Forensic Science International-Digital Investigation最新文献

英文中文

Horodocs: A scalable, sustainable, robust and privacy compliant system to securely timestamp digital evidence and documents

IF 2 4区医学 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS

Forensic Science International-Digital Investigation

Pub Date : 2025-04-15 DOI: 10.1016/j.fsidi.2025.301913

David-Olivier Jaquet-Chiffelle , Ludovic Pfeiffer , Lionel Brocard , Emmanuel Benoist , Noria Foukia

Human activities produce more and more digital traces. Criminal activities are no exception: criminals often operate on computers, carry mobile phones, use GPS devices, or are recorded by surveillance cameras. Moreover, analyses of analog traces can produce results in a digital form. As digital information (evidence or results) becomes highly relevant in today's investigations, there is a pressing need for a trustworthy way to strengthen the chain of custody for digital content, especially its integrity component.

The Horodocs timestamping system responds to the need for a scalable, robust, trustworthy, independently verifiable, chronological ledger preventing backdating and enabling integrity verification of a digital file.

In order to make the system scalable and limit costs, submitted file hash values are grouped together into a local, temporary Merkle tree, called the Horodocs tree; this tree is discarded after its root value has been used to record both a derived identifier and an encrypted random control value on the Ethereum blockchain.¹ The main innovation resides in the way information about the Horodocs tree is provided to each participant having requested a timestamp during the lifespan of this tree. Each submitter gets a receipt with enough information to verify the timestamp for the hash values that were submitted to the Horodocs system: the receipt is only valid for the hash values of the original file and allows one to recalculate the root value of the corresponding discarded Horodocs tree independently. The root value is required to find the record in the Ethereum blockchain and to recover and decrypt the stored random control value to validate the date and time of the timestamp.

Throughout its conception, the Horodocs system has been developed with a concern for strong robustness against backdating, privacy-by-design, transparency, usability, scalability, sustainability, automation, as well as cost and energy savings.

人类活动产生了越来越多的数字痕迹。犯罪活动也不例外：犯罪分子经常在电脑上操作、携带移动电话、使用 GPS 设备或被监控摄像头记录。此外，对模拟痕迹的分析可以产生数字形式的结果。由于数字信息（证据或结果）在当今的调查中变得非常重要，因此迫切需要一种值得信赖的方式来加强数字内容的监管链，特别是其完整性部分。Horodocs 时间戳系统满足了人们对可扩展、稳健、值得信赖、可独立验证、按时间顺序排列的分类账的需求，这种分类账可以防止数字文件的日期倒置并实现完整性验证。为了使系统具有可扩展性并限制成本，提交的文件哈希值被组合成一棵本地的临时梅克尔树，称为 Horodocs 树；这棵树在其根值被用于在以太坊区块链上记录衍生标识符和加密随机控制值之后就会被丢弃1。主要的创新在于，在 Horodocs 树的生命周期内，向每个申请时间戳的参与者提供 Horodocs 树信息的方式。每个提交者都会收到一份收据，其中包含足够的信息来验证提交给 Horodocs 系统的哈希值的时间戳：该收据只对原始文件的哈希值有效，并允许人们独立重新计算相应废弃 Horodocs 树的根值。需要根值才能在以太坊区块链中找到记录，并恢复和解密存储的随机控制值，以验证时间戳的日期和时间。Horodocs 系统在整个构思过程中，一直关注其强大的鲁棒性，以防止反向操作、隐私设计、透明度、可用性、可扩展性、可持续性、自动化以及成本和能源节约。

