Fant\^omas: Understanding Face Anonymization Reversibility

Face images are a rich source of information that can be used to identify individuals and infer private information about them. To mitigate this privacy risk, anonymizations employ transformations on clear images to obfuscate sensitive information, all while retaining some utility. Albeit published with impressive claims, they sometimes are not evaluated with convincing methodology. Reversing anonymized images to resemble their real input -- and even be identified by face recognition approaches -- represents the strongest indicator for flawed anonymization. Some recent results indeed indicate that this is possible for some approaches. It is, however, not well understood, which approaches are reversible, and why. In this paper, we provide an exhaustive investigation in the phenomenon of face anonymization reversibility. Among other things, we find that 11 out of 15 tested face anonymizations are at least partially reversible and highlight how both reconstruction and inversion are the underlying processes that make reversal possible

Privacy-Protecting Techniques for Behavioral Data: A Survey

Our behavior (the way we talk, walk, or think) is unique and can be used as a biometric trait. It also correlates with sensitive attributes like emotions. Hence, techniques to protect individuals privacy against unwanted inferences are required. To consolidate knowledge in this area, we systematically reviewed applicable anonymization techniques. We taxonomize and compare existing solutions regarding privacy goals, conceptual operation, advantages, and limitations. Our analysis shows that some behavioral traits (e.g., voice) have received much attention, while others (e.g., eye-gaze, brainwaves) are mostly neglected. We also find that the evaluation methodology of behavioral anonymization techniques can be further improved

A False Sense of Privacy: Towards a Reliable Evaluation Methodology for the Anonymization of Biometric Data

Biometric data contains distinctive human traits such as facial features or gait patterns. The use of biometric data permits an individuation so exact that the data is utilized effectively in identification and authentication systems. But for this same reason, privacy protections become indispensably necessary. Privacy protection is extensively afforded by the technique of anonymization. Anonymization techniques protect sensitive personal data from biometrics by obfuscating or removing information that allows linking records to the generating individuals, to achieve high levels of anonymity. However, our understanding and possibility to develop effective anonymization relies, in equal parts, on the effectiveness of the methods employed to evaluate anonymization performance. In this paper, we assess the state-of-the-art methods used to evaluate the performance of anonymization techniques for facial images and for gait patterns. We demonstrate that the state-of-the-art evaluation methods have serious and frequent shortcomings. In particular, we find that the underlying assumptions of the state-of-the-art are quite unwarranted. State-of-the-art methods generally assume a difficult recognition scenario and thus a weak adversary. However, that assumption causes state-of-the-art evaluations to grossly overestimate the performance of the anonymization. Therefore, we propose a strong adversary which is aware of the anonymization in place. This adversary model implements an appropriate measure of anonymization performance. We improve the selection process for the evaluation dataset, and we reduce the numbers of identities contained in the dataset while ensuring that these identities remain easily distinguishable from one another. Our novel evaluation methodology surpasses the state-of-the-art because we measure worst-case performance and so deliver a highly reliable evaluation of biometric anonymization techniques

Understanding Person Identification Through Gait

Gait recognition is the process of identifying humans from their bipedal locomotion such as walking or running. As such, gait data is privacy sensitive information and should be anonymized where possible. With the rise of higher quality gait recording techniques, such as depth cameras or motion capture suits, an increasing amount of detailed gait data is captured and processed. Introduction and rise of the Metaverse is but one popular application scenario in which the gait of users is transferred onto digital avatars. As a first step towards developing effective anonymization techniques for high-quality gait data, we study different aspects of movement data to quantify their contribution to gait recognition. We first extract categories of features from the literature on human gait perception and then design experiments for each category to assess how much the information they contain contributes to recognition success. Our results show that gait anonymization will be challenging, as the data is highly redundant and interdependent

Zu Risiken und Anonymisierungen von Verhaltensbiometrie

Die bestehenden Social-Media-Plattformen erweitern sukzessive die Art, Qualität und Quantität der Daten, die sie über ihre Nutzer:innen erheben. Zu bereits früher aufgezeichneten Daten kommen diverse neue Arten hinzu: Hierzu gehören Körperbewegungen, wie die Handgesten, mit denen die Geräte gesteuert werden, die Augenbewegungen, die von vielen Geräten erfasst werden, aber auch Faktoren wie die menschliche Stimme, oder Herzschläge und Gehirnaktivitäten. Neben der simplen Identifizierung von Individuen erlauben diese verhaltensbiometrische Merkmale viele Rückschlüsse über Eigenschaften aufgenommener Personen, wie Alter, Geschlecht, Gesundheitszustand, aber auch die Persönlichkeit. Für die Nutzer:innen ist dabei nur noch sehr schwer zu erkennen, welche Rückschlüsse über wesentliche Informationen möglich sind. Als Gegenmaßnahme gegen diese Privatsphäreeinschnitte haben Nutzer:innen oftmals nur die Wahl, ob eine Anwendung auf einen bestimmten Sensor vollständig zugreifen darf, oder gar nicht; wobei Letzteres oftmals damit verbunden ist, dass die Anwendung nicht mehr wie gewünscht, oder gar nicht mehr funktioniert. Um dieser Diskrepanz zwischen Datenschutz und immer weitreichenderer Datensammlung zu begegnen, bedarf es zunächst Untersuchungen über die in solchen biometrischen Daten enthaltenen Informationen. Zusätzlich werden neuartige Privatsphäre-Einstellungen nötig, in welchen die Nutzer:innen nicht nur wählen können, ob Daten geteilt werden (z.B. von bestimmten Sensoren), sondern auch ob private Eigenschaften durch Anonymisierungstechniken vor dem Teilen entfernt werden sollen

