Michael N. Johnstone

The E-book Power User in Academic and Research Libraries: Deep Log Analysis and User Customisation

In the literature on e-book adoption in academic and research libraries, user acceptance is seldom rigorously examined. As take-up of e-books has grown to achieve mass adoption, what industry analysts Gartner describe as the “plateau of productivity”, the question of user acceptance may seem less relevant. However, if attention is switched from downloads to information behaviour, expectations and gratification, the picture of acceptance is more nuanced, with some studies pointing towards user disaffection.This paper reports on the information behaviour of another category of e-book users, i.e. apparently satisfied or intensive users. The paper is based on data analysis and interpretation of data from transaction logs generated by the Ebook Library (EBL) platform in an academic library. The paper forms part of a broader investigation of technology acceptance and options for improving the user experience of e-books within an academic library context. Three years of e-books transaction logs were mined for ev...

Security Aspects of Military Sensor-Based Defence Systems

The Australian Defence Force has IMAP and JMAP to perform planning prior to the deployment of forces, but due to the dynamic nature of modern warfare there is a knowledge and security gap for on-ground forces during the execution of an operation. Multi-agent based sensor systems can provide on-ground forces with a significant amount of real-time information that can be used to modify planning due to changed conditions. Future planning will require automated agents planners capable of semi-autonomous generated plans and courses of action. Multi-agent sensor systems will also provide cyber security and management of system performance and human C2 workload. This will become a critical C3 ISTAR capability as multi-agents are faster than humans for path planning and resource allocation in multivariate, dynamic, time-pressured environments. The issue with such sensor systems is the degree to which they are vulnerable to attack by opposing forces. This paper explores the types of attack that could be successful using the IEEE 802.15.4 protocol as an example and proposes defences that could be put in place to circumvent or minimise the effect of an attack.

Towards effective algorithms for intelligent defense systems

With the volume of data required to be analysed and interpreted by security analysts, the possibility of human error looms large and the consequences possibly harmful for some systems in the event of an adverse event not being detected. In this paper we suggest machine learning algorithms that can assist in supporting the security function effectively and present a framework that can be used to choose the best algorithm for a specific domain. A qualitative framework was produced, and it is suggested that a naive Bayesian classifier and artificial neural network based algorithms are most likely the best candidates for the proposed application. A testing framework is proposed to conduct a quantitative evaluation of the algorithms as the next step in the determination of best fit for purpose algorithm. Future research will look to repeat this process for cyber security specific applications, and also examine GPGPU optimisations.

Security Issues with BACnet Value Handling.

Building automation systems, or building management systems, control services such as heating, airconditioning and security access in facilities. A common protocol used to transmit data regarding the status of components is BACnet. Unfortunately, whilst security is included in the BACnet standard, it is rarely implemented by vendors of building automation systems. This lack of attention to security can lead to vulnerabilities in the protocol being exploited with the result that the systems and the buildings they control can be compromised. This paper describes a proof-of-concept protocol attack on a BACnet system and examines the potential of modeling the basis of the attack.

An exploration of some security issues within the BACnet protocol

Building automation systems control a range of services, commonly heating, ventilation and air-conditioning. BACnet is a leading protocol used to transmit data across building automation system networks, for the purpose of reporting and control. Security is an issue in BACnet due to its initial design brief which appears to be centred around a centralised monolithic command and control architecture. With the advent of the Internet of Things, systems that were isolated are now interconnected. This interconnectivity is problematic because whilst security is included in the BACnet standard, it is not implemented by vendors of building automation systems. The lack of focus on security can lead to vulnerabilities in the protocol being exploited with the result that the systems and the buildings they control are open to attack. This paper describes two proof-of-concept protocol attacks on a BACnet system, proves one attack using experimentation and the other attack through simulation. The paper contextualises a range of identified attacks using a threat model based on the STRIDE threat taxonomy.

