Rapid technology advancements, especially in the past decade, have allowed off-the-shelf unmanned aerial vehicles (UAVs) that weigh less than 250 g to become available for recreational use by the general population. Many well-known manufacturers (e.g., DJI) are now focusing on this segment of UAVs, and the new DJI Mini 2 drone is one of many that falls under this category, which enables easy access to be purchased and used without any Part 107 certification and Remote ID registration. The versatility of drones and drone models is appealing for customers, but they pose many challenges to forensic tools and digital forensics investigators due to numerous hardware and software variations. In addition, different devices can be associated and used for controlling these drones (e.g., Android and iOS smartphones). Moreover, according to the Federal Aviation Administration (FAA), the adoption of Remote ID is not going to be required for people without the 107 certifications for this segment at least until 2023, which creates finding personally identifiable information a necessity in these types of investigations. In this research, we conducted a comprehensive investigation of DJI Mini 2 and its data stored across multiple devices (e.g., SD cards and mobile devices) that are associated with the drone. The aim of this paper is to (1) create several criminal-like scenarios, (2) acquire and analyze the created scenarios using leading forensics software (e.g., Cellebrite and Magnet Axiom) that are commonly used by law enforcement agencies, (3) and present findings associated with potential criminal activities.

The emergence of the Internet of Things technologies and the increase and convenience of smart home devices have contributed to the growth of self-installed home security systems. While home security devices have become more accessible and can help users monitor and secure their homes, they can also become targets of cyberattacks and/or witnesses of criminal activities, hence sources of forensic evidence. To date, there is little existing literature on forensic analysis and the security and privacy of home security systems. In this paper, we seek to better understand and assess the forensic artifacts that can be extracted, the security and privacy concerns around the use of home security devices, and the challenges forensic investigators might encounter, by performing a comprehensive investigation of the SimpliSafe security system. We investigated the interaction of the security system with the SimpliSafe companion app on both Android and iOS devices. We analyzed the network traffic as the user interacts with the system to identify any security or privacy concerns. Our method can help investigators working on other home security systems, and our findings can further help developers to improve the confidentiality and privacy of user data in home security devices and their applications.

Wearable devices are becoming increasingly popular, diverse, and accessible. To put it in perspective, in 2022 alone, more than 490 million wearable devices were sold. The diversity of wearables is beneficial to users but poses challenges for mobile forensic investigators. These devices track, utilize, and collect a wide range of user information, generating a wealth of data that can potentially be used or presented in court as evidence. To keep up with these innovations, mobile forensic investigators must continuously monitor and update their knowledge. In particular, smart rings are gaining popularity, with the Oura Ring Gen 3 being one of the most anticipated within the community. This study provides an initial look at the Oura Ring Generation 3 application, known as Oura, from a mobile forensic perspective. The artifacts presented in this article are derived from three different platforms: Android, iOS, and Cloud. The study reveals the exact paths of the data points and their locations. The data uncovered in this study could be significant for digital forensics investigators in various scenarios and inform users about the personal information that is stored. Information such as heart rate, various activities performed, user ID, and other user details could prove valuable in multiple instances.

Mobile devices, specifically smartphones, have become a necessity in everyday life, as we perform many essential day-to-day tasks using these devices. With the projected increase in mobile devices to 18.22 billion by 2025, the reliance on smartphones will only grow. This demand for smartphones has allowed various companies to start developing their own devices and custom operating systems, each of which puts its own touch on them. In addition, current smartphones have increased processing power, providing users with a computer experience in their pockets. Software developers have taken this opportunity to bridge the gap between personal computers and smartphones by creating the same software for personal computers and mobile devices. Kali Linux is one of the most popular penetration testing tools for desktop use and has been adapted to operate on mobile devices under the name Kali NetHunter. Kali NetHunter has three different versions on mobile platforms that provide various levels of capabilities. Kali NetHunter is just one example in which an application or an operating system applies to a specific niche of users. Highly customized operating systems or applications do not receive the same attention as field research, leaving them unfamiliar to mobile forensic investigators when used maliciously. In this paper, we conducted an exploratory study on the Kali NetHunter Lite application after it was installed and its embedded tools were utilized. Our results show a detailed analysis of the file system and reveal the data from the tests carried out during various phases. Furthermore, the locations of the folders involved in the process were described.