Network Forensics Analysis of iOS Social Networking and Messaging Apps

Bhatt, Arpita Jadhav; Gupta, Chetan; Mittal, Sangeeta

doi:10.1109/ic3.2018.8530576

Cited by 5 publications

(5 citation statements)

References 4 publications

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“…Various researchers conduct network forensics for several reasons. Some of the most prominent reasons for conducting network forensics on social media applications include (1) traffic characterization [43,70,74,75], (2) traffic decryption [71], and lastly, (3) recovering artifacts [39][40][41][42]45,72,73], as shown in Table 4.…”

Section: Network Analysis Focusmentioning

confidence: 99%

“…Furthermore, legal considerations often place Android devices at the center of criminal cases, necessitating the continuous development of expertise in Android device analysis. However, with the increasing popularity of iOS devices, more attention is being given to the iOS platform [42,68,73]. It is also interesting to note that in mobile platforms such as Blackberry, no traces of evidence could be recovered, making it a very secure platform [7,66].…”

Section: Trends In Social Media Forensicsmentioning

confidence: 99%

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A Comprehensive Survey on Artifact Recovery from Social Media Platforms: Approaches and Future Research Directions

Gupta,

Oladimeji,

Varol

et al. 2023

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Social media applications have been ubiquitous in modern society, and their usage has grown exponentially over the years. With the widespread adoption of these platforms, social media has evolved into a significant origin of digital evidence in the domain of digital forensics. The increasing utilization of social media has caused an increase in the number of studies focusing on artifact (digital remnants of data) recovery from these platforms. As a result, we aim to present a comprehensive survey of the existing literature from the past 15 years on artifact recovery from social media applications in digital forensics. We analyze various approaches and techniques employed for artifact recovery, structuring our review on well-defined analysis focus categories, which are memory, disk, and network. By scrutinizing the available literature, we determine the trends and commonalities in existing research and further identify gaps in existing literature and areas of opportunity for future research in this field. The survey is expected to provide a valuable resource for academicians, digital forensics professionals, and researchers by enhancing their comprehension of the current state of the art in artifact recovery from social media applications. Additionally, it highlights the need for continued research to keep up with social media’s constantly evolving nature and its consequent impact on digital forensics.

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Section: Network Analysis Focusmentioning

confidence: 99%

Section: Trends In Social Media Forensicsmentioning

confidence: 99%

A Comprehensive Survey on Artifact Recovery from Social Media Platforms: Approaches and Future Research Directions

Gupta,

Oladimeji,

Varol

et al. 2023

Information

View full text Add to dashboard Cite

show abstract

“…Similarly, Jadhav Bhatt et al [17] conducted a network forensic analysis of iOS social networking and messaging apps to understand the types of user data that the apps were sending and to study the runtime behavior of these apps, drawing attention to the lesser known security flaws of many of the apps studied. The methodology involves using Charles proxy and Wireshark on a Mac workstation to capture the communication between an iPad running iOS 11.2.6 and the network and analyzing the traffic on a Windows workstation.…”

Section: Literature Reviewmentioning

confidence: 99%

Forensic Analysis of TikTok Alternatives on Android and iOS Devices: Byte, Dubsmash, and Triller

et al. 2022

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TikTok has consistently been one of the most used mobile apps worldwide on any mobile operating system. However, despite people’s enjoyment of using the application, there have been growing concerns about the application’s origins and alleged privacy violations. These allegations have become such a big problem that the former President of the United States, Donald Trump, expressed a desire to ban the TikTok application from being offered on US application stores like Google’s Play Store and Apple’s App Store. This remark sent TikTok users into a frenzy to find alternatives before the ban took effect. To this end, several alternative applications for TikTok have surfaced and are already garnering millions of users. In this paper, we identified three popular alternatives to the TikTok application (Byte, Dubmash, and Triller) and forensically analyzed each on smartphones of Android version 8 and iOS version 13. We focused on identifying forensically relevant artifacts that may be helpful to investigators in the event of a criminal investigation, should these or similar apps fall under scrutiny. We used Magnet AXIOM Process and Cellebrite UFED 4PC for acquisition, and Magnet AXIOM Examine and DB Browser for SQLite for analysis and reading. The investigation resulted in successful extraction of expected yet unique data points, plain text sensitive data, directories and format. These results lead to a discussion about identifying and comparing these app’s privacy concerns to that of TikTok, as formulated from the literature.

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“…None of the detected applications are available in public app stores in Germany and, consequently, they are not included in the further analyses. The remaining seven publications deal with the distantly related topic of the impact of warning detection apps on driver behavior (Botzer et al, 2017;Payre & Diels, 2020), and the following foreign topics: service provider communication (Chen et al, 2017), hotspot detection via smartphones (Cuenca et al, 2018), an app for safely texting-while-walking in indoor environments (Huang, 2017), network forensics analysis of iOS social networking and messaging apps (Bhatt et al, 2018) and the design of driver safety UI (Lee & Lee, 2018). These projects are not further analyzed.…”

Section: Classification Of Warning Appsmentioning

confidence: 99%

Warning Apps for Road Safety: A Technological and Economical Perspective for Autonomous Driving – The Warning Task in the Transition from Human Driver to Automated Driving

Trager

Kalová

Pagany

et al. 2021

International Journal of Human–Computer Interaction

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In the last decade, mobile warning apps and security services for drivers were developed, driven by the evolving market for smartphone-based applications. Now, in times of emerging autonomous vehicles, the value of warning detection in form of warning apps for road transport needs to be reappraised. In our study, we address the following questions: Does this kind of application have a technological and economical perspective for future mobility? How will the interaction between drivers, information systems (smartphone or onboard computer), and driving systems change? In this article, we bring together the aspects to consider in terms of technology development and business modeling amidst a changing human-computer interaction (HCI) toward autonomous driving. We provide a comprehensive picture of how technology-driven applications, such as warning detection apps, could develop their economic and technological impact within the transition of individual transport. By classifying the warning apps available in German-speaking regions it became apparent that apps exist for diverse areas of risk. Some of them are currently under development, others are already in use, but still with minor operational deficits. We found out that till today, the majority of warning services provides either an interim solution with a standalone mobile app, or a first test stage approach for prospective mobility solutions, only working on the basis of a car-to-car or car-to-pedestrian communication. Nevertheless, the effectiveness of warning apps was exemplarily proven by a survey about the Wildwarner, an app for wildlife-vehicle collision warnings. Looking ahead, warning-service-usage scenarios (1) without driving assistance, (2) with driving assistance and (3) fully autonomous driving are gone through, showing the still important but altered interactions between humans, warning information systems, and automated driving systems. From an economical perspective, already existing business models for warning services are identified and evaluated according to whether they could be transferred to business models for future mobility under changing ways of user interaction. The analysis of existing established warning apps indicates that more integrated approaches combining different warning types and delivering them as services either for autonomous vehicle navigation or human drivers ought to be supported for increasing road safety.

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Network Forensics Analysis of iOS Social Networking and Messaging Apps

Cited by 5 publications

References 4 publications

A Comprehensive Survey on Artifact Recovery from Social Media Platforms: Approaches and Future Research Directions

A Comprehensive Survey on Artifact Recovery from Social Media Platforms: Approaches and Future Research Directions

Forensic Analysis of TikTok Alternatives on Android and iOS Devices: Byte, Dubsmash, and Triller

Warning Apps for Road Safety: A Technological and Economical Perspective for Autonomous Driving – The Warning Task in the Transition from Human Driver to Automated Driving

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