This paper reviews big data and Internet of Things (IoT)-based applications in smart environments. The aim is to identify key areas of application, current trends, data architectures, and ongoing ...challenges in these fields. To the best of our knowledge, this is a first systematic review of its kind, that reviews academic documents published in peer-reviewed venues from 2011 to 2019, based on a four-step selection process of identification, screening, eligibility, and inclusion for the selection process. In order to examine these documents, a systematic review was conducted and six main research questions were answered. The results indicate that the integration of big data and IoT technologies creates exciting opportunities for real-world smart environment applications for monitoring, protection, and improvement of natural resources. The fields that have been investigated in this survey include smart environment monitoring, smart farming/agriculture, smart metering, and smart disaster alerts. We conclude by summarizing the methods most commonly used in big data and IoT, which we posit to serve as a starting point for future multi-disciplinary research in smart cities and environments.
OpenFlow is considered as the most known protocol for Software Defined Networking (SDN). The main drawback of OpenFlow is the lack of support of new header definitions, which is required by network ...operators to apply new packet encapsulations. While SDN’s logically centralized control plane could enhance network security by providing global visibility of the network state, it still has many side effects. The intelligent controllers that orchestrate the dumb switches are overloaded and become prone to failure. Delegating some level of control logic to the edge or, to be precise, the switches can offload the controllers from local state based decisions that do not require global network wide knowledge. Thus, this paper, to the best of our knowledge, is the first to propose the delegation of typical security functions from specialized middleboxes to the data plane. We leverage the opportunities offered by programming protocol-independent packet processors (P4) language to present two authentication techniques to assure that only legitimate nodes are able to access the network. The first technique is the port knocking and the second technique is the One-Time Password. Our experimental results indicate that our proposed techniques improve the network overall availability by offloading the controller as well as reducing the traffic in the network without noticeable negative impact on switches’ performance.
In recent years, educational institutions have worked hard to automate their work using more trending technologies that prove the success in supporting decision-making processes. Most of the ...decisions in educational institutions rely on rating the academic research profiles of their staff. An enormous amount of scholarly data is produced continuously by online libraries that contain data about publications, citations, and research activities. This kind of data can change the accuracy of the academic decisions, if linked with the local data of universities. The linked data technique in this study is applied to generate a link between university semantic data and a scientific knowledge graph, to enrich the local data and improve academic decisions. As a proof of concept, a case study was conducted to allocate the best academic staff to teach a course regarding their profile, including research records. Further, the resulting data are available to be reused in the future for different purposes in the academic domain. Finally, we compared the results of this link with previous work, as evidence of the accuracy of leveraging this technology to improve decisions within universities.
Waterborne pathogens affect all waters globally and proceed to be an ongoing concern. Previous methods for detection of pathogens consist of a high test time and a high sample consumption, but they ...are very expensive and require specialist operators. This study aims to develop a monitoring system capable of identifying waterborne pathogens with particular characteristics using a microfluidic device, optical imaging and a classification algorithm to provide low-cost and portable solutions. This paper investigates the detection of small size microbeads (1–5 µm) from a measured water sample by using a cost-effective microscopic camera and computational algorithms. Results provide areas of opportunities to decrease sample consumption, reduce testing time and minimize the use of expensive equipment.
Wireless Body Area Network (WBAN) has been a key element in e-health to monitor bodies. This technology enables new applications under the umbrella of different domains, including the medical field, ...the entertainment and ambient intelligence areas. This survey paper places substantial emphasis on the concept and key features of the WBAN technology. First, the WBAN concept is introduced and a review of key applications facilitated by this networking technology is provided. The study then explores a wide variety of communication standards and methods deployed in this technology. Due to the sensitivity and criticality of the data carried and handled by WBAN, fault tolerance is a critical issue and widely discussed in this paper. Hence, this survey investigates thoroughly the reliability and fault tolerance paradigms suggested for WBANs. Open research and challenging issues pertaining to fault tolerance, coexistence and interference management and power consumption are also discussed along with some suggested trends in these aspects.
Wireless Body Area Network (WBAN) has been a potential avenue for future digitized healthcare systems. WBAN has unique challenges and features compared to other wireless sensor networks. In addition ...to battery power consumption, the vulnerability and the unpredicted channel behaviour make channel access a serious problem. Time Division Multiple Access (TDMA) Medium Access Control (MAC) protocols can help in achieving a reliable and energy efficient WBAN. IEEE 802.15.4 provides TDMA based mechanisms to save energy consumption. However, both contention-free and inactive periods are static and do not consider channel status or nodes reliability requirements. Hence, this paper presents two IEEE 802.15.4 TDMA based techniques to improve WBAN reliability and energy efficiency. The first technique allows nodes to avoid channel deep fade by distributing adaptively their sleep period during their active period according to their channel status. Thereafter, in the second technique, nodes are dynamically allocated time slots according to their requirements, which depend on their link's status. The proposed techniques are evaluated within various traffic rates and their performances are compared with the legacy IEEE 802.15.4 MAC. Results reveal that the proposed techniques are able to promote the WBAN reliability and energy efficiency.
