Provenance analysis for instagram photos

As a feasible device fingerprint, sensor pattern noise (SPN) has been proven to be effective in the provenance analysis of digital images. However, with the rise of social media, millions of images are being uploaded to and shared through social media sites every day. An image downloaded from social networks may have gone through a series of unknown image manipulations. Consequently, the trustworthiness of SPN has been challenged in the provenance analysis of the images downloaded from social media platforms. In this paper, we intend to investigate the effects of the pre-defined Instagram images filters on the SPN-based image provenance analysis. We identify two groups of filters that affect the SPN in quite different ways, with Group I consisting of the filters that severely attenuate the SPN and Group II consisting of the filters that well preserve the SPN in the images. We further propose a CNN-based classifier to perform filter-oriented image categorization, aiming to exclude the images manipulated by the filters in Group I and thus improve the reliability of the SPN-based provenance analysis. The results on about 20, 000 images and 18 filters are very promising, with an accuracy higher than 96% in differentiating the filters in Group I and Group II

PRNU-based image classification of origin social network with CNN

A huge amount of images are continuously shared on social networks (SNs) daily and, in most of cases, it is very difficult to reliably establish the SN of provenance of an image when it is recovered from a hard disk, a SD card or a smartphone memory. During an investigation, it could be crucial to be able to distinguish images coming directly from a photo-camera with respect to those downloaded from a social network and possibly, in this last circumstance, determining which is the SN among a defined group. It is well known that each SN leaves peculiar traces on each content during the upload-download process; such traces can be exploited to make image classification. In this work, the idea is to use the PRNU, embedded in every acquired images, as the “carrier” of the particular SN traces which diversely modulate the PRNU. We demonstrate, in this paper, that SN-modulated noise residual can be adopted as a feature to detect the social network of origin by means of a trained convolutional neural network (CNN)

Consumer Centric Data Control, Tracking and Transparency - A Position Paper

Personal data related to a user's activities, preferences and services, is considered to be a valuable commodity not only for a wide range of technology-oriented companies like Google, Amazon and Apple but also for more traditional companies like travel/transport, banking, entertainment and marketing industry. This has resulted in more targeted and to a great extend personalised services for individuals -- in most cases at a minimal financial cost to them. The operational reality upon which a user authorises companies to collect his/her personal data to receive, in return, more personalised/targeted/context-aware services and hassle-free activities (for users) is widely deployed. It becomes evident that the security, integrity and accessibility of the collected data are of paramount importance. These characteristics are becoming more entrenched in the era of Internet-of-Things (IoT), autonomous vehicles and seamless travel. In this position paper, we examine the challenges faced by both users and organisations in dealing with the Personal Identifiable Information (PII). Furthermore, we expand on the implications of the General Data Protection Regulation (GDPR) specifically for the management of the PII. Subsequently, we extend the discussion to future technologies, especially the IoT and integrated transport systems for better customer experience -- and their ramification on the data governance and PII management. Finally, we propose a framework that balances user's privacy and data control with an organisation's objective of delivering quality, targeted and efficient services to their customers using the "collected user data". This framework is referred to as "Consumer Oriented Data Control \& Auditability" (CODCA) and defines the technologies that are adapted to privacy concerns and legal/regulation-frameworks.Comment: 10 Pages, 2 Figures, Conferenc

Detection of Overlapping Passive Manipulation Techniques in Image Forensics

With a growing number of images uploaded daily to social media sites, it is essential to understand if an image can be used to trace its origin. Forensic investigations are focusing on analyzing images that are uploaded to social media sites resulting in an emphasis on building and validating tools. There has been a strong focus on understanding active manipulation or tampering techniques and building tools for analysis. However, research on manipulation is often studied in a vacuum, involving only one technique at a time. Additionally, less focus has been placed on passive manipulation, which can occur by simply uploading an image to a social media site. This research plots the path of an image through multiple social media sites and identifies unique markers in the metadata that can be used to track the image. Both Facebook and Twitter were utilized on both phone and web applications to fully understand any differences between direct and secondary uploads. A full metadata analysis was conducted including histogram and size comparisons. This paper presents several differences and unique metadata findings that allow image provenance to be traced to an original image. This includes a review of IPTC, ICC, and EXIF metadata, ICC profile and Color Profile Description, Encoding Processes, Estimated Quality Values as well as compression ratios. A checklist of variables is given to guide future evaluations of image provenance

