopsies, injections, neurosurgery, and brachytherapy cancer treatment. During needle insertion in remote robotic surgery, there is still no guarantee that the surgeon will obtain the haptic feedback from the patient side within the stringent deadlines, even in 5G settings. This paper proposes a framework for learning by imitation as a way to predict the messages that will eventually fail to reach their destination within the required deadlines. By leveraging expert demonstrations, the Hidden Markov Model is used to encapsulate a set of expert force/torque profiles and corresponding parameters during the off-line training process. A Gaussian mixture regression is then used to reproduce a generalized version of the force/torque profile and corresponding parameters during the prediction. Simulations are conducted to evaluate the performance of the proposed method. They show that our proposed framework is able to execute predictions in much less than the 1ms end-to-end latency requirement of remote robotic surgery.

Providing an acceptable level of security for Internet of Things (IoT)-based critical infrastructures, such as the connected vehicles, considers as an open research issue. Nowadays, blockchain overcomes a wide range of network limitations. In the context of IoT and blockchain, Byzantine Fault Tolerance (BFT)-based consensus protocol, that elects a set of authenticated devices/nodes within the network, considers as a solution for achieving the desired energy efficiency over the other consensus protocols. In BFT, the elected devices are responsible for ensuring the data blocks’ integrity and preventing the concurrently appended blocks that might contain some malicious data. In this paper, we evaluate the fault-tolerance with different network settings, i.e., the number of connected vehicles. We verify and validate the proposed model with MATLAB/Simulink package simulations. The results show that our proposed hybrid scenario performed over the non-hybrid scenario taking throughput and latency in the consideration as the evaluated metrics.

Connected and Autonomous Electric Vehicles (CAEVs) are becoming a feature of our roads in the imminent future. This disruptive technology is likely to enhance the way we get around the city in many ways by collecting accurate data in regards to the surrounding environment and events in a timely-manner. As such data that is time-sensitive where human life may be at risk requires reliable and on-time data delivery. In crowded dense environments, several issues can reduce the network performance due to the high density of objects such as skyscrapers and vehicles as well as the large number of exchanged data between connected vehicles and other objects on the road. Involving a swarm of autonomous Unmanned Aerial Vehicles (UAVs), namely drones, would enhance network connectivity, reduce CAEVs communication delay, facilitate CAEVs tasks distribution, and elevate provisioning services. In this paper, a routing scheme in an autonomous UAV-connected vehicles network is proposed that provides reduced communication delay. The proposed solution has been evaluated using simulations. The collected results show the feasibility and the advantage of the UAV-assisted connected vehicle network in meeting delay and energy consumption requirements.

Phishing emails are emails that pretend to be from a trusted company that target users to provide personal or financial information. Sometimes, they include links that may download malicious software on user's computers, when clicked. Such emails are easily detected by spam filters that classify any email with a link as a phishing email. However, emails that have no links, link-less emails, requires more effort from the spam filters. Although many researches have been done on this topic, spam filters are still classifying some benign emails as phishing and vice-versa. This paper is focused on classifying link-less emails using machine learning approach, deep neural networks. Deep neural networks differs from simple neural network by having multiple hidden layers where data must be processed before reaching the output layer. The data used in this research is publicly available online. Hyper parameter optimization, was performed, using different settings on the data. In order to demonstrate the effectiveness of the approach, precision, recall and accuracy were computed. The results show that the deep neural network performed well in many of its settings.

