arXiv subjects

Kim-Kwang Raymond Choo

Publications and source records attributed to Kim-Kwang Raymond Choo.

At least 55 records · Page 3Linked to original sources

arXiv2019

Integrating Privacy Enhancing Techniques into Blockchains Using Sidechains

Blockchains are turning into decentralized computing platforms and are getting worldwide recognition for their unique advantages. There is an emerging trend beyond payments that blockchains could enable a new breed of decentralized applications, and serve as the foundation for Internet's security infrastructure. The immutable nature of the blockchain makes it a winner on security and transparency; it is nearly inconceivable for ledgers to be altered in a way not instantly clear to every single user involved. However, most blockchains fall short in privacy aspects, particularly in data protection. Garlic Routing and Onion Routing are two of major Privacy Enhancing Techniques (PETs) which are popular for anonymization and security. Garlic Routing is a methodology using by I2P Anonymous Network to hide the identity of sender and receiver of data packets by bundling multiple messages into a layered encryption structure. The Onion Routing attempts to provide lowlatency Internet-based connections that resist traffic analysis, deanonymization attack, eavesdropping, and other attacks both by outsiders (e.g. Internet routers) and insiders (Onion Routing servers themselves). As there are a few controversies over the rate of resistance of these two techniques to privacy attacks, we propose a PET-Enabled Sidechain (PETES) as a new privacy enhancing technique by integrating Garlic Routing and Onion Routing into a Garlic Onion Routing (GOR) framework suitable to the structure of blockchains. The preliminary proposed GOR aims to improve the privacy of transactions in blockchains via PETES structure.

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arXiv2019

HEDGE: Efficient Traffic Classification of Encrypted and Compressed Packets

As the size and source of network traffic increase, so does the challenge of monitoring and analysing network traffic. Therefore, sampling algorithms are often used to alleviate these scalability issues. However, the use of high entropy data streams, through the use of either encryption or compression, further compounds the challenge as current state of the art algorithms cannot accurately and efficiently differentiate between encrypted and compressed packets. In this work, we propose a novel traffic classification method named HEDGE (High Entropy DistinGuishEr) to distinguish between compressed and encrypted traffic. HEDGE is based on the evaluation of the randomness of the data streams and can be applied to individual packets without the need to have access to the entire stream. Findings from the evaluation show that our approach outperforms current state of the art. We also make available our statistically sound dataset, based on known benchmarks, to the wider research community.

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arXiv2019

Blockchain-enabled Authentication Handover with Efficient Privacy Protection in SDN-based 5G Networks

5G mobile networks provide additional benefits in terms of lower latency, higher data rates, and more coverage, in comparison to 4G networks, and they are also coming close to standardization. For example, 5G has a new level of data transfer and processing speed that assures users are not disconnected when they move from one cell to another; thus, supporting faster connection. However, it comes with its own technical challenges relating to resource management, authentication handover and user privacy protection. In 5G, the frequent displacement of the users among the cells as a result of repeated authentication handovers often lead to a delay, contradicting the 5G objectives. In this paper, we propose a new authentication approach that utilizes blockchain and software defined networking (SDN) techniques to remove the re-authentication in repeated handover among heterogeneous cells. The proposed approach is designed to assure the low delay, appropriate for the 5G network in which users can be replaced with the least delay among heterogeneous cells using their public and private keys provided by the devised blockchain component while protecting their privacy. In our comparison between Proof-of-Work (POW)-based and network-based models, the delay of our authentication handover was shown to be less than 1ms. Also, our approach demonstrated less signaling overhead and energy consumption compared to peer models.

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arXiv2019

Designing Sensing as a Service (S2aaS) Ecosystem for Internet of Things

The Internet of Things (IoT) envisions the creation of an environment where everyday objects (e.g. microwaves, fridges, cars, coffee machines, etc.) are connected to the internet and make users' lives more productive, efficient, and convenient. During this process, everyday objects capture a vast amount of data that can be used to understand individuals and their behaviours. In the current IoT ecosystems, such data is collected and used only by the respective IoT solutions. There is no formal way to share data with external entities. We believe this is very efficient and unfair for users. We believe that users, as data owners, should be able to control, manage, and share data about them in any way that they choose and make or gain value out of them. To achieve this, we proposed the Sensing as a Service (S2aaS) model. In this paper, we discuss the Sensing as a Service ecosystem in terms of its architecture, components and related user interaction designs. This paper aims to highlight the weaknesses of the current IoT ecosystem and to explain how S2aaS would eliminate those weaknesses. We also discuss how an everyday user may engage with the S2aaS ecosystem and design challenges.

