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Examination of Digital Evidence on Android-based LINE Messenger.

1. INTRODUCTION

In September 2008, the very first Android smartphone was announced to the public although in 2007 the beta version of Android was launched internally in form of handset code-named "Sooner" [1]. Android smartphone is being popular during the last decade. The number of Android smartphones sold increased from about 220 million units in 2011 to around 1.2 billion in 2015 [2]. In 2018, Android has 13 names of version that always named by candy or dessert name.

The more Android versions the more various applications come up. One of them is instant messaging (IM) application. LINE messenger is one of IM that popular in Asian. LINE is ranked among the ten most successful mobile messenger applications in the world [2]. At the same time, LINE is the second most successful on the Asian market. Figure 1 shows the amount of monthly active LINE users worldwide in 2016. There are around 202.11 million average of LINE's active users in 4th quarter 2016.
Figure 1. Number of monthly active LINE users worldwide in 2016

Number of monthly active LINE users worldwide as of 4th quarter 2016
(in millions)

170     179     190     205     211     212     215     218.4

Q2 '14  Q3 '14  Q4 '14  Q1 '15  Q2 '15  Q3 '15  Q4 '15  Q1 '16

220     220     217

Q2 '16  Q3 '16  Q4. '16

Additional Information:
Worldwide: UNE: 2nd quarter 2014 to 4th quarter 2016

Source UNE [c] Statists 2018

Note: Table made from bar graph.


The widespread use of Android device makes it an inevitable source for forensic analysis both from the criminal and non-criminal point of view [3]. The widespread use of social networking applications also can increase the risk of cybercrime. One of cybercrime is being lively nowadays is cyberbullying [4]. Cyberbullying is an aggressive behavior which refers to bullying behavior by a person through social media such as web, messaging, social networking, chat rooms, etc. [5]. The crime scene in an Android device is able to solve by the mobile device forensics techniques.
Figure 2. Branches of Digital Forensics

Digital Forensics  Computer Forensics
                   Mobile Device Forensics
                   Network Forensics
                   Memory Forensics
                   Email Forensics


As seen as Figure 2, digital forensics has at least five branches of study fields. One of them is mobile device forensics. Mobile device forensics is a branch of digital forensic used for recovery of digital evidence from a mobile device.

The problem in the forensic field are many forensic tools that are not 100% as expected in their use. For this reason, NIST suggested a forensic tools testing on smartphones [6]. This also becomes a concern for the researchers. There are several research on this issue. Iqbal et. al. [7] studied the artifacts left by LINE messenger. The analysis was conducted on an iPhone running iOS6 and a HTC One Android v5. In this investigation, the text messages were successfully retrieved, but messages sent during a private messaging session were not retrieved in all scenarios. The authors use SQlite DB Browser to find database inside the mobile device.

Chang et. al [8] studied the identification of LINE's artifact. The authors focus on both the volatile memory and non-volatile memory artifacts inside a virtual machine. The author showed that this apps on volatile memory has proved that critical application data is present in the RAM and it can be extracted for further examination and analysis. The non-volatile memory analysis has shown that LINE messenger activities remain some artifacts in different locations.

Riadi, et. al. [9] studied about the technique of a forensic tools in identifying artifact in LINE messenger. The authors were able to show differences in two techniques of MOBILedit to identifying LINE' s digital evidence on Android platform.

Based on the studies above and some background issues, the researchers have a reason to conduct the experiment about the ability of forensic tools in LINE's digital evidence examination. This article was focused on the analysis of MOBILedit and Oxygen forensic ability in examination process.

2. BASIC THEORY

2.1 Digital Evidence

Nowadays, mobile phones do not only transfer voice and text message, they have become a multipurpose device that can transfer multimedia files, perform video streaming, internet browsing and other operation that relates to data transfer [10]. The data transferring between electronic gadget to server leaving the digital trace, or it could be a digital evidence. Digital evidence is information stored or transmitted in the binary form that may be relied on in court [11]. It can be found in hard drive, flash drive, phones, mobile devices, routers, tablets, and instruments such as GPS [12]. Digital evidence is fragile, volatile and vulnerable if it is not handled properly [13]. Digital evidence is commonly associated with digital or electronic crime, such as pornography, prostitution, identity theft, phishing, or credit card fraud [14]. However, digital evidence is now used to prosecute all types of crimes, not just digital crimes.

2.2 Mobile Device Forensics

Mobile device forensics is a branch of digital forensics and refers to the preservation, data acquisition, examination, and analysis of mobile devices such as cell phones, smartphones, music players, tablets, Global Positioning Systems (GPS), and other types of mobile devices [15]. Basically, it used to recover any data in the mobile device that recognized to be a digital evidence by Law. This is very useful in crime-proving in the court.

2.3 Cybercrime

According to United Nations's comprehensive study, Cybercrime is a limited number of acts against the confidentiality, integrity, and availability (CIA) of computer data or systems [16]. Cybercrime can be happened in any electronic devices, like Android smartphone. Based on this understanding, cybercrime is formulated as an act against the law that is done by using a network of electronic devices as a tool or electronic device as an object, whether to gain profit or not, and there are elements harmful to others [17].