A comparison of 2D and 3D Delaunay triangulations for fingerprint authentication

The two-dimensional (2D) Delaunay triangulation-based structure, i.e., Delaunay triangle, has been widely used in fingerprint authentication. However, we also notice the existence of three-dimensional (3D) Delaunay triangulation, which has not been extensively explored. Inspired by this, in this paper, the features of both 2D and 3D Delaunay triangulation-based structures are investigated and the findings show that a 3D Delaunay structure, e.g., Delaunay tetrahedron, can provide more feature types and a larger number of elements than a 2D Delaunay structure, which was expected to provide a higher discriminative capability. However, higher discrimination does not necessarily lead to better performance, especially in biometric applications, when biometric uncertainty is unavoidable. Experimental results show that the biometric uncertainty such as missing or spurious minutiae causes more negative influence on the 3D Delaunay triangulation than that on the 2D Delaunay triangulation in three out of four experimental data sets.

An investigation into some security issues in the DDS messaging protocol

The convergence of Operational Technology and Information Technology is driving integration of the Internet of Things and Industrial Control Systems to form the Industrial Internet of Things. Due to the influence of Information Technology, security has become a high priority particularly when implementations expand into critical infrastructure. At present there appears to be minimal research addressing security considerations for industrial systems which implement application layer IoT messaging protocols such as Data Distribution Services (DDS). Simulated IoT devices in a virtual environment using the DDSI-RTPS protocol were used to demonstrate that enumeration of devices is possible by a non-authenticated client in both active and passive mode. Further, modified sequence numbers were found to be a potential denial of service attack, and malicious heartbeat messages were fashioned to be effective at denying receipt of legitimate messages.

The effectiveness of classification algorithms on IPv6 IID construction

This study assessed the effectiveness of classifying IPv6 interface identifier (IID) address construction using machine learning algorithms. It was observed that IID construction can be reliably determined through the usage of assisted machine learning algorithms such as the naive Bayesian classifiers (NBC) or artificial neural networks (ANNs). It was also observed that the NBC classification, whilst more efficient, was less accurate than the use of ANN for classifying interface identifiers. Training times for an unoptimised ANN were seen to be far greater than NBC, which may be a considerable limitation to its effectiveness in real world applications (such as log or traffic analysis). Future research will continue to improve the classification training times for ANN situations, potentially involving general-purpose computing on graphics processing units (GPGPU) systems, as well as applying the techniques to real world applications such as IPv6 IDS sensors, honeypots or honeynets.

Revisiting Urban War Nibbling: Mobile Passive Discovery of Classic Bluetooth Devices Using Ubertooth One

The ubiquitous nature of Bluetooth technology presents opportunities for intelligence gathering based on historical and real-time device presence data. This information can be of value to law enforcement agencies, intelligence organizations, and industry. Despite the introduction of the Bluetooth Low Energy standard that incorporates anonymity preservation mechanisms, the presence of devices that support Classic Bluetooth that uses unique and persistent device identifiers is expected to remain significant for a number of years. The common approach to finding discoverable Classic Bluetooth devices relies on a standard inquiry process that is not truly passive. Furthermore, this approach fails to detect devices that remain undiscoverable. Ubertooth One, a low-cost open source Bluetooth development platform, can assist with overcoming this limitation in a truly passive manner, making it an attractive digital forensic instrument. Using vehicle-based sensors and parallel multi-method device discovery, we conduct a practical evaluation of Ubertooth One for passive discovery and contrast its discovery rate to the standard method. Based on 83 comparative field experiments, we show that Ubertooth One can produce forensically sound observations while able to discover up to ten times as many devices. We also show that this method can identify repeat device presence, as we observe 2370 instances of repeat observations on different days in single and multiple location scenarios. We conclude that this passive technique can complement the standard method and has the potential be used as a viable alternative.

Controlled Android Application Execution for the IoT Infrastructure

Android malware has grown in exponential proportions in recent times. Smartphone operating systems such as Android are being used to interface with and manage various IoT systems, such as building management and home automation systems. In such a hostile environment the ability to test and confirm device health claims is important to preserve confidentiality of user data. This paper describes a study to determine whether an Android device could be secured to prevent malware from executing in parallel with trusted applications. The research also sought to determine whether the system image could be protected from unauthorised modifications. A prototype scheme for meeting the above requirements was developed and tested. It was observed that the prototype succeeded in preventing unauthorised modification to the system image of the test device. However, the prototype failed to prevent unauthorised IPC calls when in single process mode.