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Cybersecurity education is a crucial element to provide a workforce for the future to have an awareness together with the skills and knowledge enabling them to adapt and diversify in the field. Cybercrime is covered by the need for distinct aspects of security and measures of control on subsequent systems and devices. As the need for Cybersecurity specialists has increased in recent years and during the exceptional circumstances of the Covid-19 pandemic, the provision of education in secondary, post-16 and higher education sectors needs to be met. Utilisation of strategies and innovations to meet industry and educational expectations is key for future provision. Drive for different strategies and innovations in place by governments and organisations throughout the world, as provision in education is not balanced enough to cope with the increasing demand for a cybersecurity workforce. This study will inform recommendations for effective provision of future cybersecurity education.

The rising cyber threat puts organizations and ordinary users at risk of data breaches. In many cases, Early detection can hinder the occurrence of these incidents or even prevent a full compromise of all internal systems. The existing security controls such as firewalls and intrusion prevention systems are constantly blocking numerous intrusions attempts that happen on a daily basis. However, new situations may arise where these security controls are not sufficient to provide full protection. There is a necessity to establish a threat hunting methodology that can assist investigators and members of the incident response team to analyse malicious binaries quickly and efficiently. The methodology proposed in this research is able to distinguish malicious binaries from benign binaries using a quick and efficient way. The proposed methodology consists of static and dynamic hunting techniques. Using these hunting techniques, the proposed methodology is not only capable of identifying a range of signature-based anomalies but also to pinpoint behavioural anomalies that arise in the operating system when malicious binaries are triggered. Static hunting can describe any extracted artifacts as malicious depending on a set of pre-defined patterns of malicious software. Dynamic hunting can assist investigators in finding behavioural anomalies. This work focuses on applying the proposed threat hunting methodology on samples of malicious binaries, which can be found in common malware repositories and presenting the results.

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.

Low Power and Lossy Networks (LLNs) have a crucial role in the Internet of Things (IoT) paradigm. For the IPv6 Routing Protocol for LLNs (RPL), two objective functions (OF) have been standardized so far, namely (Objective Function zero (OF0), and the Minimum Rank with Hysteresis Objective Function (MRHOF). However, these particular objective functions are used to build a topology where bottleneck nodes may suffer from an excessive unbalanced traffic load. As a result, a part of the network may be disconnected as the energy of the overburdened preferred parent node will drain much faster than other candidate parent nodes. Thus, in this paper, we propose a new objective function that balances the number of children nodes for the overburdened nodes to ensure node lifetime maximization. To implement this OF, we amended the DIO message format. By using a new utilization technique, we also mitigated any potential extra overhead. Finally, a new RPL metric has been introduced to balance the traffic load over the network. Simulation experiments have been conducted to examine the performance of our new approach. Collected results corroborate the superiority of our objective function over the existing ones in terms of lifetime, power consumption and packet delivery ratio.

The CoRE Working Group has proposed a resource directory (RD) in the centralized resource discovery of the constrained application protocol (CoAP). This directory contains a description for resources held in the servers, in which the servers register their resources in the RD while the clients are allowed to perform a lookup operation on these resources, and ask for any resource using single request. In order of making the resource directory fully updated, all nodes are periodically sending update messages (after fixed period of time) to the RD contains the latest status of their information, these update messages will result in extra signaling overhead and consume more power from node's battery, this will drain the batteries and reduce the overall network lifetime. We have proposed a dynamic tuning technique to adjust the update message interval in CoAP, the proposed algorithm is depending on the battery level of the sending node, in which the update interval increased as battery level decreased. The results of experiments show that the dynamic approach can extend the network lifetime by 25%.

Constrained Low-power and Lossy networks (LLNs) represent the building block for the ever-growing Internet of Things (IoT) that deploy the Routing Protocol for Low Power and Lossy networks (RPL) as a key routing standard. RPL, along with other routing protocols, relies on Trickle algorithm as a mechanism for controlling and maintaining the routing traffic frequency. The efficiency of Trickle has been approved in terms of power consumption and scalability. However, different settings of Trickle parameters affect differently the routing behavior, energy consumption and network convergence time. In particular, a network could be only configured to have either lower convergence time with high power consumption or vice versa using Trickle. Thus, motivated by this observation, the paper presents Trickle-Plus as an extended version of the Trickle algorithm. Trickle-Plus increases the elasticity of the protocol, enabling the network configuration within guaranteed optimality for both convergence time and energy consumption. Our simulation experiments confirm the gains of the proposed Trickle-Plus under different operating conditions.

Recently, IETF standardised a powerful and flexible Routing Protocol for Low Power and Lossy Networks (RPL). It selects the ideal routes from a source to a destination node based on certain metrics injected into the Objective Function (OF). In this study, the performance of RPL has been investigated in terms of two OFs (i.e. Minimum Rank with Hysteresis Objective Function (MRHOF) and Objective Function Zero (OF0)) in various topologies (grid, random) which makes this work distinctive. To study the RPL OFs performance, various parameters are considered Packet Delivery Ratio (PDR), Power Consumption and RX. The evaluation has been conducted based on these parameters (RX, topology) and compared for both OFs. The simulation results revealed that these parameters have a great impact on the PDR and achieved saved energy levels in the given networks. Our results have also indicated that the performance of RPL within light density networks for MRHOF can provide a better RPL behavior that OF0 could not provide.

Constrained application protocol (CoAP) has been designed for M2M and IoT applications. The resource directory (RD) in CoAP requires periodical updates by other nodes. However, a regular update process causes extra signaling overhead and drains the node's battery, which consequently reduces the battery lifetime of all nodes. Thus, there is a need to adjust the update interval to prolong the lifetime of the entire network. Although this problem has been investigated in the literature, it is still in its infancy as existing works do not consider the dynamic periodic adjustments of the update messages. To fill in this gap, this paper devise a new adaptive tuning approach between CoAP clients and their CoAP-RD to adjust the frequency of updates based on the battery level of the transmitting node. We evaluated our protocol using simulation experiments. The simulation results confirm that the adaptive tuning approach outperforms its traditional counterpart by 10 to 15% with respect to the overall network lifetime.

Energy is a precious resource in Internet of Things (IoT) especially with battery operated nodes, the overhead that consumes the battery power of the sensor nodes is a fundamental problem. This overhead is mainly caused by the frequent update messages sent to service directories. Although this problem has been investigated in the literature, it is still in its infancy as existing works do not consider the dynamic adjustments of the update messages. To fill in this gap, this paper presents a new adaptive tuning approach between sensor nodes and the resource directory to adjust the frequency of updates based on the battery level of the sensing node. Our protocol works dynamically in both modes, stateless and stateful service registration mechanisms.