Systems architecture for the acquisition and preservation of wireless network traffic

Wireless networking provides a ready and cost effective solution for business applications. It has escalated in popularity mainly due to the ability to form computer networks without a wired based infrastructure. However, accompanying the widespread usage also comes the inherent prospect of criminal misuse, including unauthorized application and the launch of system attacks. This paper presents the testing of an innovative Wireless Forensic Model (WFM) system that provides capability for acquisition and preservation of wireless network traffic (802.11) frames by implementing a wireless drone architecture. It is thus a forensic readiness system providing available evidence for forensic investigation. The results show that the tested system has the ability to collect upwards of 90% of all frames, as well as evidence and detection of attacks conducted against the wireless network

Digital forensic readiness for wireless sensor network environments

The new and upcoming field of wireless sensor networking is unfortunately still lacking in terms of both digital forensics and security. All communications between different nodes (also known as motes) are sent out in a broadcast fashion. These broadcasts make it quite difficult to capture data packets forensically and, at the same time, retain their integrity and authenticity. The study presents several attacks that can be executed successfully on a wireless sensor network, after which the dissertation delves more deeply into the flooding attack as it is one of the most difficult attacks to address in wireless sensor networks. Furthermore, a set of factors is presented to take into account while attempting to achieve digital forensic readiness in wireless sensor networks. The set of factors is subsequently discussed critically and a model is proposed for implementing digital forensic readiness in a wireless sensor network. The proposed model is next transformed into a working prototype that is able to provide digital forensic readiness to a wireless sensor network. The main contribution of this research is the digital forensic readiness prototype that can be used to add a digital forensics layer to any existing wireless sensor network. The prototype ensures the integrity and authenticity of each of the data packets captured from the existing wireless sensor network by using the number of motes in the network that have seen a data packet to determine its integrity and authenticity in the network. The prototype also works on different types of wireless sensor networks that are in the frequency range of the network on which the prototype is implemented, and does not require any modifications to be made to the existing wireless sensor network. Flooding attacks pose a major problem in wireless sensor networks due to the broadcasting of communication between motes in wireless sensor networks. The prototype is able to address this problem by using a solution proposed in this dissertation to determine a sudden influx of data packets within a wireless sensor network. The prototype is able to detect flooding attacks while they are occurring and can therefore address the flooding attack immediately. Finally, this dissertation critically discusses the advantages of having such a digital forensic readiness system in place in a wireless sensor network environment. CopyrightDissertation (MSc)--University of Pretoria, 2012.Computer Scienceunrestricte

The modelling of a digital forensic readiness approach for Wireless Local Area Networks

Over the past decade, wireless mobile communication technology based on the IEEE 802.11 Wireless Local Area Networks (WLANs) has been adopted worldwide on a massive scale. However, as the number of wireless users has soared, so has the possibility of cybercrime. WLAN digital forensics is seen as not only a response to cybercrime in wireless networks, but also a means to stem the increase of cybercrime in WLANs. The challenge in WLAN digital forensics is to intercept and preserve all the communications generated by the mobile stations and to conduct a proper digital forensic investigation. This paper attempts to address this issue by proposing a wireless digital forensic readiness model designed to monitor, log and preserve wireless network traffic for digital forensic investigations. Thus, the information needed by the digital forensic experts is rendered readily available, should it be necessary to conduct a digital forensic investigation. The availability of this digital information can maximise the chances of using it as digital evidence and it reduces the cost of conducting the entire digital forensic investigation process.The Council for Scientific and Industrial Research (CSIR) and University of Pretoria, South Africa.http://www.jucs.org

Digital Forensic Readiness in Organizations: Issues and Challenges

With the evolution in digital technologies, organizations have been forced to change the way they plan, develop, and enact their information technology strategies. This is because modern digital technologies do not only present new opportunities to business organizations but also a different set of issues and challenges that need to be resolved. With the rising threats of cybercrimes, for example, which have been accelerated by the emergence of new digital technologies, many organizations as well as law enforcement agencies globally are now erecting proactive measures as a way to increase their ability to respond to security incidents as well as create a digital forensic ready environment. It is for this reason that, this paper presents the different issues and challenges surrounding the implementation of digital forensic readiness in organizations. The main areas of concentration will be: the different proactive measures that organizations can embrace as a way to increase the ability to respond to security incidents and create a digital forensic ready environment. However, the paper will also look into the issues and challenges pertaining to data retention and disposition in organizations which may also have some effects on the implementation of digital forensic readiness. This is backed up by the fact that although the need for digital forensics and digital evidence in organizations has been explored, as has been the need for digital forensic readiness within organizations, decision-makers still need to understand what is needed within their organizations to ensure effective implementation of digital forensic readiness

Adding Digital Forensic Readiness as a Security Component to the IoT Domain

The unique identities of remote sensing, monitoring, self-actuating, self–adapting and self-configuring “things” in Internet of Things (IoT) has come out as fundamental building blocks for the development of “smart environments”. This experience has begun to be felt across different IoT-based domains like healthcare, surveillance, energy systems, home appliances, industrial machines, smart grids and smart cities. These developments have, however, brought about a more complex and heterogeneous environment which is slowly becoming a home to cyber attackers. Digital Forensic Readiness (DFR) though can be employed as a mechanism for maximizing the potential use of digital evidence while minimizing the cost of conducting a digital forensic investigation process in IoT environments in case of an incidence. The problem addressed in this paper, therefore, is that at the time of writing this paper, there still exist no IoT architectures that have a DFR capability that is able to attain incident preparedness across IoT environments as a mechanism of preparing for post-event response process. It is on this premise, that the authors are proposing an architecture for incorporating DFR to IoT domain for proper planning and preparing in the case of security incidents. It is paramount to note that the DFR mechanism in IoT discussed in this paper complies with ISO/IEC 27043: 2015, 27030:2012 and 27017: 2015 international standards. It is the authors’ opinion that the architecture is holistic and very significant in IoT forensics

