Naimah Yaakob

Internet of Things (IoT): Taxonomy of security attacks

The Internet of Things (IoT) comprises a complex network of smart devices, which frequently exchange data through the Internet. Given the significant growth of IoT as a new technological paradigm, which may involve safety-critical operations and sensitive data to be put online, its security aspect is vital. This paper studies the network security matters in the smart home, health care and transportation domains. It is possible that the interruption might occur in IoT devices during operation causing them to be in the shutdown mode. Taxonomy of security attacks within IoT networks is constructed to assist IoT developers for better awareness of the risk of security flaws so that better protections shall be incorporated.

Energy-Efficient Remote Healthcare Monitoring Using IoT: A Review of Trends and Challenges

The emergence of Internet and technologies such as Wireless Sensor Network (WSN) has created another platform of Wireless Body Area Network (WBAN) and also an ever growing new area of Internet of Thing (IoT). A WBAN offers a flexibility and mobility to health monitoring system. Most of WBAN is made up of several small and light-weighted battery-operated sensor nodes and lead to energy-constrained system. Thus, an energy-efficient WBAN system is crucially needed to make the network last longer. In addition, data reliability and data transmission is important to make the system more effective. IoT concept helps in forming an interaction of things in the surrounding as well as support data storage (database) for collected vital body sign by the sensors. In this paper, we review the concept and design of energy-efficient WBAN and contribution of IoT in healthcare monitoring system.

On the effectiveness of congestion control mechanisms for remote healthcare monitoring system in IoT environment — A review

A progressive advancement in biosensors and wireless technology are the major contributors to the realization of continuous remote health monitoring system (RHMS). Wireless Body Area Network (WBAN) is part of this technology due to the deployment of multiple sensors such as Electrocardiogram (ECG) to collect vital body signals for processing and diagnosis. Among the benefits offered by this technology include remote monitoring of patients health status and early detection of abnormalities in the collected signals. Once detected, several preventive measurements can be taken. However, this system needs to encounter some challenges in the wireless network such as delay, packet loss and throughput due to network congestion when transmitting and receiving a bulk of multiple data. Generally, the presence of these problems in transmitting vital body signals may result in incorrect medical diagnosing which can increase mortality rate and cause severe impact to the overall systems performance. Thus, a suitable design of congestion control mechanism is urgently needed in designing a reliable and efficient remote health monitoring system.

Performance Investigation of Joint User-Proportional Fair Scheduling Algorithm in LTE-Advanced System with Carrier Aggregation

Carrier Aggregation (CA) is a promising technology that proposed by 3GPP in the latest LTEAdvanced (LTE-A) criterions in order to satisfy the future IMT-Advanced mobile networks demands. While CA allows aggregation of component carriers (CCs) dispersed within and transversely in diverse bands (intra/inter-band), CA is expected to offer a powerful boost to the user throughput in LTEAdvanced system. In addition, it will permit the achievement of the target peak data rates in excess of 1 Gbps in the downlink and 500 Mbps in the uplink in which the users has the right to use up to 100 MHz total of bandwidth. The mixture of LTE-A and LTE users within a multi-carrier LTE-A network may perhaps exist simultaneously. Each of them has various CA capabilities. The former has the ability to assign on multiple CCs, whereas the later can allocate on one CC. Moreover, they demand diverse QoS requirements which present new challenges to optimize the performance of LTE-Advanced system. Therefore, the choice of scheduling strategies plays a key role in guaranteeing desirable end to end system performance. The study of this paper will be beneficial for understanding the radio resource management (RRM) function with carrier aggregation feature. In addition, this article presents the Joint UserProportional Fair scheduling scheme (JUS-PF) for resource allocation and its impacts on two deployment scenarios which are LTE-A users and mixture (LTE/LTE-A) users’ scenario in terms of average user throughput, cell edge user throughput, and fairness.

Image Classification for Snake Species Using Machine Learning Techniques

This paper investigates the accuracy of five state-of-the-art machine learning techniques — decision tree J48, nearest neighbors, k-nearest neighbors (k-NN), backpropagation neural network, and naive Bayes — for image-based snake species identification problem. Conventionally, snake species identification is conducted manually based on the observation of the characteristics such head shape, body pattern, body color, and eyes shape. Images of 22 species of snakes that can be found in Malaysia were collected into a database, namely the Snakes of Perlis Corpus. Then, an intelligent approach is proposed to automatically identify a snake species based on an image which is useful for content retrieval purpose where a snake species can be predicted whenever a snake image is given as input. Our experiment shows that backpropagation neural network and nearest neighbour are highly accurate with greater than 87 % accuracy on CEDD descriptor in this problem.