Tracing images back to their social network of origin: A CNN-based approach

Recovering information about the history of a digital content, such as an image or a video, can be strategic to address an investigation from the early stages. Storage devices, smart-phones and PCs, belonging to a suspect, are usually confiscated as soon as a warrant is issued. Any multimedia content found is analyzed in depth, in order to trace back its provenance and, if possible, its original source. This is particularly important when dealing with social networks, where most of the user-generated photos and videos are uploaded and shared daily. Being able to discern if images are downloaded from a social network or directly captured by a digital camera, can be crucial in leading consecutive investigations. In this paper, we propose a novel method based on convolutional neural networks (CNN) to determine the image provenance, whether it originates from a social network, a messaging application or directly from a photo-camera. By considering only the visual content, the method works irrespective of an eventual manipulation of metadata performed by an attacker. We have tested the proposed technique on three publicly available datasets of images downloaded from seven popular social networks, obtaining state-of-the-art results

De Montréal à la région d’Yverdon-les-Bains, comment les influenceurs nous font voyager

Ce travail consiste à étudier théoriquement, puis plus concrètement, comment la collaboration avec des influenceurs peut être intégrée dans une stratégie de marketing d’une destination touristique. L’objectif final est d’élaborer des recommandations et de proposer un plan d’action à la région d’Yverdon-les-Bains qui souhaite initier une telle démarche. Pour ce faire, j’ai procédé en trois étapes. Dans un premier temps, une recherche minutieuse a été menée dans la littérature et sur internet afin de comprendre comment interagir avec ces nouveaux prescripteurs de tendances dans le domaine du tourisme. Il a ensuite été question d’interroger la ville de Montréal pour recueillir un avis concret sur les bonnes pratiques de la collaboration avec ces leaders d’opinion digitaux. Enfin, sur la base des recherches effectuées et des enseignements livrés par l’expérience de Montréal, des recommandations ont été proposées à la région d’Yverdon-les-Bains dans le but d’intégrer les influenceurs dans sa stratégie de marketing. Si la ville de Montréal est très avancée dans ce domaine et attire un public jeune, Yverdon-les-Bains région, au contraire, mise actuellement son offre touristique sur son patrimoine et attire un public plus âgé. La région possède un bon potentiel pour implanter cette nouvelle méthode de communication. Il sera cependant fondamental qu’elle suive rigoureusement les étapes proposées dans ce travail afin de créer les conditions nécessaires à une collaboration avec des influenceurs. Plus généralement, aucune destination ne devrait négliger l’impact potentiel de ce type de collaboration dans sa stratégie marketing

Unified Model for Data Security -- A Position Paper

One of the most crucial components of modern Information Technology (IT) systems is data. It can be argued that the majority of IT systems are built to collect, store, modify, communicate and use data, enabling different data stakeholders to access and use it to achieve different business objectives. The confidentiality, integrity, availability, audit ability, privacy, and quality of the data is of paramount concern for end-users ranging from ordinary consumers to multi-national companies. Over the course of time, different frameworks have been proposed and deployed to provide data security. Many of these previous paradigms were specific to particular domains such as military or media content providers, while in other cases they were generic to different verticals within an industry. There is a much needed push for a holistic approach to data security instead of the current bespoke approaches. The age of the Internet has witnessed an increased ease of sharing data with or without authorisation. These scenarios have created new challenges for traditional data security. In this paper, we study the evolution of data security from the perspective of past proposed frameworks, and present a novel Unified Model for Data Security (UMDS). The discussed UMDS reduces the friction from several cross-domain challenges, and has the functionality to possibly provide comprehensive data security to data owners and privileged users

Supporting Collaborative Health Tracking in the Hospital: Patients' Perspectives

The hospital setting creates a high-stakes environment where patients' lives depend on accurate tracking of health data. Despite recent work emphasizing the importance of patients' engagement in their own health care, less is known about how patients track their health and care in the hospital. Through interviews and design probes, we investigated hospitalized patients' tracking activity and analyzed our results using the stage-based personal informatics model. We used this model to understand how to support the tracking needs of hospitalized patients at each stage. In this paper, we discuss hospitalized patients' needs for collaboratively tracking their health with their care team. We suggest future extensions of the stage-based model to accommodate collaborative tracking situations, such as hospitals, where data is collected, analyzed, and acted on by multiple people. Our findings uncover new directions for HCI research and highlight ways to support patients in tracking their care and improving patient safety

Reading Mediated Identities: Auto/biographical Agency in the Material Book, Museum Space, Social Media Platforms, and Archives

Ph.D

Searchable Signatures: Context and the Struggle for Recognition

Social networking sites made possible through Web 2.0 allow for unique user-generated tags called “searchable signatures.” These tags move beyond the descriptive and act as means for users to assert online individual and group identities. This paper presents a study of searchable signatures on the Instagram application, demonstrating that these types of tags are valuable not only because they allow for both individuals and groups to engage in what social theorist Axel Honneth calls the “struggle for recognition,” but also because they provide contextual use data and sociohistorical information so important to the understanding of digital objects. Methods for the gathering and display of searchable signatures in digital library environments are also explored