2.4 LINE Messenger

LINE is an instant messenger application launched in Japan since June 2011 [18]. LINE messenger is one of IM provides their users by phone number registration. There are many features in LINE messenger, such as private chat, group chat, stickers, etc. Despite the advantages imparted by LINE, it is vulnerable to threats. LINE IM application sends messages unencrypted over the internet [19].

2.5 Oxygen Forensic

This tool has several features which can be selected in a criminal case. Oxygen Forensic has the ability to perform logical acquisition and physical acquisition [20]. Oxygen Forensic Suite also has the capability to provide general information about the smartphone and the network that the device was connected to [14].

2.6 MOBILedit Forensic

MOBILedit is a forensic tool that has the ability to perform logical acquisition and physical acquisition like Oxygen Forensic. This software is good enough to be used to obtain phone system information and other information such as contacts, text messages, and picture. MOBILedit supports extraction and viewing data from different sources such as; Contact book, call history, text and multimedia messages, files, calendars, notes, reminders, raw application data, IMEI, operating systems, firmware including SIM details (IMSi), ICCID and location area information [3].

3 TOOLS AND METHODOLOGY

The main objective of this study is to evaluate the performance of some existing mobile forensics tools in acquiring data, from LINE messenger application, such as text, picture, audio, and video. In this section, we discuss the materials used and methods adopted for evaluation.

3.1 Tools Requirements

The materials, hardware, and software, used to achieve the objective of the study include:

This study was focused on data that could be acquired from a smartphone. The technique of extracting data is the physical acquisition. It means the smartphone must be rooted already in gaining data easier. LINE messenger is unable to extract nicely with the logical acquisition.

3.2 Research methodology

The research used the steps as in Figure 3. The steps of the research are divided into four: device acquisition, LINE messenger examination, data analysis, and conclusion.
Figure 3. Research Methodology

Start
Device Acquisition
LINE Messenger
Examination
Data Analysis
Conclusion
End


* Device acquisition: Figure 4 shows the brief process of acquisition performed. The data from gadget was recovered and sorted in a list of each category.

* LINE Messenger examination: The researchers will perform forensic analysis on smartphone devices using the Oxygen forensics, and MOBILedit forensic. The forensic analysis will be conducted under closed conditions in the sense that smartphone devices will be converted into Airplane Mode to maintain data integrity.

* Data Analysis: The performance of each forensic tool will be analyzed using a comparison table.

* Conclusion: classifying the ability of each forensic tool.

4 RESULT AND DISCUSSION

4.1 Oxygen Forensic

Oxygen Forensic has the ability to perform logical acquisition and physical acquisition. Oxygen Forensic successfully obtains smartphone device information. Figure 5 shows LINE messenger chat text artifacts obtained using Oxygen forensic. Text message artifact from LINE messenger can be generated only from the physical acquisition. Oxygen forensic also able to perform timeline analysis that can be used by the expert to explain the conversation history from all calls, messages, calendar events, geo-data, and applications activities in a chronological way, as seen as in Figure 6. This feature is very useful for doing timeframe analysis that defined by U.S. Department of Justice (DOJ) as determining when events occurred on the system by reviewing any logs and time stamps in the file system [6].

4.2 MOBILedit Forensic

Just like oxygen forensic, MOBILedit forensic also has the ability to perform the logical and physical acquisition. MOBILedit Forensic successfully obtains smartphone device information. MOBILedit was able to identify the IMEI number of both mobile phones, IMSI and ICCID of the registered SIM cards.

MOBILedit was succeeded to gain contact information, text message, and picture from LINE messenger while video artifact was unable to perform in MOBILedit acquisition. The picture artifact as in Figure 7 has a brief information about the path of the file, size of the file, created and modified the file. The picture file can be a clue to investigate the production of this file.

Figure 8 is a piece of text conversation in LINE messenger. The text conversation also shows an incoming picture and outgoing picture that occur in this section of chat. But in this text conversation, there is a problem in sorting the chronological timeline.

MOBILedit was also success to gain deleted contact data as seen as in Figure 9. This particular data can be a clue to accuse the suspect statements about the deleted contact.

As in Table 2, we can see the difference result from both forensic tools ability in digital evidence examination. Both of them were successful to recover text messages and contact information from LINE messenger. MOBILedit forensic seems more has advantage than Oxygen forensics in the amount of file examined. Nevertheless, Oxygen has the advantage in data analysis features, those are timeline and social graph.

5 CONCLUSION AND FUTURE WORK

Based on the forensic tool experiment in digital evidence from Android-based LINE messenger examination that has been discussed, it can be concluded:

Oxygen forensics was good to perform timeline analysis. This is useful for the examiner in an investigation. Oxygen forensic success to gain text messages, but it failed to gain any picture or video files from LINE messenger acquisition. MOBILedit was able to gain text messages, pictures, and also deleted contact data. In the examination process, MOBILedit was failed to sorting the chronological conversation on LINE messenger. However, it still good considering there is a timestamp section in each text message.

