Digital forensic readiness intelligence crime repository

It may not always be possible to conduct a digital (forensic) investigation post-event if there is no process in place to preserve potential digital evidence. This study posits the importance of digital forensic readiness, or forensic-by-design, and presents an approach that can be used to construct a Digital Forensic Readiness Intelligence Repository (DFRIR). Based on the concept of knowledge sharing, the authors leverage this premise to suggest an intelligence repository. Such a repository can be used to cross-reference potential digital evidence (PDE) sources that may help digital investigators during the process. This approach employs a technique of capturing PDE from different sources and creating a DFR repository that can be able to be shared across diverse jurisdictions among digital forensic experts and law enforcement agencies (LEAs), in the form of intelligence. To validate the approach, the study has employed a qualitative approach based on a number of metrics and an analysis of experts\u27 opinion has been incorporated. The DFRIR seeks to maximize the collection of PDE, and reducing the time needed to conduct forensic investigation (e.g., by reducing the time for learning). This study then explains how such an approach can be employed in conjunction with ISO/IEC 27043: 2015

Quantifying the need for supervised machine learning in conducting live forensic analysis of emergent configurations (ECO) in IoT environments

© 2020 The Author(s) Machine learning has been shown as a promising approach to mine larger datasets, such as those that comprise data from a broad range of Internet of Things devices, across complex environment(s) to solve different problems. This paper surveys existing literature on the potential of using supervised classical machine learning techniques, such as K-Nearest Neigbour, Support Vector Machines, Naive Bayes and Random Forest algorithms, in performing live digital forensics for different IoT configurations. There are also a number of challenges associated with the use of machine learning techniques, as discussed in this paper

LiPISC: A Lightweight and Flexible Method for Privacy-Aware Intersection Set Computation

Privacy-aware intersection set computation (PISC) can be modeled as secure multi-party computation. The basic idea is to compute the intersection of input sets without leaking privacy. Furthermore, PISC should be sufficiently flexible to recommend approximate intersection items. In this paper, we reveal two previously unpublished attacks against PISC, which can be used to reveal and link one input set to another input set, resulting in privacy leakage. We coin these as Set Linkage Attack and Set Reveal Attack. We then present a lightweight and flexible PISC scheme (LiPISC) and prove its security (including against Set Linkage Attack and Set Reveal Attack)

A hierarchical key pre-distribution scheme for fog networks

Security in fog computing is multi-faceted, and one particular challenge is establishing a secure communication channel between fog nodes and end devices. This emphasizes the importance of designing efficient and secret key distribution scheme to facilitate fog nodes and end devices to establish secure communication channels. Existing secure key distribution schemes designed for hierarchical networks may be deployable in fog computing, but they incur high computational and communication overheads and thus consume significant memory. In this paper, we propose a novel hierarchical key pre-distribution scheme based on “Residual Design” for fog networks. The proposed key distribution scheme is designed to minimize storage overhead and memory consumption, while increasing network scalability. The scheme is also designed to be secure against node capture attacks. We demonstrate that in an equal-size network, our scheme achieves around 84% improvement in terms of node storage overhead, and around 96% improvement in terms of network scalability. Our research paves the way for building an efficient key management framework for secure communication within the hierarchical network of fog nodes and end devices. KEYWORDS: Fog Computing, Key distribution, Hierarchical Networks

On the security of consumer wearable devices in the Internet of Things

Miniaturization of computer hardware and the demand for network capable devices has resulted in the emergence of a new class of technology called wearable computing. Wearable devices have many purposes like lifestyle support, health monitoring, fitness monitoring, entertainment, industrial uses, and gaming. Wearable devices are hurriedly being marketed in an attempt to capture an emerging market. Owing to this, some devices do not adequately address the need for security. To enable virtualization and connectivity wearable devices sense and transmit data, therefore it is essential that the device, its data and the user are protected. In this paper the use of novel Integrated Circuit Metric (ICMetric) technology for the provision of security in wearable devices has been suggested. ICMetric technology uses the features of a device to generate an identification which is then used for the provision of cryptographic services. This paper explores how a device ICMetric can be generated by using the accelerometer and gyroscope sensor. Since wearable devices often operate in a group setting the work also focuses on generating a group identification which is then used to deliver services like authentication, confidentiality, secure admission and symmetric key generation. Experiment and simulation results prove that the scheme offers high levels of security without compromising on resource demands

What Do Men Want from a Health Screening Mobile App? A Qualitative Study.