Summary The rapid proliferation of Internet of things (IoT) devices, such as smart meters and water valves, into industrial critical infrastructures and control systems has put stringent performance and scalability requirements on modern Supervisory Control and Data Acquisition (SCADA) systems. While cloud computing has enabled modern SCADA systems to cope with the increasing amount of data generated by sensors, actuators, and control devices, there has been a growing interest recently to deploy edge data centers in fog architectures to secure low‐latency and enhanced security for mission‐critical data. However, fog security and privacy for SCADA‐based IoT critical infrastructures remains an under‐researched area. To address this challenge, this contribution proposes a novel security “toolbox” to reinforce the integrity, security, and privacy of SCADA‐based IoT critical infrastructure at the fog layer. The toolbox incorporates a key feature: a cryptographic‐based access approach to the cloud services using identity‐based cryptography and signature schemes at the fog layer. We present the implementation details of a prototype for our proposed secure fog‐based platform and provide performance evaluation results to demonstrate the appropriateness of the proposed platform in a real‐world scenario. These results can pave the way toward the development of a more secure and trusted SCADA‐based IoT critical infrastructure, which is essential to counter cyber threats against next‐generation critical infrastructure and industrial control systems. The results from the experiments demonstrate a superior performance of the secure fog‐based platform, which is around 2.8 seconds when adding five virtual machines (VMs), 3.2 seconds when adding 10 VMs, and 112 seconds when adding 1000 VMs, compared to the multilevel user access control platform.

Slices were introduced in 5G to enable the co-existence of applications with different requirements on a single infrastructure. Slices may be delay-constrained for mission-critical applications such as Tactile Internet applications. When delay-constrained slices are implemented as collections of virtual network function (VNF) chains, a key challenge is to place the VNFs and route the traffic through the chains to meet a strict delay constraint. Parallel VNF processing has been proposed as a promising approach. However, this approach increases the number of physical nodes in the chains, and thus decreases the reliability, which is also critical for Tactile Internet applications. Furthermore, the cost depends upon the specific VNF placement and traffic routing, as nodes and links are heterogeneous. This article tackles the issues of reliability and cost when embedding delay-constrained slices. We model the problem as an optimization problem that minimizes reliability degradation and cost while ensuring the strict delay constraint when a parallel VNF processing approach is used. Due to the complexity of the formulated problem, we also propose a Tabu search-based algorithm to find sub-optimal solutions. The results indicate that our proposed algorithm can significantly improve cost and reliability while meeting a strict delay constraint.

Due to unavoidable environmental factors, wireless sensor networks are facing numerous tribulations regarding network coverage. These arose due to the uncouth deployment of the sensor nodes in the wireless coverage area that ultimately degrades the performance and confines the coverage range. In order to enhance the network coverage range, an instance (node) redeployment-based Bodacious-instance Coverage Mechanism (BiCM) is proposed. The proposed mechanism creates new instance positions in the coverage area. It operates in two stages; in the first stage, it locates the intended instance position through the Dissimilitude Enhancement Scheme (DES) and moves the instance to a new position, while the second stage is called the depuration, when the moving distance between the initial and intended instance positions is sagaciously reduced. Further, the variations of various parameters of BiCM such as loudness, pulse emission rate, maximum frequency, grid points, and sensing radius have been explored, and the optimized parameters are identified. The performance metric has been meticulously analyzed through simulation results and is compared with the state-of-the-art Fruit Fly Optimization Algorithm (FOA) and, one step above, the tuned BiCM algorithm in terms of mean coverage rate, computation time, and standard deviation. The coverage range curve for various numbers of iterations and sensor nodes is also presented for the tuned Bodacious-instance Coverage Mechanism (tuned BiCM), BiCM, and FOA. The performance metrics generated by the simulation have vouched for the effectiveness of tuned BiCM as it achieved more coverage range than BiCM and FOA.

Fog computing is a promising network paradigm in the IoT area as it has a great potential to reduce processing time for time-sensitive IoT applications. However, fog can get congested very easily due to fog resources limitations in term of capacity and computational power. In this paper, we tackle the issue of fog congestion through a request offloading algorithm. The result shows that the performance of fogs nodes can be increased be sharing fog's overload over several fog nodes. The proposed offloading algorithm could have the potential to achieve a sustainable network paradigm and highlights the significant benefits of fog offloading for the future networking paradigm.