Performances of Machine Learning Algorithms for Binary Classification of Network Anomaly Detection System

The rapid growth of technologies might endanger them to various network attacks due to the nature of data which are frequently exchange their data through Internet and large-scale data that need to be handle. Moreover, network anomaly detection using machine learning faced difficulty when dealing the involvement of dataset where the number of labelled network dataset is very few in public and this caused many researchers keep used the most commonly network dataset (KDDCup99) which is not relevant to employ the machine learning (ML) algorithms for a classification. Several issues regarding these available labelled network datasets are discussed in this paper. The aim of this paper to build a network anomaly detection system using machine learning algorithms that are efficient, effective and fast processing. The finding showed that AODE algorithm is performed well in term of accuracy and processing time for binary classification towards UNSW-NB15 dataset.

Performance Analysis of Single and Multi-controller using OpenFlow Protocol for SoftwareDefined Networks

A Software Defined Network (SDN) is a relatively advanced way to implement communication networks. The decision making SDN separates the control layer, which determines where the packets are sent, from the basic infrastructure (also known as the infrastructure layer or data plan) which restores the packets to the specified destination. The newly emerging standard for enactment is the OpenFlow protocol, which contains a standard protocol for communications between the control layer and the infrastructure layer. This study analyzes the impact of OpenFlow single and multi-controllers on the performance of the OpenFlow protocol network. The research was conducted using the discrete event network simulation, omnet++, and involved analyzing the main network metrics including End to End Delay and Throughput. The results indicate that the type of controller used has a clear impact on the performance of the network.

QoS Based Independent Carrier Scheduling Scheme for Heterogeneous Services in 5G LTE-Advanced Networks

Efficient user-level QoS provisioning for heterogeneous services is of vital importance in future 5G Long-Term Evolution-Advanced (LTE-A) with Carrier Aggregation (CA) mobile system. The CA is very vital technique which invented by 3GPP for creating the huge virtual carrier bandwidths to support the 5G LTE-A network with unprecedented speed of data transmission and minimal latency. To the best of our knowledge, in order to support and fulfill the user level QoS obligations for diversified services “Real-Time (RT) and Non-Real-Time (NRT)”, one of the main challenges in the presence of CA is to offer robust and suitable resource scheduling scheme. In this paper, the authors propose an efficient scheduling scheme, termed as “QoS based Independent Carrier (QoS-IC)” by designing Round-Robin with Service (RR-S) method for ensuring the load balancing based on the user’s service in 5G LTE-A system. In addition, a user-level Quality of Service aware packet scheduling for OFDMA resource blocks suitable to multi-services system is proposed by introducing the service utility factor. The design objective is to guarantee the user quality of service (QoS) and equitable allocation of radio resources among users. Extensive simulation outcomes demonstrate that our scheduling algorithm offers significantly better QoS performance in terms of packet drop rate (PDR), variance of packet drop rate, and the average packet delay for RT traffic as well as satisfying the minimum transmission rate demand for NRT traffic.

Congestion control mechanism for Internet-of-Things (IOT) paradigm

Wireless Sensor Network (WSN) is one of the Internet-of-Things (IoT) paradigms which provide monitoring services for natural disasters such as volcanoes eruption and earthquake which can affect the life of human being. As such, the Quality-of-Service (QoS) of the underlying applications is of important issue in order to ensure its effectiveness and robustness. Besides its undoubtedly services and contributions in monitoring systems, WSNs limited resources can severely degrade the QoS in IoT applications. Congestion in WSN will further reduce the expected QoS of the associated applications. In this case, efficient used of the scarce resources is important to ensure seamless data transmission. The power consumption of a sensor node can be reduced by reducing the rate of packet retransmission which is caused by congestion. In this paper, a selective packet discarding method which is known as Packet Discarding based Node Clustering (PDNC) is introduced. All nodes deployed in the targeted area will be clustered into several groups and a cluster head will be selected at a time. The packet discarding process will then be carried at each node to reduce the number of packets contributing to congestion. Simulation analysis using NS-2 shows that the proposed technique is able to reduce congestion thus improve the overall performance.