Seeing the forest for the trees: using the Gene Ontology to restructure hierarchical clustering

Motivation: There is a growing interest in improving the cluster analysis of expression data by incorporating into it prior knowledge, such as the Gene Ontology (GO) annotations of genes, in order to improve the biological relevance of the clusters that are subjected to subsequent scrutiny. The structure of the GO is another source of background knowledge that can be exploited through the use of semantic similarity

Temporal and Spatial Expression of Muc1 During Implantation in Sows

Recent evidence points to an important role for Muc1 in embryo implantation. In this study, Real-time PCR and immunohistochemistry were used to study mRNA and protein levels at, and between, the attachment sites of the endometrium of Day 13, 18 and 24 pregnant sows. The results indicate that Muc1 mRNA expression was higher between attachment sites than at attachment sites during implantation and this effect was significant on Day 13 (P < 0.01) and 24 (P < 0.01). Intense Muc1 immunostaining was observed in luminal epithelium and stroma and the staining between attachment sites was stronger than at attachment sites on Days 13 and 18. Collectively, these results suggest the crucial role of Muc1 in successful implantation and embryo survival

Mitochondrial genes are altered in blood early in Alzheimer's disease

Although mitochondrial dysfunction is a consistent feature of Alzheimer's disease in the brain and blood, the molecular mechanisms behind these phenomena are unknown. Here we have replicated our previous findings demonstrating reduced expression of nuclear-encoded oxidative phosphorylation (OXPHOS) subunits and subunits required for the translation of mitochondrial-encoded OXPHOS genes in blood from people with Alzheimer's disease and mild cognitive impairment. Interestingly this was accompanied by increased expression of some mitochondrial-encoded OXPHOS genes, namely those residing closest to the transcription start site of the polycistronic heavy chain mitochondrial transcript (MT-ND1, MT-ND2, MT-ATP6, MT-CO1, MT-CO2, MT-C03) and MT-ND6 transcribed from the light chain. Further we show that mitochondrial DNA copy number was unchanged suggesting no change in steady-state numbers of mitochondria. We suggest that an imbalance in nuclear and mitochondrial genome-encoded OXPHOS transcripts may drive a negative feedback loop reducing mitochondrial translation and compromising OXPHOS efficiency, which is likely to generate damaging reactive oxygen species

Protective Gene Expression Changes Elicited by an Inherited Defect in Photoreceptor Structure

Inherited defects in retinal photoreceptor structure impair visual transduction, disrupt relationship with the retinal pigment epithelium (RPE), and compromise cell viability. A variety of progressive retinal degenerative diseases can result, and knowledge of disease etiology remains incomplete. To investigate pathogenic mechanisms in such instances, we have characterized rod photoreceptor and retinal gene expression changes in response to a defined insult to photoreceptor structure, using the retinal degeneration slow (rds) mouse model. Global gene expression profiling was performed on flow-sorted rds and wild-type rod photoreceptors immediately prior and subsequent to times at which OSs are normally elaborated. Dysregulated genes were identified via microarray hybridization, and selected candidates were validated using quantitative PCR analyses. Both the array and qPCR data revealed that gene expression changes were generally modest and dispersed amongst a variety of known functional networks. Although genes showing major (>5-fold) differential expression were identified in a few instances, nearly all displayed transient temporal profiles, returning to WT levels by postnatal day (P) 21. These observations suggest that major defects in photoreceptor cell structure may induce early homeostatic responses, which function in a protective manner to promote cell viability. We identified a single key gene, Egr1, that was dysregulated in a sustained fashion in rds rod photoreceptors and retina. Egr1 upregulation was associated with microglial activation and migration into the outer retina at times subsequent to the major peak of photoreceptor cell death. Interestingly, this response was accompanied by neurotrophic factor upregulation. We hypothesize that activation of Egr1 and neurotrophic factors may represent a protective immune mechanism which contributes to the characteristically slow retinal degeneration of the rds mouse model

Prediction of Protein Binding Regions in Disordered Proteins

Many disordered proteins function via binding to a structured partner and undergo a disorder-to-order transition. The coupled folding and binding can confer several functional advantages such as the precise control of binding specificity without increased affinity. Additionally, the inherent flexibility allows the binding site to adopt various conformations and to bind to multiple partners. These features explain the prevalence of such binding elements in signaling and regulatory processes. In this work, we report ANCHOR, a method for the prediction of disordered binding regions. ANCHOR relies on the pairwise energy estimation approach that is the basis of IUPred, a previous general disorder prediction method. In order to predict disordered binding regions, we seek to identify segments that are in disordered regions, cannot form enough favorable intrachain interactions to fold on their own, and are likely to gain stabilizing energy by interacting with a globular protein partner. The performance of ANCHOR was found to be largely independent from the amino acid composition and adopted secondary structure. Longer binding sites generally were predicted to be segmented, in agreement with available experimentally characterized examples. Scanning several hundred proteomes showed that the occurrence of disordered binding sites increased with the complexity of the organisms even compared to disordered regions in general. Furthermore, the length distribution of binding sites was different from disordered protein regions in general and was dominated by shorter segments. These results underline the importance of disordered proteins and protein segments in establishing new binding regions. Due to their specific biophysical properties, disordered binding sites generally carry a robust sequence signal, and this signal is efficiently captured by our method. Through its generality, ANCHOR opens new ways to study the essential functional sites of disordered proteins