{"title":"Horodocs: A scalable, sustainable, robust and privacy compliant system to securely timestamp digital evidence and documents","authors":"David-Olivier Jaquet-Chiffelle , Ludovic Pfeiffer , Lionel Brocard , Emmanuel Benoist , Noria Foukia","doi":"10.1016/j.fsidi.2025.301913","DOIUrl":"10.1016/j.fsidi.2025.301913","url":null,"abstract":"<div><div>Human activities produce more and more digital traces. Criminal activities are no exception: criminals often operate on computers, carry mobile phones, use GPS devices, or are recorded by surveillance cameras. Moreover, analyses of analog traces can produce results in a digital form. As digital information (evidence or results) becomes highly relevant in today's investigations, there is a pressing need for a trustworthy way to strengthen the chain of custody for digital content, especially its integrity component.</div><div>The Horodocs timestamping system responds to the need for a scalable, robust, trustworthy, independently verifiable, chronological ledger preventing backdating and enabling integrity verification of a digital file.</div><div>In order to make the system scalable and limit costs, submitted file hash values are grouped together into a local, temporary Merkle tree, called the Horodocs tree; this tree is discarded after its root value has been used to record both a derived identifier and an encrypted random control value on the Ethereum blockchain.<span><span><sup>1</sup></span></span> The main innovation resides in the way information about the Horodocs tree is provided to each participant having requested a timestamp during the lifespan of this tree. Each submitter gets a receipt with enough information to verify the timestamp for the hash values that were submitted to the Horodocs system: the receipt is only valid for the hash values of the original file and allows one to recalculate the root value of the corresponding discarded Horodocs tree independently. The root value is required to find the record in the Ethereum blockchain and to recover and decrypt the stored random control value to validate the date and time of the timestamp.</div><div>Throughout its conception, the Horodocs system has been developed with a concern for strong robustness against backdating, privacy-by-design, transparency, usability, scalability, sustainability, automation, as well as cost and energy savings.</div></div>","PeriodicalId":48481,"journal":{"name":"Forensic Science International-Digital Investigation","volume":"53 ","pages":"Article 301913"},"PeriodicalIF":2.0,"publicationDate":"2025-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143829696","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

I know where you have been last summer: Extracting privacy-sensitive information via forensic analysis of the Mercedes-Benz NTG5*2 infotainment system 我知道你去年夏天去了哪里：通过对梅赛德斯-奔驰 NTG5*2 信息娱乐系统的取证分析提取隐私敏感信息

IF 2 4区医学 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS

Forensic Science International-Digital Investigation

Pub Date : 2025-03-14 DOI: 10.1016/j.fsidi.2025.301909

Dario Stabili, Filip Valgimigli, Mirco Marchetti

Modern vehicles are equipped with In-Vehicle Infotainment (IVI) systems that offers different functions, such as typical radio and multimedia services, navigation and internet browsing. To operate properly, IVI systems have to store locally different types of data, reflecting user preferences and behaviors. If stored and managed insecurely, these data might expose sensitive information and represent a privacy risk. In this paper we address this issue by presenting a methodology for the extraction of privacy-sensitive information from the popular

N T G 5

COMMAND IVI system (specifically, the

N T G 5 ⁎ 2

version by Harman), deployed in some Mercedes-Benz vehicles from 2013 to 2019. We show that it is possible to extract information related to geographic locations and various vehicles events (such as ignition and doors opening and closing) dating back to the previous 8 months, and that these data can be cross-referenced to precisely identify the activities and habits of the driver. Moreover, we develop a novel forensic tool to automate this task.¹ Given the past usage of the

N T G 5

system, our work might have real life implications for the privacy of millions of drivers, owners and passengers. As a final contribution, we develop a novel technique for SQLite data carving specifically designed to identify deleted data. Comparison with existing state-of-the-art tools for SQLite3 data recovery demonstrates that our approach is more effective in recovering deleted traces than general purpose tools.