Tactile Internet is a next generation Internet. It allows the exchange of haptic sensations in addition to audio and video content. It is a key enabler of several emerging applications as remote robotic surgery and autonomous driving, when combined with 5G and Edge Computing. Because Tactile Internet will enable mission critical applications, it has to adhere to strict requirements, mainly in terms of ultra-responsiveness, ultra-reliability and security. In this paper, we propose a fog-based architecture for remote phobia treatment, a Tactile Internet application. The proposed architecture offers a set of software modules that allow a phobia patient to have a therapy session, under the guidance of an expert therapist located remotely, with the patient and the therapist sharing the same virtual reality environment. We use the fog paradigm to meet the stringent Tactile Internet requirements, namely the round trip latency of 1ms. The components of the architecture offer high level interfaces to simplify interaction with external software components as well as with a wide range of hardware devices. A prototype is also implemented and the performance is discussed.

Within the Internet of Things (IoT) era, a big volume of data is generated/gathered every second from billions of connected devices. The current network paradigm, which relies on centralised data centres (a.k.a. Cloud computing), becomes impractical solution for IoT data storing and processing due to the long distance between the data source (e.g., sensors) and designated data centres. In other words, by the time the data reaches a far data centre, the importance of the data would be vanished. Therefore, the network topologies have been evolved to permit data processing and storage at the edge of the network, introducing what so-called "Fog computing". The later will obviously lead to improvements in quality of service (QoS) via processing and responding quickly and efficiently to varieties of data processing requests. Therefore, understanding Fog computing architecture and its role in improving QoS is a paramount research topic. In this research, we are proposing a Fog computing architecture and framework to improve QoS for IoT applications. Proposed system supports cooperation among Fog nodes in a given location, in order to permit data processing in a shared mode, hence satisfies QoS and serves largest number of service requests. The proposed framework could have the potential in achieving sustainable network paradigm and highlights significant benefits of Fog computing into the computing ecosystem.

In the distributed Internet of Things (IoT) architecture, sensors collect data from vehicles, home appliances and office equipment and other environments. Various objects contain the sensor which process data, cooperate and exchange information with other embedded devices and end users in a distributed network. It is important to provide end-to-end communication security and an authentication system to guarantee the security and reliability of the data in such a distributed system. Two-factor authentication is a solution to improve the security level of password-based authentication processes and immunized the system against many attacks. At the same time, the computational and storage overhead of an authentication method also needs to be considered in IoT scenarios. For this reason, many cryptographic schemes are designed especially for the IoT; however, we observe a lack of laboratory hardware test beds and modules, and universal authentication hardware modules. This paper proposes a design and analysis for a hardware module in the IoT which allows the use of two-factor authentication based on smart cards, while taking into consideration the limited processing power and energy reserves of nodes, as well as designing the system with scalability in mind.

The use of mobile sensing systems (MSS), via smartphone, in various application domains such as (medical and healthcare) are growing rapidly. However, there is a very limited research and development effort put toward exploiting these smartphone sensing technologies to promote human beings wellness and active lifestyle. This paper introduces “Alert Me”, a smartphone application that quantifies the sedentary behavior (e.g., prolonged sitting) and aims at reducing it. It generates the timely personalized messages by suggesting short breaks to promote active lifestyle. We utilize the accelerometer sensor of smartphone to observe the sedentary behavior of the user under free-living conditions. Alert Me computes the features over accelerometer data and performs the classification to generate the alerts by using computation power of smartphone. It facilitates the users to create a personal profile and manage alerts according to their own choice. We develop an initial working prototype to evaluate the applicability of our approach in a real-world scenario to avoid prolonged uninterrupted periods of sedentary time.

Fourth-Generation (4G) mobile networks are based on Long-Term Evolution (LTE) technologies and are being deployed worldwide, while research on further evolution towards the Fifth Generation (5G) has been recently initiated. 5G will be featured with advanced network infrastructure sharing capabilities among different operators. Therefore, an open-source implementation of 4G/5G networks with this capability is crucial to enable early research in this area. The main contribution of this paper is the design and implementation of such a 4G/5G open-source testbed to investigate multioperator infrastructure sharing capabilities executed in virtual architectures. The proposed design and implementation enable the virtualization and sharing of some of the components of the LTE architecture. A testbed has been implemented and validated with intensive empirical experiments conducted to validate the suitability of virtualizing LTE components in virtual infrastructures (i.e., infrastructures with multitenancy sharing capabilities). The impact of the proposed technologies can lead to significant saving of both capital and operational costs for mobile telecommunication operators.