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arXiv2018

Empirical Vulnerability Analysis of Automated Smart Contracts Security Testing on Blockchains

The emerging blockchain technology supports decentralized computing paradigm shift and is a rapidly approaching phenomenon. While blockchain is thought primarily as the basis of Bitcoin, its application has grown far beyond cryptocurrencies due to the introduction of smart contracts. Smart contracts are self-enforcing pieces of software, which reside and run over a hosting blockchain. Using blockchain-based smart contracts for secure and transparent management to govern interactions (authentication, connection, and transaction) in Internet-enabled environments, mostly IoT, is a niche area of research and practice. However, writing trustworthy and safe smart contracts can be tremendously challenging because of the complicated semantics of underlying domain-specific languages and its testability. There have been high-profile incidents that indicate blockchain smart contracts could contain various code-security vulnerabilities, instigating financial harms. When it involves security of smart contracts, developers embracing the ability to write the contracts should be capable of testing their code, for diagnosing security vulnerabilities, before deploying them to the immutable environments on blockchains. However, there are only a handful of security testing tools for smart contracts. This implies that the existing research on automatic smart contracts security testing is not adequate and remains in a very stage of infancy. With a specific goal to more readily realize the application of blockchain smart contracts in security and privacy, we should first understand their vulnerabilities before widespread implementation. Accordingly, the goal of this paper is to carry out a far-reaching experimental assessment of current static smart contracts security testing tools, for the most widely used blockchain, the Ethereum and its domain-specific programming language, Solidity to provide the first...

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arXiv2018

Digital Blues: An Investigation into the Use of Bluetooth Protocols

The proliferation of Bluetooth mobile device communications into all aspects of modern society raises security questions by both academicians and practitioners. This environment prompted an investigation into the real-world use of Bluetooth protocols along with an analysis of documented security attacks. The experiment discussed in this paper collected data for one week in a local coffee shop. The data collection took about an hour each day and identified 478 distinct devices. The contribution of this research is two-fold. First, it provides insight into real-world Bluetooth protocols that are being utilized by the general public. Second, it provides foundational research that is necessary for future Bluetooth penetration testing research.

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arXiv2018

Non-Reciprocity Compensation Combined with Turbo Codes for Secret Key Generation in Vehicular Ad Hoc Social IoT Networks

The physical attributes of the dynamic vehicle-to-vehicle (V2V) propagation channel can be utilised for the generation of highly random and symmetric cryptographic keys. However, in a physical-layer key agreement scheme, non-reciprocity due to inherent channel noise and hardware impairments can propagate bit disagreements. This has to be addressed prior to the symmetric key generation which is inherently important in social Internet of Things (IoT) networks, including in adversarial settings (e.g. battlefields). In this paper, we parametrically incorporate temporal variability attributes, such as three-dimensional (3D) scattering and scatterers mobility. Accordingly, this is the first work to incorporate such features into the key generation process by combining non-reciprocity compensation with turbo codes. Preliminary results indicate a significant improvement when using Turbo Codes in bit mismatch rate (BMR) and key generation rate (KGR) in comparison to sample indexing techniques.

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arXiv2018

Ubuntu One Investigation: Detecting Evidences on Client Machines

STorage as a Service (STaaS) cloud services has been adopted by both individuals and businesses as a dominant technology worldwide. Similar to other technologies, this widely accepted service can be misused by criminals. Investigating cloud platforms is becoming a standard component of contemporary digital investigation cases. Hence, digital forensic investigators need to have a working knowledge of the potential evidence that might be stored on cloud services. In this chapter, we conducted a number of experiments to locate data remnants of users' activities when utilizing the Ubuntu One cloud service. We undertook experiments based on common activities performed by users on cloud platforms including downloading, uploading, viewing, and deleting files. We then examined the resulting digital artifacts on a range of client devices, namely, Windows 8.1, Apple Mac OS X, and Apple iOS. Our examination extracted a variety of potentially evidential items ranging from Ubuntu One databases and log files on persistent storage to remnants of user activities in device memory and network traffic.