{"title":"I know where you have been last summer: Extracting privacy-sensitive information via forensic analysis of the Mercedes-Benz NTG5*2 infotainment system","authors":"Dario Stabili, Filip Valgimigli, Mirco Marchetti","doi":"10.1016/j.fsidi.2025.301909","DOIUrl":"10.1016/j.fsidi.2025.301909","url":null,"abstract":"<div><div>Modern vehicles are equipped with In-Vehicle Infotainment (IVI) systems that offers different functions, such as typical radio and multimedia services, navigation and internet browsing. To operate properly, IVI systems have to store locally different types of data, reflecting user preferences and behaviors. If stored and managed insecurely, these data might expose sensitive information and represent a privacy risk. In this paper we address this issue by presenting a methodology for the extraction of privacy-sensitive information from the popular <span><math><mi>N</mi><mi>T</mi><mi>G</mi><mn>5</mn></math></span> COMMAND IVI system (specifically, the <span><math><mi>N</mi><mi>T</mi><mi>G</mi><mn>5</mn><mo>⁎</mo><mn>2</mn></math></span> version by Harman), deployed in some Mercedes-Benz vehicles from 2013 to 2019. We show that it is possible to extract information related to geographic locations and various vehicles events (such as ignition and doors opening and closing) dating back to the previous 8 months, and that these data can be cross-referenced to precisely identify the activities and habits of the driver. Moreover, we develop a novel forensic tool to automate this task.<span><span><sup>1</sup></span></span> Given the past usage of the <span><math><mi>N</mi><mi>T</mi><mi>G</mi><mn>5</mn></math></span> system, our work might have real life implications for the privacy of millions of drivers, owners and passengers. As a final contribution, we develop a novel technique for SQLite data carving specifically designed to identify deleted data. Comparison with existing state-of-the-art tools for SQLite3 data recovery demonstrates that our approach is more effective in recovering deleted traces than general purpose tools.</div></div>","PeriodicalId":48481,"journal":{"name":"Forensic Science International-Digital Investigation","volume":"53 ","pages":"Article 301909"},"PeriodicalIF":2.0,"publicationDate":"2025-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143620486","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Blind protocol identification using synthetic dataset: A case study on geographic protocols

IF 2 4区医学 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS

Forensic Science International-Digital Investigation

Pub Date : 2025-03-13 DOI: 10.1016/j.fsidi.2025.301911

Mohammad Abbasi-Azar , Mehdi Teimouri , Mohsen Nikray

Network forensics faces major challenges, including increasingly sophisticated cyberattacks and the difficulty of obtaining labeled datasets for training AI-driven security tools. Blind Protocol Identification (BPI), essential for detecting covert data transfers, is particularly impacted by these data limitations. This paper introduces a novel and inherently scalable method for generating synthetic datasets tailored for BPI in network forensics. Our approach emphasizes feature engineering and a statistical-analytical model of feature distributions to address the scarcity and imbalance of labeled data. We demonstrate the effectiveness of this method through a case study on geographic protocols, where we train Random Forest models using only synthetic datasets and evaluate their performance on real-world traffic. This work presents a promising solution to the data challenges in BPI, enabling reliable protocol identification while maintaining data privacy and overcoming traditional data collection limitations.

引用次数: 0

A review study of digital forensics in IoT: Process models, phases, architectures, and ontologies

IF 2 4区医学 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS

Forensic Science International-Digital Investigation

Pub Date : 2025-03-10 DOI: 10.1016/j.fsidi.2025.301912

Thiago J. Silva , Edson OliveiraJr , Maximiano Eduardo Pereira , Avelino F. Zorzo

The Internet of Things (IoT) involves integrating uniquely identifiable computing devices into various infrastructures. Technological advancements have led to a proliferation of interconnected devices in public and private infrastructures, such as healthcare, transportation, and manufacturing. However, this expansion also presents significant challenges, including managing large volumes of data, navigating diverse infrastructures, dealing with network limitations, and lacking standards in IoT device formats. The increase in digital crimes has spurred the growth of the Digital Forensics (DF) field, which plays a crucial role in various interdisciplinary contexts. DF involves analyzing digital crime-related data and going through phases such as identification, collection, organization, and presentation of evidence. As DF develops, there are emerging structural and methodological initiatives aimed at formalizing concepts and establishing a common vocabulary. The literature has proposed various frameworks, conceptual models, methodologies, and ontologies to support this area. To identify and examine existing models, frameworks, methodologies, or ontologies for digital forensics on the Internet of Things (IoT), this article presents a systematic literature review (SLR). The systematic literature review outlined methods for constructing models, different types of models, feasibility criteria, evaluation methods, and models for different stages and aspects of DF. The findings were derived from an analysis of 23 primary studies, which helped address four specific research questions. Additionally, the paper suggests further model-based assistance for DF research, aiming to assist researchers and professionals in addressing current research gaps. The contributions of this work aim to fill the gaps imposed by the practical implications for digital forensic investigators in IoT. In this case, one can mention the use of DF models and phases to assist in the analysis of evidence, recoveries, information, and identification of data patterns sent via IoT.

