Showing papers in "Computer Networks in 2019"

TL;DR: This paper presents an analysis of recent research in IoT security from 2016 to 2018, its trends and open issues, and the relevant tools, modellers and simulators.

TL;DR: A technical taxonomy is presented for the IoT applications approaches according to the content of current studies that are selected with SLR process in this study including health care, environmental monitoring, smart city, commercial, industrial and general aspects in IoT applications.

TL;DR: Recent and in-depth research of relevant works that deal with several intelligent techniques and their applied intrusion detection architectures in computer networks with emphasis on the Internet of Things and machine learning are aimed at.

TL;DR: From the experiments conducted in this research work using the proposed model, it is proved that the proposed routing algorithm provided better network performance in terms of the metrics namely energy utilization, packet delivery ratio, delay and network lifetime.

TL;DR: The state-of-the-art of the network architecture topology and applications in the IoT based healthcare solutions, including privacy, authentication, energy, power, resource management, Quality of Services and the real-time wireless health monitoring are reviewed.

TL;DR: Experimental results show that the proposed hybrid dimensionality reduction method with the ensemble of the base learners contributes more critical features and significantly outperforms individual approaches, achieving high accuracy and low false alarm rates.

TL;DR: Results obtained prove that the proposed scheme is effective for trading the energy between EVs and CS while securing the underlying trading transactions using blockchain, and the communication and computation cost of the proposed framework comes out to be small which proves that it can be used in real-world applications.

TL;DR: A novel multimodal DL framework for encrypted TC is proposed, named MIMETIC, able to capitalize traffic data heterogeneity (by learning both intra- and inter-modality dependences), overcome performance limitations of existing (myopic) single- modality DL-based TC proposals, and support the challenging mobile scenario.

TL;DR: A Systematic Literature Review (SLR) of the IDSs in the IoT environment has been presented and detailed categorizations of theIDSs (anomaly-based, signature-based), (centralized, distributed, hybrid), (simulation, theoretical), (denial of service attack, Sybil attack, replay attack, selective forwarding attack, worm hole attack, sinkhole attack, jamming attack, false data attack) have been provided using common features.

TL;DR: The routing protocols, mobility and trajectory optimization models that have been used in FANet to solve communication and collaboration issues between UAVs are exposed, the security challenges that need to be overcome are outlined and FANET networking open issues are discussed.

TL;DR: This work presents the first application of adversarial reinforcement learning for intrusion detection, and provides a novel technique that incorporates the environment's behavior into the learning process of a modified reinforcement learning algorithm.

TL;DR: Simulation results show that the new algorithm exhibits superior connectivity, power consumption validity, clustering interference, and network performance, can effectively reduce the overall power consumption and prolong the lifetime of the network, thus ensure the monitoring data transmitted to the monitoring center rapidly and quickly.

TL;DR: A novel cyber-physical system spanning ground, air, and space, called the Internet of Space Things/CubeSats (IoST) is introduced, envisioned as a means to achieving global connectivity at low costs, which is further bolstered by the use of Software-Defined Networking and Network Function Virtualization.

TL;DR: A new authentication technique for communication on the Internet of Things (IoT) using simple XOR and one-way Cryptographic hash function is introduced, which not only provides security but also maintains equilibrium between the efficiency and communication cost.

TL;DR: The results show that the proposed Deep Multi-Scale Learning Model is superior to the current state-of-the-art models in top-1 accuracy, recall and f1-score, and can help to understand mobility accurately.

TL;DR: A real time violence detection system is proposed which processes the huge input streaming data and recognize the violence with human intelligence simulation and it proves the sturdiness of the system with an accuracy of 94.5 percentage in recognizing the violent action.

TL;DR: This paper proposes an efficient approach to generate fingerprints of IoT devices based on neural network algorithms, and uses those device fingerprints to discover 15.3 million network-connected devices and analyze their distribution characteristics in cyberspace.

TL;DR: An Internet of Things (IoT) framework for the classification of stroke from CT images applying Convolutional Neural Networks (CNN) in order to identifying a healthy brain, an ischemic stroke or a hemorrhagic stroke is presented.

TL;DR: Experimental results demonstrate that the proposed model achieve higher evaluation accuracy than the existing reference models, but it also provides a promising solution to future physical fitness evaluation for teenagers through a machine-learning-model based intelligent computing instead of traditional empirical- model based manual calculation.

TL;DR: This work presents a formal study of LoRaWAN security, an increasingly popular technology, which defines the structure and operation of LPWAN networks based on the LoRa physical layer, and develops realistic models that can be used and extended to formally analyze, inspect, and explore the security features of the protocols.

TL;DR: The paper makes an in-depth analysis of the latest development in IoT security by observing from data perspectives, summarizing open issues and suggesting promising directions for further research and applications of IoT security.

TL;DR: This paper presents a comprehensive survey and taxonomy of the existing security solutions for V2X communication technology, and provides discussions and comparisons with regard to some pertinent criteria.

TL;DR: It can be concluded that the proposed CMMA not only minimize the energy utilization of edge-computing based IoMT systems but it also uniformly distribute cluster heads in the network so to increase its network lifetime.

TL;DR: A range of techniques related to mobile robots in WSNs are reviewed, divided into three categories according to the tasks that are executed by mobile robots, and the relationship among different solutions is outlined.

TL;DR: A privacy-preserving raw data collection scheme for IoT is proposed, in which the participant's data is collected and obfuscated with the other participants’ data within a group in order to mask the individual's privacy.

TL;DR: A novel hybrid framework based on data stream approach for detecting DDoS attack with incremental learning is proposed and the naive Bayes, random forest, decision tree, multilayer perceptron (MLP), and k-nearest neighbors (K-NN) on the proxy side to make better results.

TL;DR: A method has been developed for real-time in situ estimation of relative permittivity of soil, and soil moisture, that is determined from the propagation path loss, and velocity of wave propagation of an underground (UG) transmitter and receiver link in wireless underground communications (WUC).

TL;DR: A classification module for video streaming traffic, based on machine learning, is presented as a solution for network schemes that require adequate real-time traffic treatment and adopts a new approach for the relaxation of the hypothesis of independence between the attributes of the Naive Bayes algorithm.

TL;DR: A novel concept for enhancing the capabilities of ITS via the newly proposed 5G-based SDN architecture for ITS is presented and simulation results show that the proposed system architecture achieves better results than the ad-hoc on-demand distance vector routing protocol.

TL;DR: A Range-dependent Regulated Transmission (RRT) with doze formulation improves the communication time and rate of the road side relay units but adjusting the communication factors with respect to the vehicle requirements.