Now showing 1 - 10 of 52
  • Publication
    Hierarchical Bloom Filter Trees for Approximate Matching
    (Journal of Digital Forensics, Security and Law, 2018-01) ; ;
    Bytewise approximate matching algorithms have in recent years shown significant promise in detecting files that are similar at the byte level. This is very useful for digital forensic investigators, who are regularly faced with the problem of searching through a seized device for pertinent data. A common scenario is where an investigator is in possession of a collection of "known-illegal" files (e.g. a collection of child abuse material) and wishes to find whether copies of these are stored on the seized device. Approximate matching addresses shortcomings in traditional hashing, which can only find identical files, by also being able to deal with cases of merged files, embedded files, partial files, or if a file has been changed in any way. Most approximate matching algorithms work by comparing pairs of files, which is not a scalable approach when faced with large corpora. This paper demonstrates the effectiveness of using a "Hierarchical Bloom Filter Tree" (HBFT) data structure to reduce the running time of collection-against-collection matching, with a specific focus on the MRSH-v2 algorithm. Three experiments are discussed, which explore the effects of different configurations of HBFTs. The proposed approach dramatically reduces the number of pairwise comparisons required, and demonstrates substantial speed gains, while maintaining effectiveness.
      362
  • Publication
    Improving the accuracy of automated facial age estimation to aid CSEM investigations
    The investigation of violent crimes against individuals, such as the investigation of child sexual exploitation material (CSEM), is one of the more commonly encountered criminal investigation types throughout the world. While hash lists of known CSEM content are commonly used to identify previously encountered material on suspects’ devices, previously unencountered material requires expert, manual analysis and categorisation. The discovery, analysis, and categorisation of these digital images and videos has the potential to be significantly expedited with the use of automated artificial intelligence (AI) based techniques. Intelligent, automated evidence processing and prioritisation has the potential to aid investigators in alleviating some of the digital evidence backlogs that have become commonplace worldwide. In order for AI-aided CSEM investigations to be beneficial, the fundamental question when analysing multimedia content becomes “how old is each subject encountered?’’. Our work presents the evaluation of existing cloud-based and offline age estimation services, introduces our deep learning model, DS13K, which was created with a VGG-16 Deep Convolutional Neural Network (CNN) architecture, and develops an ensemble technique that improves the accuracy of underage facial age estimation. In addition to our model, a number of existing services including Amazon Rekognition, Microsoft Azure Cognitive Services, How-Old.net, and Deep Expectation (DEX) were used to create an ensemble learning technique. It was found that for the borderline adulthood age range (i.e., 16–17 years old), our DS13K model substantially outperformed existing services, achieving a performance accuracy of 68%. A comparative examination of the obtained results allowed us to identify performance trends and issues inherent to each service/tool and develop ensemble techniques to improve the accuracy of automated adulthood determination.
      17
  • Publication
    A Week in the Life of the Most Popular BitTorrent Swarms
    The popularity of peer-to-peer (P2P) file distribution is consistently increasing since the late 1990’s. In 2008, P2P traffic accounted for over half of the world’s Internet traffic. P2P networks lend themselves well to the unauthorised distribution of copyrighted material due to their ease of use, the abundance of material available and the apparent anonymity awarded to the downloaders. This paper presents the results of an investigation conducted on the top 100 most popular BitTorrent swarms over the course of one week. The purpose of this investigation is to quantify the scale of unauthorised distribution of copyrighted material through the use of the BitTorrent protocol. Each IP address, which was discovered over the period of the weeklong investigation, is mapped through the use of a geolocation database, which results in the ability to determine where the participation in these swarms is prominent worldwide.
      366
  • Publication
    Enabling the remote acquisition of digital forensic evidence through secure data transmission and verification
    (University College Dublin. School of Computer Science  , 2009) ;
    Providing the ability to any law enforcement officer to remotely transfer an image from any suspect computer directly to a forensic laboratory for analysis, can only help to greatly reduce the time wasted by forensic investigators in conducting on-site collection of computer equipment. RAFT (Remote Acquisition Forensic Tool) is a system designed to facilitate forensic investigators by remotely gathering digital evidence. This is achieved through the implementation of a secure, verifiable client/server imaging architecture. The RAFT system is designed to be relatively easy to use, requiring minimal technical knowledge on behalf of the user. One of the key focuses of RAFT is to ensure that the evidence it gathers remotely is court admissible. This is achieved by ensuring that the image taken using RAFT is verified to be identical to the original evidence on a suspect computer.
      315
  • Publication
    Leveraging Decentralisation to Extend the Digital Evidence Acquisition Window: Case Study on BitTorrent Sync
    File synchronization services such as Dropbox, Google Drive, Microsoft OneDrive, Apple iCloud, etc., are becoming increasingly popular in today’s always-connected world. A popular alternative to the aforementioned services is BitTorrent Sync. This is a decentralized/cloudless file synchronization service and is gaining significant popularity among Internet users with privacy concerns over where their data is stored and who has the ability to access it. The focus of this paper is the remote recovery of digital evidence pertaining to files identified as being accessed or stored on a suspect’s computer or mobile device. A methodology for the identification, investigation, recovery and verification of such remote digital evidence is outlined. Finally, a proof-of-concept remote evidence recovery from BitTorrent Sync shared folder highlighting a number of potential scenarios for the recovery and verification of such evidence.