{"title":"A review study of digital forensics in IoT: Process models, phases, architectures, and ontologies","authors":"Thiago J. Silva , Edson OliveiraJr , Maximiano Eduardo Pereira , Avelino F. Zorzo","doi":"10.1016/j.fsidi.2025.301912","DOIUrl":"10.1016/j.fsidi.2025.301912","url":null,"abstract":"<div><div>The Internet of Things (IoT) involves integrating uniquely identifiable computing devices into various infrastructures. Technological advancements have led to a proliferation of interconnected devices in public and private infrastructures, such as healthcare, transportation, and manufacturing. However, this expansion also presents significant challenges, including managing large volumes of data, navigating diverse infrastructures, dealing with network limitations, and lacking standards in IoT device formats. The increase in digital crimes has spurred the growth of the Digital Forensics (DF) field, which plays a crucial role in various interdisciplinary contexts. DF involves analyzing digital crime-related data and going through phases such as identification, collection, organization, and presentation of evidence. As DF develops, there are emerging structural and methodological initiatives aimed at formalizing concepts and establishing a common vocabulary. The literature has proposed various frameworks, conceptual models, methodologies, and ontologies to support this area. To identify and examine existing models, frameworks, methodologies, or ontologies for digital forensics on the Internet of Things (IoT), this article presents a systematic literature review (SLR). The systematic literature review outlined methods for constructing models, different types of models, feasibility criteria, evaluation methods, and models for different stages and aspects of DF. The findings were derived from an analysis of 23 primary studies, which helped address four specific research questions. Additionally, the paper suggests further model-based assistance for DF research, aiming to assist researchers and professionals in addressing current research gaps. The contributions of this work aim to fill the gaps imposed by the practical implications for digital forensic investigators in IoT. In this case, one can mention the use of DF models and phases to assist in the analysis of evidence, recoveries, information, and identification of data patterns sent via IoT.</div></div>","PeriodicalId":48481,"journal":{"name":"Forensic Science International-Digital Investigation","volume":"53 ","pages":"Article 301912"},"PeriodicalIF":2.0,"publicationDate":"2025-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143579615","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Corrigendum to “Adding transparency to uncertainty: An argument-based method for evaluative opinions” [FSIDI 48 (2023) 301657]

IF 2 4区医学 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS

Forensic Science International-Digital Investigation

Pub Date : 2025-03-05 DOI: 10.1016/j.fsidi.2025.301910

Nina Sunde , Virginia N.L. Franqueira

引用次数: 0

Welcome to the 12th Annual DFRWS Europe Conference!

IF 2 4区医学 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS

Forensic Science International-Digital Investigation

Pub Date : 2025-03-01 DOI: 10.1016/j.fsidi.2025.301879

Edita Bajramovic, Olga Angelopoulou

引用次数: 0

A scenario-based quality assessment of memory acquisition tools and its investigative implications

IF 2 4区医学 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS

Forensic Science International-Digital Investigation

Pub Date : 2025-03-01 DOI: 10.1016/j.fsidi.2025.301868

Lisa Rzepka , Jenny Ottmann , Radina Stoykova , Felix Freiling , Harald Baier

During digital forensic investigations volatile data from random-access memory (RAM) can provide crucial information such as access credentials or encryption keys. This data is usually obtained using software that copies contents of RAM to a memory dump file concurrently to normal system operation. It is well-known that this results in many inconsistencies in the copied data. Based on established quality criteria from the literature and on four typical investigative scenarios, we present and evaluate a methodology to assess the quality of memory acquisition tools in these scenarios. The methodology basically relates three factors: (1) the quality criteria of the memory dump, (2) the applied memory forensics analysis technique, and (3) its success in the given investigative scenario. We apply our methodology to four memory acquisition tools (from both the open source and the commercial community). It turns out that all tools have weaknesses but that their inconsistencies appear to be not as bad as anticipated. Another finding is that unstructured memory analysis methods are more robust against low quality (i.e., inconsistent) memory dumps than structured analysis methods. We provide the measurement dataset together with the tool by which it was acquired and also examine our findings in the context of legal and international standards for digital forensics in law enforcement investigations.

