Exposing Manipulated Photos and Videos in Digital Forensics Analysis.

Tampered multimedia content is being increasingly used in a broad range of cybercrime activities. The spread of fake news, misinformation, digital kidnapping, and ransomware-related crimes are amongst the most recurrent crimes in which manipulated digital photos and videos are the perpetrating and disseminating medium. Criminal investigation has been challenged in applying machine learning techniques to automatically distinguish between fake and genuine seized photos and videos. Despite the pertinent need for manual validation, easy-to-use platforms for digital forensics are essential to automate and facilitate the detection of tampered content and to help criminal investigators with their work. This paper presents a machine learning Support Vector Machines (SVM) based method to distinguish between genuine and fake multimedia files, namely digital photos and videos, which may indicate the presence of deepfake content. The method was implemented in Python and integrated as new modules in the widely used digital forensics application Autopsy. The implemented approach extracts a set of simple features resulting from the application of a Discrete Fourier Transform (DFT) to digital photos and video frames. The model was evaluated with a large dataset of classified multimedia files containing both legitimate and fake photos and frames extracted from videos. Regarding deepfake detection in videos, the Celeb-DFv1 dataset was used, featuring 590 original videos collected from YouTube, and covering different subjects. The results obtained with the 5-fold cross-validation outperformed those SVM-based methods documented in the literature, by achieving an average F1-score of 99.53%, 79.55%, and 89.10%, respectively for photos, videos, and a mixture of both types of content. A benchmark with state-of-the-art methods was also done, by comparing the proposed SVM method with deep learning approaches, namely Convolutional Neural Networks (CNN). Despite CNN having outperformed the proposed DFT-SVM compound method, the competitiveness of the results attained by DFT-SVM and the substantially reduced processing time make it appropriate to be implemented and embedded into Autopsy modules, by predicting the level of fakeness calculated for each analyzed multimedia file.

HS.Register - An Audit-Trail Tool to Respond to the General Data Protection Regulation (GDPR).

Introduction The new General Data Protection Regulation (GDPR) compels health care institutions and their software providers to properly document all personal data processing and provide clear evidence that their systems are inline with the GDPR. All applications involved in personal data processing should therefore produce meaningful event logs that can later be used for the effective auditing of complex processes. Aim This paper aims to describe and evaluate HS.Register, a system created to collect and securely manage at scale audit logs and data produced by a large number of systems. Methods HS.Register creates a single audit log by collecting and aggregating all kinds of meaningful event logs and data (e.g. ActiveDirectory, syslog, log4j, web server logs, REST, SOAP and HL7 messages). It also includes specially built dashboards for easy auditing and monitoring of complex processes, crossing different systems in an integrated way, as well as providing tools for helping on the auditing and on the diagnostics of difficult problems, using a simple web application. HS.Register is currently installed at five large Portuguese Hospitals and is composed of the following open-source components: HAproxy, RabbitMQ, Elasticsearch, Logstash and Kibana. Results HS.Register currently collects and analyses an average of 93 million events per week and it is being used to document and audit HL7 communications. Discussion Auditing tools like HS.Register are likely to become mandatory in the near future to allow for traceability and detailed auditing for GDPR compliance.

Temporal anomaly detection: an artificial immune approach based on T cell activation, clonal size regulation and homeostasis.

This paper presents an artificial immune system (AIS) based on Grossman's tunable activation threshold (TAT) for temporal anomaly detection. We describe the generic AIS framework and the TAT model adopted for simulating T Cells behaviour, emphasizing two novel important features: the temporal dynamic adjustment of T Cells clonal size and its associated homeostasis mechanism. We also present some promising results obtained with artificially generated data sets, aiming to test the appropriateness of using TAT in dynamic changing environments, to distinguish new unseen patterns as part of what should be detected as normal or as anomalous. We conclude by discussing results obtained thus far with artificially generated data sets.

Patient empowerment by the means of citizen-managed Electronic Health Records: web 2.0 health digital identity scenarios.

With the advent of more sophisticated and comprehensive healthcare information systems, system builders are becoming more interested in patient interaction and what he can do to help to improve his own health care. Information systems play nowadays a crucial and fundamental role in hospital work-flows, thus providing great opportunities to introduce and improve upon "patient empowerment" processes for the personalization and management of Electronic Health Records (EHRs). In this paper, we present a patient's privacy generic control mechanisms scenarios based on the Extended OpenID (eOID), a user centric digital identity provider previously developed by our group, which leverages a secured OpenID 2.0 infrastructure with the recently released Portuguese Citizen Card (CC) for secure authentication in a distributed health information environment. eOID also takes advantage of Oauth assertion based mechanisms to implement patient controlled secure qualified role based access to his EHR, by third parties.

Access and privacy rights using web security standards to increase patient empowerment.

Electronic Health Record (EHR) systems are becoming more and more sophisticated and include nowadays numerous applications, which are not only accessed by medical professionals, but also by accounting and administrative personnel. This could represent a problem concerning basic rights such as privacy and confidentiality. The principles, guidelines and recommendations compiled by the OECD protection of privacy and trans-border flow of personal data are described and considered within health information system development. Granting access to an EHR should be dependent upon the owner of the record; the patient: he must be entitled to define who is allowed to access his EHRs, besides the access control scheme each health organization may have implemented. In this way, it's not only up to health professionals to decide who have access to what, but the patient himself. Implementing such a policy is walking towards patient empowerment which society should encourage and governments should promote. The paper then introduces a technical solution based on web security standards. This would give patients the ability to monitor and control which entities have access to their personal EHRs, thus empowering them with the knowledge of how much of his medical history is known and by whom. It is necessary to create standard data access protocols, mechanisms and policies to protect the privacy rights and furthermore, to enable patients, to automatically track the movement (flow) of their personal data and information in the context of health information systems. This solution must be functional and, above all, user-friendly and the interface should take in consideration some heuristics of usability in order to provide the user with the best tools. The current official standards on confidentiality and privacy in health care, currently being developed within the EU, are explained, in order to achieve a consensual idea of the guidelines that all member states should follow to transfer such principles into national laws. A perspective is given on the state of the art concerning web security standards, which can be used to easily engineer health information systems complying with the patient empowering goals. In conclusion health systems with the characteristics thus described are technically feasible and should be generally implemented and deployed.