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arXiv2018

A Cyber Kill Chain Based Taxonomy of Banking Trojans for Evolutionary Computational Intelligence

Malware such as banking Trojans are popular with financially-motivated cybercriminals. Detection of banking Trojans remains a challenging task, due to the constant evolution of techniques used to obfuscate and circumvent existing detection and security solutions. Having a malware taxonomy can facilitate the design of mitigation strategies such as those based on evolutionary computational intelligence. Specifically, in this paper, we propose a cyber kill chain based taxonomy of banking Trojans features. This threat intelligence based taxonomy providing a stage-by-stage operational understanding of a cyber-attack, can be highly beneficial to security practitioners and the design of evolutionary computational intelligence on Trojans detection and mitigation strategy. The proposed taxonomy is validated by using a real-world dataset of 127 banking Trojans collected from December 2014 to January 2016 by a major UK-based financial organisation.

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arXiv2018

Greening Cloud-Enabled Big Data Storage Forensics: Syncany as a Case Study

The pervasive nature of cloud-enabled big data storage solutions introduces new challenges in the identification, collection, analysis, preservation and archiving of digital evidences. Investigation of such complex platforms to locate and recover traces of criminal activities is a time-consuming process. Hence, cyber forensics researchers are moving towards streamlining the investigation process by locating and documenting residual artefacts (evidences) of forensic value of users activities on cloud-enabled big data platforms in order to reduce the investigation time and resources involved in a real-world investigation. In this paper, we seek to determine the data remnants of forensic value from Syncany private cloud storage service, a popular storage engine for big data platforms. We demonstrate the types and the locations of the artefacts that can be forensically recovered. Findings from this research contribute to an in-depth understanding of cloud-enabled big data storage forensics, which can result in reduced time and resources spent in real-world investigations involving Syncany-based cloud platforms.

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arXiv2018

CloudMe Forensics: A Case of Big-Data Investigation

The issue of increasing volume, variety and velocity of has been an area of concern in cloud forensics. The high volume of data will, at some point, become computationally exhaustive to be fully extracted and analysed in a timely manner. To cut down the size of investigation, it is important for a digital forensic practitioner to possess a well-rounded knowledge about the most relevant data artefacts from the cloud product investigating. In this paper, we seek to tackle on the residual artefacts from the use of CloudMe cloud storage service. We demonstrate the types and locations of the artefacts relating to the installation, uninstallation, log-in, log-off, and file synchronisation activities from the computer desktop and mobile clients. Findings from this research will pave the way towards the development of data mining methods for cloud-enabled big data endpoint forensics investigation.

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arXiv2018

Digital forensic investigation of two-way radio communication equipment and services

Historically, radio-equipment has solely been used as a two-way analogue communication device. Today, the use of radio communication equipment is increasing by numerous organisations and businesses. The functionality of these traditionally short-range devices have expanded to include private call, address book, call-logs, text messages, lone worker, telemetry, data communication, and GPS. Many of these devices also integrate with smartphones, which delivers Push-To-Talk services that make it possible to setup connections between users using a two-way radio and a smartphone. In fact, these devices can be used to connect users only using smartphones. To date, there is little research on the digital traces in modern radio communication equipment. In fact, increasing the knowledge base about these radio communication devices and services can be valuable to law enforcement in a police investigation. In this paper, we investigate what kind of radio communication equipment and services law enforcement digital investigators can encounter at a crime scene or in an investigation. Subsequent to seizure of this radio communication equipment we explore the traces, which may have a forensic interest and how these traces can be acquired. Finally, we test our approach on sample radio communication equipment and services.

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arXiv2018

A fuzzy-PSO system for indoor localization based on visible light communications

Indoor positioning systems using visible light communication (VLC) have potential applications in smart buildings, for instance, in developing economical, easy-to-use, widely accessible positioning system based on light-emitting diodes. Thus using VLCs, we introduce a new fuzzy-based system for indoor localization in this paper. The system processes data from transmitters (i.e., anchor nodes) and delivers the calculated position of a receiver. A particle swarm optimization (PSO) technique is then employed to obtain the optimal configuration of the proposed fuzzy logic controllers (FLCs). Specifically, the proposed PSO technique optimizes the membership functions of the FLCs by adjusting their range to achieve the best results regarding the localization reliability. We demonstrate the utility of the proposed approach using experiments.