{"title":"A scenario-based quality assessment of memory acquisition tools and its investigative implications","authors":"Lisa Rzepka , Jenny Ottmann , Radina Stoykova , Felix Freiling , Harald Baier","doi":"10.1016/j.fsidi.2025.301868","DOIUrl":"10.1016/j.fsidi.2025.301868","url":null,"abstract":"<div><div>During digital forensic investigations volatile data from random-access memory (RAM) can provide crucial information such as access credentials or encryption keys. This data is usually obtained using software that copies contents of RAM to a memory dump file concurrently to normal system operation. It is well-known that this results in many inconsistencies in the copied data. Based on established quality criteria from the literature and on four typical investigative scenarios, we present and evaluate a methodology to assess the quality of memory acquisition tools in these scenarios. The methodology basically relates three factors: (1) the quality criteria of the memory dump, (2) the applied memory forensics analysis technique, and (3) its success in the given investigative scenario. We apply our methodology to four memory acquisition tools (from both the open source and the commercial community). It turns out that all tools have weaknesses but that their inconsistencies appear to be not as bad as anticipated. Another finding is that unstructured memory analysis methods are more robust against low quality (i.e., inconsistent) memory dumps than structured analysis methods. We provide the measurement dataset together with the tool by which it was acquired and also examine our findings in the context of legal and international standards for digital forensics in law enforcement investigations.</div></div>","PeriodicalId":48481,"journal":{"name":"Forensic Science International-Digital Investigation","volume":"52 ","pages":"Article 301868"},"PeriodicalIF":2.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143679790","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Tapping .IPAs: An automated analysis of iPhone applications using apple silicon macs

IF 2 4区医学 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS

Forensic Science International-Digital Investigation

Pub Date : 2025-03-01 DOI: 10.1016/j.fsidi.2025.301871

Steven Seiden , Andrew M. Webb , Ibrahim Baggili

Dynamic analysis of iOS applications poses significant challenges due to the platform's stringent security measures. Historically, investigations often required jailbreaking, but recent enhancements in iOS security have diminished the viability of this approach. Consequently, alternative methodologies are necessary. In this study, we explore the feasibility of automated iOS application analysis on the ARM-based M1 Mac platform. To do so, we utilized an ARM-based Mac to install several popular iOS applications. Our manual analysis using existing macOS tools demonstrated the potential to uncover artifacts such as chat messages and browsing history. To streamline this process, we developed a tool, AppTap, which facilitates the entire forensic procedure from installation to artifact extraction. AppTap enables analysts to quickly install, test, and retrieve file system artifacts from these applications and allows for the easy checkpointing of user files generated by iOS apps. These checkpoints help analysts correlate artifacts with user actions. We tested AppTap with the top 100 iPhone apps and top 100 iPhone games from the U.S. App Store (n=200). Our results showed that 46 % of these applications were installed and operated as expected, while 30.5% failed to install, likely due to the older macOS version—a necessary condition for this study. We discuss several strategies to enhance application support in the future, which could significantly increase the number of supported applications. Applying our methodologies as-is to the M1 Mac platform has significantly streamlined the forensic process for iOS applications, saving time for analysts and expanding future capabilities.