There is a lack of mobile app which aims to improve health screening uptake developed for men. As part of the study to develop an effective mobile app to increase health screening uptake in men, we conducted a needs assessment to find out what do men want from a health screening mobile app. In-depth interviews and focus group discussions were conducted with 31 men from a banking institution in Kuala Lumpur. The participants were purposely sampled according to their job position, age, ethnicity and screening status. The recruitment was stopped once data saturation was achieved. The audio-recorded interviews were transcribed verbatim and analyzed using thematic approach. Three themes emerged from the analysis and they were: content, feature and dissemination. In terms of the content, men wanted the app to provide information regarding health screening and functions that can assess their health; which must be personalized to them and are trustable. The app must have user-friendly features in terms of information delivery, ease of use, attention allocation and social connectivity. For dissemination, men proposed that advertisements, recommendations by health professionals, providing incentive and integrating the app as into existing systems may help to increase the dissemination of the app. This study identified important factors that need to be considered when developing a mobile app to improve health screening uptake. Future studies on mobile app development should elicit users' preference and need in terms of its content, features and dissemination strategies to improve the acceptability and the chance of successful implementation

GDTN: Genome-Based Delay Tolerant Network Formation in Heterogeneous 5G Using Inter-UA Collaboration

This work was supported by ‘The Cross-Ministry Giga KOREA Project’ grant from the Ministry of Science, ICT and Future Planning, Korea. Also, it was in part supported by the Soonchunhyang University Research Fund.With a more Internet-savvy and sophisticated user base, there are more demands for interactive applications and services. However, it is a challenge for existing radio access networks (e.g. 3G and 4G) to cope with the increasingly demanding requirements such as higher data rates and wider coverage area. One potential solution is the inter-collaborative deployment of multiple radio devices in a 5G setting designed to meet exacting user demands, and facilitate the high data rate requirements in the underlying networks. These heterogeneous 5G networks can readily resolve the data rate and coverage challenges. Networks established using the hybridization of existing networks have diverse military and civilian applications. However, there are inherent limitations in such networks such as irregular breakdown, node failures, and halts during speed transmissions. In recent years, there have been attempts to integrate heterogeneous 5G networks with existing ad hoc networks to provide a robust solution for delay-tolerant transmissions in the form of packet switched networks. However, continuous connectivity is still required in these networks, in order to efficiently regulate the flow to allow the formation of a robust network. Therefore, in this paper, we present a novel network formation consisting of nodes from different network maneuvered by Unmanned Aircraft (UA). The proposed model utilizes the features of a biological aspect of genomes and forms a delay tolerant network with existing network models. This allows us to provide continuous and robust connectivity. We then demonstrate that the proposed network model has an efficient data delivery, lower overheads and lesser delays with high convergence rate in comparison to existing approaches, based on evaluations in both real-time testbed and simulation environment.Yeshttp://www.plosone.org/static/editorial#pee

Finite state machine for cloud forensic readiness as a service (CFRaaS) events

The importance of demonstrating the correctness of forensic analysis tools and automated incident management tools reinforces the need for a finite state machine (FSM) engine that can generate automated forensic processes. Hence, in this paper, we present an event-based FSM representation for Cloud Forensic Readiness as a Service (CFRaaS), where we also show how the FSM's predetermined states and transitions could be used to formulate an automated forensic process and generate a hypothesis for litigation purposes. Specifically, this proposition comprises a two-step level CFRaaS-FSM with possible transitions and states. This representation is useful because it can alert digital forensic investigators on how to deduce current and next state of attacks based on transitions and current states. Validerad;2022;Nivå 2;2022-01-31 (johcin)</p

Formal Analysis of Secure Contracting Protocol for E-Tendering Abstract

Formal specification and verification of protocols have been credited for uncovering protocol flaws; revealing inadequacies in protocol design of the Initial Stage and Negotiation Stage; and proved that improved protocol performs in the desired manner while under modelled attacks from dishonest players. It also shows how formal methods can be used by protocol designer to achieve a better design of a complex system. concept with a more complete and consistent protocol specification. Complex system protocol can be easily specified with simplifying assumptions for a high level of protocol verification. This set of assumptions can then be used to further explore the protocol. Using formal methods for complex secure system protocol design will provide not only better quality protocol concept to a more practical stage for development