The resource-constrained nature of IoT objects makes the Routing Protocol for Low-power and Lossy Networks (RPL) vulnerable to several attacks. Although RPL specification provides encryption ...protection to control messages, RPL is still vulnerable to internal attackers and selfish behaviours. To address the lack of robust security mechanisms in RPL, we design a new Metric-based RPL Trustworthiness Scheme (MRTS) that introduces trust evaluation for secure routing topology construction. Extensive simulations show that MRTS is efficient in terms of packet delivery ratio, energy consumption, nodes’ rank changes, and throughput. In addition, a mathematical modelling analysis shows that MRTS meets the requirements of consistency, optimality, and loop-freeness and that the proposed trust-based routing metric has the isotonicity and monotonicity properties required for a routing protocol. By using game theory concepts, we formally describe MRTS as a strategy for the iterated Prisoner’s Dilemma and demonstrate its cooperation enforcement characteristic. Both mathematical analysis and evolutionary simulation results show clearly that MRTS, as a strategy, is an efficient approach in promoting the stability and the evolution of the Internet of Things network.
In RPL routing protocol, the destination advertisement object (DAO) control messages are announced by the child nodes to their parents to build downward routes. A malicious insider node can exploit ...this feature to send fake DAOs to its parents periodically, triggering those parents, in turn, to forward the fake messages upward to the root node. In this letter, we show how this behavior can have a detrimental side effect on the performance of the network, increasing power consumption, latency, and reducing reliability. To address this problem, a new scheme is introduced to mitigate significantly the effect of the DAO attack on network performance.
The IPv6 Routing Protocol for Low-Power and Lossy Networks (RPL) was standardised by the IETF ROLL Working Group to address the routing issues in the Internet of Things (IoT) Low-Power and Lossy ...Networks (LLNs). RPL builds and maintains a Destination Oriented Directed Acyclic Graph (DODAG) topology using pieces of information propagated within the DODAG Information Object (DIO) control message. When a node intends to join the DODAG, it either waits for DIO or sends a DODAG Information Solicitation (DIS) control message Multicast to solicit DIOs from nearby nodes. Nevertheless, sending Multicast DIS messages resets the timer that regulates the transmission rate of DIOs to its minimum value, which leads to the network’s congestion with control messages. Because of the resource-constrained nature of RPL-LLNs, the lack of tamper resistance, and the security gaps of RPL, malicious nodes can exploit the Multicast DIS solicitation mechanism to trigger an RPL-specification-based attack, named DIS attack. The DIS attack can have severe consequences on RPL networks, especially on control packets overhead and power consumption. In this paper, we use the Cooja–Contiki simulator to assess the DIS attack’s effects on both static and dynamic PRL networks. Besides, we propose and implement a novel approach, namely RPL-MRC, to improve the RPL’s resilience against DIS Multicast. RPL-MRC aims to reduce the response to DIS Multicast messages. Simulation results demonstrate how the attack could damage the network performance by significantly increasing the control packets overhead and power consumption. On the other hand, the RPL-MRC proposed mechanism shows a significant enhancement in reducing the control overhead and power consumption for different scenarios.
Internet of Things (IoT) has emerged as a key component of all advanced critical infrastructures. However, with the challenging nature of IoT, new security breaches have been introduced, especially ...against the Routing Protocol for Low-power and Lossy Networks (RPL). Artificial-Intelligence-based technologies can be used to provide insights to deal with IoT’s security issues. In this paper, we describe the initial stages of developing, a new Intrusion Detection System using Machine Learning (ML) to detect routing attacks against RPL. We first simulate the routing attacks and capture the traffic for different topologies. We then process the traffic and generate large 2-class and multi-class datasets. We select a set of significant features for each attack, and we use this set to train different classifiers to make the IDS. The experiments with 5-fold cross-validation demonstrated that decision tree (DT), random forests (RF), and K-Nearest Neighbours (KNN) achieved good results of more than 99% value for accuracy, precision, recall, and F1-score metrics, and RF has achieved the lowest fitting time. On the other hand, Deep Learning (DL) model, MLP, Naïve Bayes (NB), and Logistic Regression (LR) have shown significantly lower performance.
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