{"title":"Tapping .IPAs: An automated analysis of iPhone applications using apple silicon macs","authors":"Steven Seiden , Andrew M. Webb , Ibrahim Baggili","doi":"10.1016/j.fsidi.2025.301871","DOIUrl":"10.1016/j.fsidi.2025.301871","url":null,"abstract":"<div><div>Dynamic analysis of iOS applications poses significant challenges due to the platform's stringent security measures. Historically, investigations often required jailbreaking, but recent enhancements in iOS security have diminished the viability of this approach. Consequently, alternative methodologies are necessary. In this study, we explore the feasibility of automated iOS application analysis on the ARM-based M1 Mac platform. To do so, we utilized an ARM-based Mac to install several popular iOS applications. Our manual analysis using existing macOS tools demonstrated the potential to uncover artifacts such as chat messages and browsing history. To streamline this process, we developed a tool, <em>AppTap</em>, which facilitates the entire forensic procedure from installation to artifact extraction. AppTap enables analysts to quickly install, test, and retrieve file system artifacts from these applications and allows for the easy checkpointing of user files generated by iOS apps. These checkpoints help analysts correlate artifacts with user actions. We tested AppTap with the top 100 iPhone apps and top 100 iPhone games from the U.S. App Store (<em>n</em>=200). Our results showed that 46 % of these applications were installed and operated as expected, while 30.5% failed to install, likely due to the older macOS version—a necessary condition for this study. We discuss several strategies to enhance application support in the future, which could significantly increase the number of supported applications. Applying our methodologies as-is to the M1 Mac platform has significantly streamlined the forensic process for iOS applications, saving time for analysts and expanding future capabilities.</div></div>","PeriodicalId":48481,"journal":{"name":"Forensic Science International-Digital Investigation","volume":"52 ","pages":"Article 301871"},"PeriodicalIF":2.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143679881","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Forensic analysis of Telegram Messenger on iOS smartphones

IF 2 4区医学 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS

Forensic Science International-Digital Investigation

Pub Date : 2025-03-01 DOI: 10.1016/j.fsidi.2025.301866

Lukas Jaeckel, Michael Spranger, Dirk Labudde

As mobile messengers have dominated and penetrated our daily communication and activities, the odds of them being involved in criminal activities have increased. Since each messenger usually uses its own proprietary data schema (including encoding, encryption and frequent updates) to store communication data, with a pressing demand, investigative authorities require a solution to transfer the data in a processable structure to analyse it efficiently, especially in a forensic context. Therefore, this work identifies and examines locally stored data of the Telegram Messenger with high forensic value on iOS devices. In particular, this work deals with extracting contact and communication data to link and analyse it. For this purpose, artificially generated test data, as well as the open source code of the Telegram Messenger under iOS, are analysed. The main focus of this work lies on the primary database in which a large part of data is coded and, therefore, needs to be transferred into an interpretable form. In summary, this work enables a manual or automated analysis of Messenger data for investigative authorities and IT companies with forensic reference. The proposed method can also be adapted in research to analyse further instant messaging services.

{"title":"Forensic analysis of Telegram Messenger on iOS smartphones","authors":"Lukas Jaeckel, Michael Spranger, Dirk Labudde","doi":"10.1016/j.fsidi.2025.301866","DOIUrl":"10.1016/j.fsidi.2025.301866","url":null,"abstract":"<div><div>As mobile messengers have dominated and penetrated our daily communication and activities, the odds of them being involved in criminal activities have increased. Since each messenger usually uses its own proprietary data schema (including encoding, encryption and frequent updates) to store communication data, with a pressing demand, investigative authorities require a solution to transfer the data in a processable structure to analyse it efficiently, especially in a forensic context. Therefore, this work identifies and examines locally stored data of the Telegram Messenger with high forensic value on iOS devices. In particular, this work deals with extracting contact and communication data to link and analyse it. For this purpose, artificially generated test data, as well as the open source code of the Telegram Messenger under iOS, are analysed. The main focus of this work lies on the primary database in which a large part of data is coded and, therefore, needs to be transferred into an interpretable form. In summary, this work enables a manual or automated analysis of Messenger data for investigative authorities and IT companies with forensic reference. The proposed method can also be adapted in research to analyse further instant messaging services.</div></div>","PeriodicalId":48481,"journal":{"name":"Forensic Science International-Digital Investigation","volume":"52 ","pages":"Article 301866"},"PeriodicalIF":2.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143679788","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Preserving meaning of evidence from evolving systems