      138
  • Publication
    Leveraging Decentralisation to Extend the Digital Evidence Acquisition Window: Case Study on BitTorrent Sync
    (Association of Digital Forensics, Security and Law, 2014) ; ; ;
    File synchronization services such as Dropbox, Google Drive, Microsoft OneDrive, Apple iCloud, etc., are becoming increasingly popular in today's always-connected world. A popular alternative to the aforementioned services is BitTorrent Sync. This is a decentralized/cloudless file synchronization service and is gaining significant popularity among Internet users with privacy concerns over where their data is stored and who has the ability to access it. The focus of this paper is the remote recovery of digital evidence pertaining to files identified as being accessed or stored on a suspect's computer or mobile device. A methodology for the identification, investigation, recovery and verification of such remote digital evidence is outlined. Finally, a proof-of-concept remote evidence recovery from BitTorrent Sync shared folder highlighting a number of potential scenarios for the recovery and verification of such evidence.
      160
  • Publication
    An Evaluation of Google Plus Communities as an Active Learning Journal Alternative to Improve Learning Efficacy
    (ICEP, 2015-12-04) ;
    Learning journals are a very beneficial learning tool for students across a range of disciplines. The requirement of frequent entries to a journal encourages students to start achieving the learning objectives from the first week of a module. The completed journal serves as a useful revision resource for students preparing for a final exam or even long after the module’s completion. The downside to learning journals is that they are passive and the class as a whole does not benefit from the variety of opinions, articles and personal experiences logged in their classmates' journals. If the journal is only handed in at the end a semester, there is no room for feedback for the students on their entries until after the module has completed. In this paper, guidelines for the deployment of an active learning journal alternative, using Google Plus Communities, are presented. A literature review is also included for alternative case studies in using learning journals, weblogs, and wikis for recording and encouraging student learning throughout a module.
      205
  • Publication
    HTML5 Zero Configuration Covert Channels: Security Risks and Challenges
    In recent months there has been an increase in the popularity and public awareness of secure, cloudless file transfer systems. The aim of these services is to facilitate the secure transfer of files in a peer-to- peer (P2P) fashion over the Internet without the need for centralised authentication or storage. These services can take the form of client installed applications or entirely web browser based interfaces. Due to their P2P nature, there is generally no limit to the file sizes involved or to the volume of data transmitted – and where these limitations do exist they will be purely reliant on the capacities of the systems at either end of the transfer. By default, many of these services provide seamless, end-to-end encryption to their users. The cyber security and cyber forensic consequences of the potential criminal use of such services are significant. The ability to easily transfer encrypted data over the Internet opens up a range of opportunities for illegal use to cyber criminals requiring minimal technical know-how. This paper explores a number of these services and provides an analysis of the risks they pose to corporate and governmental security. A number of methods for the forensic investigation of such transfers are discussed.
      527
  • Publication
    Evaluation of Digital Forensic Process Models with Respect to Digital Forensics as a Service
    (Academic Conferences And Publishing International Limited, 2017-06-12) ; ;
    Digital forensic science is very much still in its infancy, but is becoming increasingly invaluable to investigators. A popular area for research is seeking a standard methodology to make the digital forensic process accurate, robust, and efficient. The first digital forensic process model proposed contains four steps: Acquisition, Identification, Evaluation and Admission. Since then, numerous process models have been proposed to explain the steps of identifying, acquiring, analysing, storage, and reporting on the evidence obtained from various digital devices. In recent years, an increasing number of more sophisticated process models have been proposed. These models attempt to speed up the entire investigative process or solve various of problems commonly encountered in the forensic investigation. In the last decade, cloud computing has emerged as a disruptive technological concept, and most leading enterprises such as IBM, Amazon, Google, and Microsoft have set up their own cloud-based services. In the field of digital forensic investigation, moving to a cloudbased evidence processing model would be extremely beneficial and preliminary attempts have been made in its implementation. Moving towards a Digital Forensics as a Service model would not only expedite the investigative process, but can also result in significant cost savings - freeing up digital forensic experts and law enforcement personnel to progress their caseload. This paper aims to evaluate the applicability of existing digital forensic process models and analyse how each of these might apply to a cloud-based evidence processing paradigm.
      24
  • Publication
    Overview of the Forensic Investigation of Cloud Services
    Cloud Computing is a commonly used, yet ambiguous term, which can be used to refer to a multitude of differing dynamically allocated services. From a law enforcement and forensic investigation perspective, cloud computing can be thought of as a double edged sword. While on one hand, the gathering of digital evidence from cloud sources can bring with it complicated technical and cross-jurisdictional legal challenges. On the other, the employment of cloud storage and processing capabilities can expedite the forensics process and focus the investigation onto pertinent data earlier in an investigation. This paper examines the state-of-the-art in cloud-focused, digital forensic practises for the collection and analysis of evidence and an overview of the potential use of cloud technologies to provide Digital Forensics as a Service.
      931Scopus© Citations 28