Drone forensics: A case study on a DJI mavic air

© 2019 IEEE. The use and sale of Unmanned Aerial Vehicles (UAVs), or drones, have seen an immense amount of growth over the past few years. While capturing mass-market appeal and serving legitimate uses, there have been many incidents where UAVs were used to commit various sinister activities. Digital forensic examiners have consequently come to play a vital role in the emerging field of drone or UAV forensics. In this research we perform a forensic investigation on an Unmanned Aircraft System (UAS), specifically the DJI Mavic Air, using an iOS-based smartphone device. In our study we examine the data that can be extracted from the UAS in addition to investigating and analyzing the logical acquisition of the associated smartphone device created by Apple\u27s iTunes backup utility. Our findings indicate that the mobile application used to control the UAV contains a significant amount of forensic data. Furthermore, we obtained valuable data from the external MicroSD card, the mobile device and the drone

Messaging Forensic Framework for Cybercrime Investigation

Online predators, botmasters, and terrorists abuse the Internet and associated web technologies by conducting illegitimate activities such as bullying, phishing, and threatening. These activities often involve online messages between a criminal and a victim, or between criminals themselves. The forensic analysis of online messages to collect empirical evidence that can be used to prosecute cybercriminals in a court of law is one way to minimize most cybercrimes. The challenge is to develop innovative tools and techniques to precisely analyze large volumes of suspicious online messages. We develop a forensic analysis framework to help an investigator analyze the textual content of online messages with two main objectives. First, we apply our novel authorship analysis techniques for collecting patterns of authorial attributes to address the problem of anonymity in online communication. Second, we apply the proposed knowledge discovery and semantic anal ysis techniques for identifying criminal networks and their illegal activities. The focus of the framework is to collect creditable, intuitive, and interpretable evidence for both technical and non-technical professional experts including law enforcement personnel and jury members. To evaluate our proposed methods, we share our collaborative work with a local law enforcement agency. The experimental result on real-life data suggests that the presented forensic analysis framework is effective for cybercrime investigation

Assisting People of Determination and the Elderly Using Social Robot: A Case Study

A technological innovation that has recently garnered attention in the literature is social humanoid robots' applications. Ever since their commercialization, social robots have been viewed as a valuable tool to assist individuals in their daily activities. As people grow older, their capabilities to accomplish everyday activities gradually deteriorate. Consequently, there is a pressing need for research on the positive benefits offered by humanoid robots. This paper explores the implications of a social robot, Zenbo, in the United Arab Emirates (UAE). We propose that the Zenbo be helpful in assisting vulnerable elderly populations, ordinary citizens, and People of Determination. This study can guide the UAE policymakers to allow elderly peoples and disabled individuals to use Zenbo to ensure their safety and well-being. This technological advancement can help transform the traditional support systems offered to the vulnerable populations in the Middle East

Towards a better understanding of drone forensics: A case study of parrot AR drone 2.0

Copyright © 2020, IGI Global. Unmanned aerial vehicles (drones) have gained increased popularity as their innovative uses continue to expand across various fields. Despite their numerous beneficial uses, drones have unfortunately been misused, through many reported cases, to launch illegal and sometimes criminal activities that pose direct threats to individuals, organizations, public safety and national security. These threats have recently led law enforcement agencies and digital forensic investigators to pay special attention to the forensic aspects of drones. This important research topic, however, remains underexplored. This study aims to further explore drone forensics in terms of challenges, forensic investigation procedures and experimental results through a forensic investigation study performed on a Parrot AR drone 2.0. In this study, the authors present new insights on drone forensics in terms of forensic approaches, access to drone’s digital containers and the retrieval of key information that can assist digital forensic investigators establish ownership, recuperate flight data and gain access to media files

Drone Forensics: A Detailed Analysis of Emerging DJI Models

© 2020 IEEE. The widespread use and fast-paced development of drones pose a challenge for law enforcement and other enterprises due to their increased use in digital crimes. To keep up with this development and to effectively extract information required for forensics investigations, examiners need in-depth knowledge of drones, forensics methods, and the capabilities of available tools. In this study, we examine and analyze the data extracted from four hobbyist drone models (DJI Mavic 2 Pro, DJI Mavic Air, DJI Spark, and DJI Phantom 4), while comparing the applicability and capability of several commercial and open-source forensics tools. Our findings indicate that most of the new drone models are relatively difficult to analyze due to the enhanced security of these models. It is imperative to develop novel forensics processes and specialized forensics tools to enhance the forensic analysis of drones