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arXiv2017

Performance of Android Forensics Data Recovery Tools

Recovering deleted or hidden data is among most important duties of forensics investigators. Extensive utilisation of smartphones as subject, objects or tools of crime made them an important part of residual forensics. This chapter investigates the effectiveness of mobile forensic data recovery tools in recovering evidences from a Samsung Galaxy S2 i9100 Android phone. We seek to determine the amount of data that could be recovered using Phone image carver, Access data FTK, Foremost, Diskdigger, and Recover My File forensic tools. The findings reflected the difference between recovery capacities of studied tools showing their suitability in their specialised contexts only.

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arXiv2017

Investigation and Automating Extraction of Thumbnails Produced by Image viewers

Today, in digital forensics, images normally provide important information within an investigation. However, not all images may still be available within a forensic digital investigation as they were all deleted for example. Data carving can be used in this case to retrieve deleted images but the carving time is normally significant and these images can be moreover overwritten by other data. One of the solutions is to look at thumbnails of images that are no longer available. These thumbnails can often be found within databases created by either operating systems or image viewers. In literature, most research and practical focus on the extraction of thumbnails from databases created by the operating system. There is a little research working on the thumbnails created by the image reviewers as these thumbnails are application-driven in terms of pre-defined sizes, adjustments and storage location. Eventually, thumbnail databases from image viewers are significant forensic artefacts for investigators as these programs deal with large amounts of images. However, investigating these databases so far is still manual or semi-automatic task that leads to the huge amount of forensic time. Therefore, in this paper we propose a new approach of automating extraction of thumbnails produced by image viewers. We also test our approach with popular image viewers in different storage structures and locations to show its robustness.

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arXiv2017

Medical Cyber-Physical Systems Development: A Forensics-Driven Approach

The synthesis of technology and the medical industry has partly contributed to the increasing interest in Medical Cyber-Physical Systems (MCPS). While these systems provide benefits to patients and professionals, they also introduce new attack vectors for malicious actors (e.g. financially-and/or criminally-motivated actors). A successful breach involving a MCPS can impact patient data and system availability. The complexity and operating requirements of a MCPS complicates digital investigations. Coupling this information with the potentially vast amounts of information that a MCPS produces and/or has access to is generating discussions on, not only, how to compromise these systems but, more importantly, how to investigate these systems. The paper proposes the integration of forensics principles and concepts into the design and development of a MCPS to strengthen an organization's investigative posture. The framework sets the foundation for future research in the refinement of specific solutions for MCPS investigations.

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arXiv2017

Forensic Investigation of P2P Cloud Storage: BitTorrent Sync as a Case Study

Cloud computing has been regarded as the technology enabler for the Internet of Things (IoT). To ensure the most effective collection of IoT-based evidence, it is vital for forensic practitioners to possess a contemporary understanding of the artefacts from different cloud services. In this paper, we seek to determine the data remnants from the use of BitTorrent Sync version 2.0. Findings from our research using mobile and computer devices running Windows 8.1, Mac OS X Mavericks 10.9.5, Ubuntu 14.04.1 LTS, iOS 7.1.2, and Android KitKat 4.4.4 suggested that artefacts relating to the installation, uninstallation, log-in, log-off, and file synchronisation could be recovered, which are potential sources of IoT forensics. We also present a forensically sound investigation methodology for BitTorrent Sync.

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arXiv2017

Cloud Storage Forensics: Analysis of Data Remnants on SpiderOak, JustCloud, and pCloud

STorage as a Service (STaaS) cloud platforms benefits such as getting access to data anywhere, anytime, on a wide range of devices made them very popular among businesses and individuals. As such forensics investigators are increasingly facing cases that involve investigation of STaaS platforms. Therefore, it is essential for cyber investigators to know how to collect, preserve, and analyse evidences of these platforms. In this paper, we describe investigation of three STaaS platforms namely SpiderOak, JustCloud, and pCloud on Windows 8.1 and iOS 8.1.1 devices. Moreover, possible changes on uploaded and downloaded files metadata on these platforms would be tracked and their forensics value would be investigated.

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