Speed measurement is an important issue for some types of Wireless Sensor Networks (WSN), especially for Vehicular Ad-hoc Networks (VANETs).However, calculating this value is error-prone and costly.This report intends to demonstrate the calculation of speed of an object without the use of any additional devices or sensor boards, only using Received Signal Strength Indication (RSSI) for localization of the vehicles and time calculation using synchronization.We implemented these methods in actual IRIS motes, and tested them.The results show that, while not perfectly accurate, our method proved to be reliable and close to the real speed.In addition, the results do not have any linear correlation in divergence of real speed and calculated speed, which means the system avoids systematic errors.

Wireless Sensor Networks (WSNs) are an emerging type of networks formed by a set of distributed sensor nodes that collaborate to monitor environmental and physical conditions. Mobile medical sensor devices are rapidly emerging as one promising way to monitor patient health and the quality of patient care while improving convenience to the patient and reducing the cost of care by allowing patients to spend more time out of the hospital. In the future, mobile sensors could keep track of everyday behaviors that are reflective of physical and physiological health states and predictive of future health problems. We expect that wearable, portable, and even embeddable sensors will overcome some of the challenges of existing approaches and enable long-term continuous medical monitoring for many purposes. Examples include: Outpatients with chronic medical conditions (such as diabetes); individuals seeking to change behavior (such as losing weight); physicians needing to quantify and detect behavioral aberrations for early diagnosis (such as depression); or athletes wishing to monitor their condition and performance. In this paper, we focus on adapting smartphones used by individuals for health monitoring and present a case study on the design and implementation of a context-aware wireless healthcare application that leverages the capabilities of phone sensor subsystem in tracking human health conditions. The application's detailed scenario and enhanced Android architecture for this solution is presented.

Securing communications in wireless sensor networks is increasingly important, as the diversity of applications increases. In this paper, we analyze the performance and power efficiency of bulk user data communications in a simple, secure PKI-based communication scheme employing a hybrid cryptographic approach. Detailed benchmarks of the involved cryptographic primitives are performed. The results are used to determine how the necessary computing ressources can be reduced from the current implementation, without compromising and even increasing security. At the same time, the special circumstances of the PKI-based framework on memory constrained sensor motes, such as IRIS or MICA2 motes, are considered. An improved set of cryptographic primitives is determined and implemented, improving execution speed and thus energy efficiency.

The IP Multimedia Subsystem (IMS) is one of the key components of third generation (3G) networks, while Wireless Sensor Networks (WSNs) are an emerging type of networks formed by a set of distributed sensor nodes that collaborate to monitor environmental and physical conditions. Combining the capabilities of WSNs and the IMS opens the door to a wide range of personalized and adaptive value added services for 3G users. We have previously proposed a solution for WSN/IMS integration. This solution enriches the IMS architecture with context acquisition and management components, and enables access to those capabilities via standard IMS interfaces. Wireless healthcare is one of the important application areas that can benefit from the combined IMS/WSNs capabilities. In this paper, we focus on this application area and present a case study on the design and implementation of a context-aware IMS wireless healthcare application, that leverages the capabilities of our WSN/IMS integration solution. The application's detailed scenario and IMS deployment architecture are presented and a prototype is built and tested using Ericsson's IMS simulated environment.

This paper introduces an optimal deployment algorithm of sensors in a given region to provide desired coverage and connectivity for a wireless sensor network. Our paper utilizes two separate procedures for covering different regions of a symmetrical rectangular area. The proposed method divides the given area of interest into two distinct sub-regions termed as the central and edge regions. In each region, a unique scheme is used to determine the number and location of sensors required to monitor and completely cover the region keeping the connectivity and coverage ranges of the sensors, their hardware specification and the dimensions of the region concerned as the constraints. Our scheme reduces the overhead in determining the position of sensors for deployment by following a coverage and connectivity algorithm of lesser complexity rather than those present in related schemes. Finally, we compare our deployment scheme with the interpolation scheme of [2] in regions of different dimensions and different coverage and connectivity levels with different sensing ranges of the sensors to show our cost efficiency over the latter.