Fuzzy Query Routing in Unstructured Mobile Peer-to-Peer Networks

© 2016 IEEE. Due to the disparity between the peer-to-peer (P2P) and the physical networks, we study the challenging problems of mobile routing in unstructured P2P networks over mobile ad hoc networks (MANETs). To route queries and objects of interest, the existing mobile P2P protocols widely adopted an inflexible techniques which experience a relatively high delivery time due to remarkable network traffic, nodes mobility and broken links. The bond between routing and mobility is crucial to obtain efficient searching in mobile P2P network. To solve this problem, we proposed fuzzy search controller [1] which reduced search time but due to peer mobility the protocol causes low hit rate and high overhead. Thus, this article proposes novel fuzzy controller based possibilistic routing for unstructured mobile P2P networks to reduce routing time. The possibilistic routing is based on ultrapeer mobility, active time and location. The inference rules are defined to select the best route to forward query walker. Simulations show that the fuzzy search controller gives better performance than the competing protocols in terms of reducing response time and increasing hit rate in different mobility scenarios

Mining criminal networks from chat log

Cyber criminals exploit opportunities for anonymity and masquerade in web-based communication to conduct illegal activities such as phishing, spamming, cyber predation, cyber threatening, blackmail, and drug trafficking. One way to fight cyber crime is to collect digital evidence from online documents and to prosecute cyber criminals in the court of law. In this paper, we propose a unified framework using data mining and natural language processing techniques to analyze online messages for the purpose of crime investigation. Our framework takes the chat log from a confiscated computer as input, extracts the social networks from the log, summarizes chat conversations into topics, identifies the information relevant to crime investigation, and visualizes the knowledge for an investigator. To ensure that the implemented framework meets the needs of law enforcement officers in real-life investigation, we closely collaborate with the cyber crime unit of a law enforcement agency in Canada. Both the feedback from the law enforcement officers and experimental results suggest that the proposed chat log mining framework is effective for crime investigation. © 2012 IEEE

A Preliminary Study of Research-Driven University Spin-off Companies in UAE

Entrepreneurship is the procedure of a new business development to make a profit in the market. In many countries, Technology Transfer Offices (TTOs) in research-driven universities serve as an intermediary between suppliers of innovations and those who can potentially commercialize them. TTOs are always run as cost-centers on campus, often have business or operation managers, and facilitate intellectual property licensing activities. In the United Arab Emirates (UAE), TTOs are taking an important role in the evolution of a successful spin-off company from innovation to production to sales to sustainable profit. An innovative technology may be a research outcome and seem to have value as an application or product with commercial potential in the market. In this context, TTOs often support spin-off companies becoming a learning organization and easing into an articulated management of activities complementary to the research and design activities that create the innovation and drive the transition from innovation to product lines. That is, even though such academic entrepreneurs have built and run entities that are similar to small businesses, and even though these entrepreneurs have learned how to secure and manage revenues to sustain cash flows for their companies, they still may not be sustainable in the market. The long term of this research study aims to investigate the current situation of research-driven university entrepreneurship in UAE. This paper presents a preliminary study of two TTOs: Etisalat BT Innovation Center (EBTIC) at Khalifa University and Masdar Institute

Systematic privacy impact assessment scheme for smart connected toys data privacy compliance

Children\u27s privacy compliance assessment in the area of smart connected toy (SCT) or play robot is a challenge, considering the plethora of device manufacturers using varied controls in an attempt to address diverse global children\u27s privacy regulations. Systematic privacy impact assessment scheme (SPIAS) is an abstract model developed to assess children\u27s SCT privacy compliance to known global child-centered legislation such as the Children\u27s Online Privacy Protection Act (COPPA). SPIAS addresses this issue by integrating global survey and analysis of existing children\u27s privacy legislation, and evaluating privacy theories to provide means of classifying data processed by SCT into set states using a finite state machine (FSM). SPIAS, as a tool to, can be adapted assess and address privacy risks and compliance arising from a new SCT or the convergence of existing SCT that collects, processes, and transfers children information