There are a lot of forensic tools that have not been tested in a specific case as same as in LINE messenger. A future research perspective should include the analysis of different instant messaging applications by a group of different forensic tools. This analysis also needs to conduct on different mobile platforms because it can affect the result.

REFERENCES

[1] J. Callaham, "The history of Android OS: its name, origin and more," Androidauthority.com, 2018. [Online]. Available: https://www.androidauthority.com/history-android-os-name-789433/. [Accessed: 27-Apr-2018].

[2] Statista, "Global smartphone sales by operating system from 2009 to 2017 (in millions)," Statista.com, 2018. [Online]. Available: https://www.statista.com/statistics/263445/global-smartphone-sales-by-operating-system-since-2009/. [Accessed: 27-Apr-2018].

[3] N. R. Roy, A. K. Khanna, and L. Aneja, "Android phone forensic:

Tools and techniques," in Proceeding - IEEE International Conference on Computing, Communication and Automation, ICCCA 2016, 2017, pp. 605-610.

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[5] D. Satalina, "Cyberbullying Behavior Tendency Of Extrovert And Introvert Personality Type," J. Ilm. Psikol. Terap., vol. 2, no. 2, pp. 294-310, 2014.

[6] R. Ayers, S. Brothers, and W. Jansen, "Guidelines on mobile device forensics," NIST Spec. Publ., vol. 1, no. 1, p. 85, 2014.

[7] A. Iqbal, H. Alobaidli, A. Almarzooqi, and A. Jones, "LINE IM app Forensic Analysis."

[8] M. S. Chang and C. Y. Chang, "Forensic Analysis of LINE Messenger on Android," J. Comput., vol. 29, no. 1, pp. 11-20, 2018.

[9] I. Riadi, A. Fadlil, and A. Fauzan, "Evidence Gathering and Identification of LINE Messenger on Android Device," Int. J. Comput. Sci. Inf. Secur. (IJCSIS), vol. 16, no. June, pp. 201-205, 2018.

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[15] G. C. Kessler, "Are mobile device examinations practiced like 'forensics'?," Digit. Evid. Electron. Signat. Law Rev., vol. 12, pp. 3-9, 2015.

[16] UNODC, "Comprehensive Study on Cybercrime," Vienna, 2013.

[17] J. Clough, Cybercrime Principles. Cambridge: Cambridge University Press, 2010.

[18] A. Iqbal, H. Alobaidli, A. Almarzooqi, and A. Jones, "LINE IM app Forensic Analysis," 12th Int. Conf. High-capacity Opt. Networks Enabling/Emerging Technol. (HONET-ICT 2015) poster, no. IM, 2015.

[19] V. Jain, D. R. Sahu, and D. S. Tomar, "Evidence Gathering of Line Messenger on iPhones," Int. J. Innov. Eng. Manag., vol. 4, no. 2, pp. 1-9, 2015.

[20] R. Umar, I. Riadi, and G. Maulana, "A Comparative Study of Forensic Tools for WhatsApp Analysis using NIST Measurements," Int. J. Adv. Comput. Sci. Appl., vol. 8, no. 12, 2017.

Imam Riadi (1), Sunardi (2), Ammar Fauzan (3)

(1) Department of Information System, Universitas Ahmad Dahlan

(2,3) Department of Informatics Engineering, Universitas Ahmad Dahlan Jl. Prof. DR. Soepomo S.H., Warungboto, Umbulharjo, Kota Yogyakarta, Daerah Istimewa Yogyakarta 55164

(1) imam.riadi@is.uad.ac.id, (2) sunardi@mti.uad.ac.id, (3) ammar1607048001@webmail.uad.ac.id
Table 1. Tools requirements

Tools             Specification

Asus Zenfone C    Android 4.4.2 (KitKat),
                  Internal 8 GB, Removable
                  GSM/HSPA Network, Dual
                  SIM, Rooted
LINE messenger    Ver. 6.60
                  ASUS Intel Core i3
Workstation       processor, RAM 4 GB,
                  HDD 500GB, OS: Win 10
USB Cable         Ver. 2.0
Oxygen Forensics  Oxygen Forensics
                  Ver. 6.4
MOBILedit         MOBILedit! Forensic
                  version 9.0

Table 2. The comparison result of the forensic tools

No.  Type of file   Oxygen                   MOBILedit
                    Forensics                Forensic

1    Text messages  [square root of (term)]  [square root of (term)]
2    Picture/photo  X                        [square root of (term)]
3    Video          X                        X
4    Audio          X                        X
5    Contact        [square root of (term)]  [square root of (term)]
     Information
6    Document       X                        X
7    Call logs      X                        X
8    Deleted data   X                        [square root of (term)]
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Article Details
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Author:Riadi, Imam; Sunardi; Fauzan, Ammar
Publication:International Journal of Cyber-Security and Digital Forensics
Article Type:Case study
Date:Sep 1, 2018
Words:2685
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