Recently, key extraction from multipath wireless channels has been largely investigated. This paper tackles practical issues affecting the reliability of key agreement. We first analyze the effect of delay between the channel estimates on the probability of disagreement, and we propose a robust key extraction mechanism against delay. Later, we study the effect of mobility and improve our key generation mechanism taking into account the decorrelation of the channel. Finally, we investigate the impact of mobility on the overall secret bit generation rate.

Sensor nodes of Wireless Sensor Networks (WSNs) are resource constraints in energy, memory, processing and communication bandwidth. Since they are operated by battery, their life span is limited. Specially, energy conservation is very important issue in the WSN, because it directly affects the life of the node as well as the entire network. Here, we develop a new way of electing a node among many trustworthy nodes for routing processes. This method consumes the energies of network nodes based on Fuzzy logic applied on their residual energy, trust level and distance from the Base Station. The proposed method elects one indispensible node for participating in routing among many worthy nodes. Hence, this method of election of node for routing in WSN sees the conservation of nodes energies go by very smooth and justifying, thereby increasing the life of the WSN.

In ad hoc networks, trust calculation mechanisms contribute to distinguish between trustworthy and untrustworthy nodes. The individual trust is an important element for the security of the network to isolate the malicious nodes; a related topic is the extent to which it is possible to trust a group as a separate entity. For the most important trust metric, the authenticity of the participants in the network, we propose a self-organized group-based authentication mechanism (SGAM) in which not only the social relationship between each individual, but also the social relationship between groups is considered to authenticate a node. We propose a model that shows how a group of nodes can be trusted. It defines the notion of trust between groups based on different relationships. With this notion, it is possible to identify and isolate low reputed groups containing malicious members and consequently to increase the trust level of authenticity of the nodes in the whole network.

This paper presents a formal analysis of an authentication handover framework. The framework provides a fast re-authentication mechanism to authenticate a mobile node that moves through different domains without the need to communicate with the home domain. We model the protocol using the high level protocol specification language (HLPSL) and we verify our model using the AVISPA model checking tool. Two main security properties are checked: authenticity and secrecy. We consider different scenarios in order to verify the protocol. Our results show that the protocol fulfills its requirements in almost all tested scenarios.

Security in Wireless Sensor Networks (WSNs) is a major requirement especially when these networks are used in hostile environments. In this paper, we present an efficient Trust-Aware GEographical Routing (TAGER) protocol which expands the simple and scalable position-based routing protocol and utilizes a trust strategy to safeguard routing behaviors and reduce the possibility of selecting the misbehaving nodes as forwarding nodes in WSNs. The algorithm is based on Greedy and Face routing strategies which are restricted in the trusted subminimal ellipses fixed by three points. Herein trust is characterized by the neighbors' feedback suggestions which can be perceived and obtained from reactive acknowledgement. In proposed TAGER protocol scheme, the recommendations are parameterized as trust values, which are changed and updated repeatedly. If the node data forwarding is successful, its trust value would be improved; else its trust level would be decreased because misbehaving nodes have been used as forwarding nodes or forwarding is abnormal. Our simulation results show how our TAGER protocol alleviates the effect of malicious nodes, and improves the packets delivery rate in WSNs.

Pervasive wireless networking requires continuous connection to the Internet while moving from one administration domain to another. To enable continuous connection seamless handover has to be ensured. A concept to ensure seamless handover is the make-before-break approach which can be achieved by performing the pre-authentication in the new domain while maintaining connection to current domain. The duration of the authentication is critical for the handover process because if the mobile nodes move very fast the remaining amount of time of connection to the current domain can become very limited. Therefore, it is a vital issue for seamless mobility to study the authentication performance of a pre-authentication framework. In this paper we model an authentication infrastructure and consider a scenario in which a high number of nodes handover to a new administration domain. The simulation of the authentication process shows the relation between authentication performance and traffic intensity. Furthermore we identify some critical points and potential bottlenecks of this pre-authentication approach.