Forensic analysis of open-source XMPP/Jabber multi-client instant messaging apps on Android smartphones

In the quest for a panacea to ensure digital privacy, many users have switched to using decentralized open-source Extensible Messaging and Presence Protocol multi-client instant messaging (IM) apps for secure end-to-end communication. In this paper, we present a forensic analysis of the artefacts generated on Android smartphones by Conversations and Xabber apps. We identified databases maintained by each app and external Secure Digital card directories that store local copies of user metadata. We analysed each app’s storage locations for forensic artefacts and how they can be used in a forensic investigation. The results in this paper show a detailed analysis of forensic files of interest which can be correlated to identify the local user’s multiple IM accounts and contact list, contents of messages exchanged with contacts, deleted files, time, and dates in the order of their occurrence. The contributions of this research include a comprehensive description of artefacts, which are of forensic interest, for each app analysed

Forensic analysis of open-source XMPP multi-client social networking apps on iOS devices

In this paper, we present forensic analysis of Monal and Siskin IM, two decentralized open-source XMPP multi-client social networking apps on iOS devices that provide anonymity and privacy using OMEMO end-to-end encryption. We identified databases maintained by each app and storage locations within the iOS file system that stores the local copies of user information and metadata. We analyzed the databases and storage locations for evidential data of forensic value. The results in this paper show a detailed analysis and correlation of data stored in each app's database to identify the local user's multiple IM accounts and contact list, contents of messages exchanged with contacts, and chronology of conversations. The focus and main contributions of this study include a detailed description of artifacts of forensic interest that can be used to aid mobile forensic investigations

Virtual reality forensics: Forensic analysis of Meta Quest 2

The Meta Quest 2 is one of the most popular Virtual Reality (VR) entertainment headsets to date. The headset, developed by Meta Platforms Inc., immerses the user in a completely simulated environment. Some VR environments can be shared over the Internet to allow users to communicate and interact with one another and share their experiences. Unfortunately, the safety of these VR environments cannot always be guaranteed, generating a risk that users may be exposed to illicit online behaviour in the form of online harassment, grooming, and cyberbullying. Therefore, forensic examiners must be able to conduct sound forensic analysis of VR headsets to investigate these criminal investigations. In this study, we conduct digital forensic acquisition and analysis of the Meta Quest 2 VR headset. Analysis of the forensic image exemplified that there were several digital artefacts relating to user activities, device information and stored digital artefacts that can be extracted in a forensically sound manner. The main contributions of this study include a detailed description of the forensic acquisition process, identification of internal file storage locations, and recovery and analysis of digital artefacts that can be used to aid VR forensic investigations

Forensic analysis of ephemeral messaging applications: Disappearing messages or evidential data?

Ephemeral messaging or ‘disappearing messages’ is the mobile-to-mobile transmission of multimedia messages that automatically disappear from the recipient's screen after the message has been viewed. This new feature can be enabled by users for more privacy when using instant messaging apps. A user can set messages to disappear within a certain timeframe: 24 hours, 7 days, or 90 days, after the time they are sent. While disappearing messages provide additional privacy to users, its anti-forensics capability creates challenges for investigators in the recovery of evidential artefacts that could be crucial to an investigation. In this paper, we conduct a comprehensive forensic analysis of ‘disappearing messages’ across different digital platforms (mobile, desktop, and cloud) and instant messaging apps (WhatsApp, Snapchat, and Telegram) to determine whether they can be recovered within a limited timeframe. The results from this study provide valuable information to investigators dealing with instant messaging apps that have this feature enabled and provides detailed understanding of how disappearing messages are stored, managed, and deleted compared to messages sent without this feature enabled

A systematic literature review of blockchain-based Internet of Things (IoT) forensic investigation process models

Digital forensic examiners and stakeholders face increasing challenges during the investigation of Internet of Things (IoT) environments due to the heterogeneous nature of the IoT infrastructure. These challenges include guaranteeing the integrity of forensic evidence collected and stored during the investigation process. Similarly, they also encounter challenges in ensuring the transparency of the investigation process which includes the chain-of-custody and evidence chain. In recent years, some blockchain-based secure evidence models have been proposed especially for IoT forensic investigations. These proof-of-concept models apply the inherent properties of blockchain to secure the evidence chain of custody, maintain privacy, integrity, provenance, traceability, and verification of evidence collected and stored during the investigation process. Although there have been few prototypes to demonstrate the practical implementation of some of these proposed models, there is a lack of descriptive review of these blockchain-based IoT forensic models. In this paper, we report a comprehensive Systematic Literature Review (SLR) of the latest blockchain-based IoT forensic investigation process models. Particularly, we systematically review how blockchain is being used to securely improve the forensic investigation process and discuss the efficiency of these proposed models. Finally, the paper highlights challenges, open issues, and future research directions of blockchain technology in the field of IoT forensic investigations

COV-ECGNET: COVID-19 detection using ECG trace images with deep convolutional neural network

The reliable and rapid identification of the COVID-19 has become crucial to prevent the rapid spread of the disease, ease lockdown restrictions and reduce pressure on public health infrastructures. Recently, several methods and techniques have been proposed to detect the SARS-CoV-2 virus using different images and data. However, this is the first study that will explore the possibility of using deep convolutional neural network (CNN) models to detect COVID-19 from electrocardiogram (ECG) trace images. In this work, COVID-19 and other cardiovascular diseases (CVDs) were detected using deep-learning techniques. A public dataset of ECG images consisting of 1937 images from five distinct categories, such as normal, COVID-19, myocardial infarction (MI), abnormal heartbeat (AHB), and recovered myocardial infarction (RMI) were used in this study. Six different deep CNN models (ResNet18, ResNet50, ResNet101, InceptionV3, DenseNet201, and MobileNetv2) were used to investigate three different classification schemes: (i) two-class classification (normal vs COVID-19); (ii) three-class classification (normal, COVID-19, and other CVDs), and finally, (iii) five-class classification (normal, COVID-19, MI, AHB, and RMI). For two-class and three-class classification, Densenet201 outperforms other networks with an accuracy of 99.1%, and 97.36%, respectively; while for the five-class classification, InceptionV3 outperforms others with an accuracy of 97.83%. ScoreCAM visualization confirms that the networks are learning from the relevant area of the trace images. Since the proposed method uses ECG trace images which can be captured by smartphones and are readily available facilities in low-resources countries, this study will help in faster computer-aided diagnosis of COVID-19 and other cardiac abnormalities