IF 2 4区医学 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS

Forensic Science International-Digital Investigation

Pub Date : 2025-03-01 DOI: 10.1016/j.fsidi.2025.301867

Hannes Spichiger , Frank Adelstein

Preservation is generally considered as the step in the forensic process that stops evidence from decaying. In this paper, we argue that the traditional scope of preservation in digital forensic science, focused on the trace, is not sufficient to ensure the stop of decay in the context of evolving systems. Instead, insufficiently preserved reference material may lead to the loss of meaning, resulting in an overall increase of uncertainty in the presented evidence. An expanded definition of Preservation and a definition of Reference Data are proposed. We present suggestions for future avenues of research of ways to preserve reference data in order to avoid a loss of meaning of the trace data.

引用次数: 0

下一页尾页

类型

全部化学•材料生命科学医学物理工程技术环境•农林材料科学地球科学法学管理学化学环境科学与生态学计算机科学教育学经济学农林科学人文科学生物学数学物理与天体物理心理学综合性期刊其他工业工程理学历史学农学文学信息工程

数据库

全部 ACS Publications Elsevier ieeexplore Springer The Royal Society of Chemistry Wiley

期刊

Forensic Science International-Digital Investigation

全部 Acc. Chem. Res. ACS Applied Bio Materials ACS Appl. Electron. Mater. ACS Appl. Energy Mater. ACS Appl. Mater. Interfaces ACS Appl. Nano Mater. ACS Appl. Polym. Mater. ACS BIOMATER-SCI ENG ACS Catal. ACS Cent. Sci. ACS Chem. Biol. ACS Chemical Health & Safety ACS Chem. Neurosci. ACS Comb. Sci. ACS Earth Space Chem. ACS Energy Lett. ACS Infect. Dis. ACS Macro Lett. ACS Mater. Lett. ACS Med. Chem. Lett. ACS Nano ACS Omega ACS Photonics ACS Sens. ACS Sustainable Chem. Eng. ACS Synth. Biol. Anal. Chem. BIOCHEMISTRY-US Bioconjugate Chem. BIOMACROMOLECULES Chem. Res. Toxicol. Chem. Rev. Chem. Mater. CRYST GROWTH DES ENERG FUEL Environ. Sci. Technol. Environ. Sci. Technol. Lett. Eur. J. Inorg. Chem. IND ENG CHEM RES Inorg. Chem. J. Agric. Food. Chem. J. Chem. Eng. Data J. Chem. Educ. J. Chem. Inf. Model. J. Chem. Theory Comput. J. Med. Chem. J. Nat. Prod. J PROTEOME RES J. Am. Chem. Soc. LANGMUIR MACROMOLECULES Mol. Pharmaceutics Nano Lett. Org. Lett. ORG PROCESS RES DEV ORGANOMETALLICS J. Org. Chem. J. Phys. Chem. J. Phys. Chem. A J. Phys. Chem. B J. Phys. Chem. C J. Phys. Chem. Lett. Analyst Anal. Methods Biomater. Sci. Catal. Sci. Technol. Chem. Commun. Chem. Soc. Rev. CHEM EDUC RES PRACT CRYSTENGCOMM Dalton Trans. Energy Environ. Sci. ENVIRON SCI-NANO ENVIRON SCI-PROC IMP ENVIRON SCI-WAT RES Faraday Discuss. Food Funct. Green Chem. Inorg. Chem. Front. Integr. Biol. J. Anal. At. Spectrom. J. Mater. Chem. A J. Mater. Chem. B J. Mater. Chem. C Lab Chip Mater. Chem. Front. Mater. Horiz. MEDCHEMCOMM Metallomics Mol. Biosyst. Mol. Syst. Des. Eng. Nanoscale Nanoscale Horiz. Nat. Prod. Rep. New J. Chem. Org. Biomol. Chem. Org. Chem. Front. PHOTOCH PHOTOBIO SCI PCCP Polym. Chem.

﹀