Are You Ready? A Proposed Framework For The Assessment Of Digital Forensic Readiness

This dissertation develops a framework to assess Digital Forensic Readiness (DFR) in organizations. DFR is the state of preparedness to obtain, understand, and present digital evidence when needed. This research collects indicators of digital forensic readiness from a systematic literature review. More than one thousand indicators were found and semantically analyzed to identify the dimensions to where they belong. These dimensions were subjected to a q-sort test and validated using association rules, producing a preliminary framework of DFR for practitioners. By classifying these indicators into dimensions, it was possible to distill them into 71 variables further classified into either extant or perceptual variables. Factor analysis was used to identify latent factors within the two groups of variables. A statistically-based framework to assess DFR is presented, wherein the extant indicators are used as a proxy of the real DFR status and the perceptual factors as the perception of this status

DIGITAL FORENSIC READINESS FRAMEWORK BASED ON HONEYPOT AND HONEYNET FOR BYOD

The utilization of the internet within organizations has surged over the past decade. Though, it has numerous benefits, the internet also comes with its own challenges such as intrusions and threats. Bring Your Own Device (BYOD) as a growing trend among organizations allow employees to connect their portable devices such as smart phones, tablets, laptops, to the organization’s network to perform organizational duties. It has gained popularity over the years because of its flexibility and cost effectiveness. This adoption of BYOD has exposed organizations to security risks and demands proactive measures to mitigate such incidents. In this study, we propose a Digital Forensic Readiness (DFR) framework for BYOD using honeypot technology. The framework consists of the following components: BYOD devices, Management, People, Technology and DFR. It is designed to comply with ISO/IEC 27043, detect security incidents/threats and collect potential digital evidence using low- and high-level interaction honeypots. Besides, the framework proffers adequate security support to the organization through space isolation, device management, crypto operations, and policies database. This framework would ensure and improve information security as well as securely preserve digital evidence. Embedding DFR into BYOD will improve security and enable an organization to stay abreast when handling a security incident

Proceedings of the 15th Australian Digital Forensics Conference, 5-6 December 2017, Edith Cowan University, Perth, Australia

Conference Foreword This is the sixth year that the Australian Digital Forensics Conference has been held under the banner of the Security Research Institute, which is in part due to the success of the security conference program at ECU. As with previous years, the conference continues to see a quality papers with a number from local and international authors. 8 papers were submitted and following a double blind peer review process, 5 were accepted for final presentation and publication. Conferences such as these are simply not possible without willing volunteers who follow through with the commitment they have initially made, and I would like to take this opportunity to thank the conference committee for their tireless efforts in this regard. These efforts have included but not been limited to the reviewing and editing of the conference papers, and helping with the planning, organisation and execution of the conference. Particular thanks go to those international reviewers who took the time to review papers for the conference, irrespective of the fact that they are unable to attend this year. To our sponsors and supporters a vote of thanks for both the financial and moral support provided to the conference. Finally, to the student volunteers and staff of the ECU Security Research Institute, your efforts as always are appreciated and invaluable. Yours sincerely, Conference ChairProfessor Craig ValliDirector, Security Research Institute Congress Organising Committee Congress Chair: Professor Craig Valli Committee Members: Professor Gary Kessler – Embry Riddle University, Florida, USA Professor Glenn Dardick – Embry Riddle University, Florida, USA Professor Ali Babar – University of Adelaide, Australia Dr Jason Smith – CERT Australia, Australia Associate Professor Mike Johnstone – Edith Cowan University, Australia Professor Joseph A. Cannataci – University of Malta, Malta Professor Nathan Clarke – University of Plymouth, Plymouth UK Professor Steven Furnell – University of Plymouth, Plymouth UK Professor Bill Hutchinson – Edith Cowan University, Perth, Australia Professor Andrew Jones – Khalifa University, Abu Dhabi, UAE Professor Iain Sutherland – Glamorgan University, Wales, UK Professor Matthew Warren – Deakin University, Melbourne Australia Congress Coordinator: Ms Emma Burk

Precognition: Automated Digital Forensic Readiness System for Mobile Computing Devices in Enterprises

Enterprises are facing an unprecedented risk of security incidents due to the influx of emerging technologies, like smartphones and wearables. Most of the current Mobile security systems are not maturing in pace with technological advances. They lack the ability to learn and adapt from the past knowledge base. In the case of a security incident, enterprises find themselves underprepared for the lack of evidence and data. The systems are not designed to be forensic ready. There is a need for automated security analysis and forensically ready solution, which can learn and continuously adapt to new challenges, improve efficiency and productivity of the system. In this research, the authors have designed a security analysis and digital forensic readiness system targeted at smartphones and wearables in an enterprise environment. The proposed system detects applications violating security policies, analyzes Android and iOS applications to identify possible vulnerabilities on the server, apply machine learning algorithms to improve the efficiency and accuracy of vulnerability prediction. The System continuously learns from past incidents, proactively collect required information from the devices which can help in digital forensics. Machine learning techniques are applied to the set of features extracted from the decompiled Mobile applications and applications classified based on consisting of one or more vulnerabilities. The system was evaluated in a real-world enterprise environment with 14151 mobile applications and vulnerabilities was predicted with an accuracy of 94.2%. The system can also work on virtual instances of the mobile devices