Resistance to Mucosal Lysozyme Compensates for the Fitness Deficit of Peptidoglycan Modifications by Streptococcus pneumoniae

The abundance of lysozyme on mucosal surfaces suggests that successful colonizers must be able to evade its antimicrobial effects. Lysozyme has a muramidase activity that hydrolyzes bacterial peptidoglycan and a non-muramidase activity attributable to its function as a cationic antimicrobial peptide. Two enzymes (PgdA, a N-acetylglucosamine deacetylase, and Adr, an O-acetyl transferase) that modify different sites on the peptidoglycan of Streptococcus pneumoniae have been implicated in its resistance to lysozyme in vitro. Here we show that the antimicrobial effect of human lysozyme is due to its muramidase activity and that both peptidoglycan modifications are required for full resistance by pneumococci. To examine the contribution of lysozyme and peptidoglycan modifications during colonization of the upper respiratory tract, competition experiments were performed with wild-type and pgdAadr mutant pneumococci in lysozyme M-sufficient (LysM+/+) and -deficient (LysM−/−) mice. The wild-type strain out-competed the double mutant in LysM+/+, but not LysM−/− mice, indicating the importance of resistance to the muramidase activity of lysozyme during mucosal colonization. In contrast, strains containing single mutations in either pgdA or adr prevailed over the wild-type strain in both LysM+/+ and LysM−/− mice. Our findings demonstrate that individual peptidoglycan modifications diminish fitness during colonization. The competitive advantage of wild-type pneumococci in LysM+/+ but not LysM−/− mice suggests that the combination of peptidoglycan modifications reduces overall fitness, but that this is outweighed by the benefits of resistance to the peptidoglycan degrading activity of lysozyme

Lysozyme M deficiency leads to an increased susceptibility to Streptococcus pneumoniae-induced otitis media

<p>Abstract</p> <p>Background</p> <p>Lysozyme is an antimicrobial innate immune molecule degrading peptidoglycan of the bacterial cell wall. Lysozyme shows the ubiquitous expression in wide varieties of species and tissues including the tubotympanum of mammals. We aim to investigate the effects of lysozyme depletion on pneumococcal clearance from the middle ear cavity.</p> <p>Methods</p> <p>Immunohistochemistry was performed to localize lysozyme in the Eustachian tube. Lysozyme expression was compared between the wild type and the lysozyme M^-/-mice using real time quantitative RT-PCR and western blotting. Muramidase activity and bactericidal activity of lysozyme was measured using a lysoplate radial diffusion assay and a liquid broth assay, respectively. To determine if depletion of lysozyme M increases a susceptibility to pneumococal otitis media, 50 CFU of <it>S. pneumoniae </it>6B were transtympanically inoculated to the middle ear and viable bacteria were counted at day 3 and 7 with clinical grading of middle ear inflammation.</p> <p>Results</p> <p>Immunolabeling revealed that localization of lysozyme M and lysozyme P is specific to some/particular cell types of the Eustachian tube. Lysozyme P of lysozyme M^-/-mice was mainly expressed in the submucosal gland but not in the tubal epithelium. Although lysozyme M^-/-mice showed compensatory up-regulation of lysozyme P, lysozyme M depletion resulted in a decrease in both muramidase and antimicrobial activities. Deficiency in lysozyme M led to an increased susceptibility to middle ear infection with <it>S. pneumoniae </it>6B and resulted in severe middle ear inflammation, compared to wild type mice.</p> <p>Conclusion</p> <p>The results suggest that lysozyme M plays an important role in protecting the middle ear from invading pathogens, particularly in the early phase. We suggest a possibility of the exogenous lysozyme as an adjuvant therapeutic agent for otitis media, but further studies are necessary.</p

Innate Immune Responses of Pulmonary Epithelial Cells to Burkholderia pseudomallei Infection

10.1371/journal.pone.0007308PLoS ONE410

Antimicrobial proteins and polypeptides in pulmonary innate defence

Inspired air contains a myriad of potential pathogens, pollutants and inflammatory stimuli. In the normal lung, these pathogens are rarely problematic. This is because the epithelial lining fluid in the lung is rich in many innate immunity proteins and peptides that provide a powerful anti-microbial screen. These defensive proteins have anti-bacterial, anti- viral and in some cases, even anti-fungal properties. Their antimicrobial effects are as diverse as inhibition of biofilm formation and prevention of viral replication. The innate immunity proteins and peptides also play key immunomodulatory roles. They are involved in many key processes such as opsonisation facilitating phagocytosis of bacteria and viruses by macrophages and monocytes. They act as important mediators in inflammatory pathways and are capable of binding bacterial endotoxins and CPG motifs. They can also influence expression of adhesion molecules as well as acting as powerful anti-oxidants and anti-proteases. Exciting new antimicrobial and immunomodulatory functions are being elucidated for existing proteins that were previously thought to be of lesser importance. The potential therapeutic applications of these proteins and peptides in combating infection and preventing inflammation are the subject of ongoing research that holds much promise for the future