Clearing your cookies is not enough to protect your privacy online. New research led by Texas A&M University has found that websites are covertly using browser fingerprinting—a method to uniquely identify a web browser—to track people across browser sessions and sites.

Facial morphology is a distinctive biometric marker, offering invaluable insights into personal identity, especially in forensic science. In the context of high-throughput sequencing, the reconstruction of 3D human facial images from DNA is becoming a revolutionary approach for identifying individuals based on unknown biological specimens. Inspired by artificial intelligence techniques in text-to-image synthesis, it proposes Difface, a multi-modality model designed to reconstruct 3D facial images only from DNA. Specifically, Difface first utilizes a transformer and a spiral convolution network to map high-dimensional Single Nucleotide Polymorphisms and 3D facial images to the same low-dimensional features, respectively, while establishing the association between both modalities in the latent features in a contrastive manner; and then incorporates a diffusion model to reconstruct facial structures from the characteristics of SNPs. Applying Difface to the Han Chinese database with 9,674 paired SNP phenotypes and 3D facial images demonstrates excellent performance in DNA-to-3D image alignment and reconstruction and characterizes the individual genomics. Also, including phenotype information in Difface further improves the quality of 3D reconstruction, i.e. Difface can generate 3D facial images of individuals solely from their DNA data, projecting their appearance at various future ages. This work represents pioneer research in de novo generating human facial images from individual genomics information.

(Repost)

This study has introduced Difface, a de novo multi-modality model to reconstruct 3D facial images from DNA with remarkable precision, by a generative diffusion process and a contrastive learning scheme. Through comprehensive analysis and SNP-FACE matching tasks, Difface demonstrated superior performance in generating accurate facial reconstructions from genetic data. In particularly, Difface could generate/predict 3D facial images of individuals solely from their DNA data at various future ages. Notably, the model’s integration of transformer networks with spiral convolution and diffusion networks has set a new benchmark in the fidelity of generated images to their real images, as evidenced by its outstanding accuracy in critical facial landmarks and diverse facial feature reproduction.

Difface’s novel approach, combining advanced neural network architectures, significantly outperforms existing models in genetic-to-phenotypic facial reconstruction. This superiority is attributed to its unique contrastive learning method of aligning high-dimensional SNP data with 3D facial point clouds in a unified low-dimensional feature space, a process further enhanced by adopting diffusion networks for phenotypic characteristic generation. Such advancements contribute to the model’s exceptional precision and ability to capture the subtle genetic variations influencing facial morphology, a feat less pronounced in previous methodologies.

Despite Difface’s demonstrated strengths, there remain directions for improvement. Addressing these limitations will require a focused effort to increase the model’s robustness and adaptability to diverse datasets. Future research should aim to incorporating variables like age and BMI would allow Difface to simulate age-related changes, enabling the generation of facial images at different life stages an application that holds significant potential in both forensic science and medical diagnostics. Similarly, BMI could help the model account for variations in body composition, improving its ability to generate accurate facial reconstructions across a range of body types.

Chinese scientists have developed laser-imaging technology sufficiently powerful to capture face biometric details from more than 60 milesaway.

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Indian court orders blocking of Proton Mail citing AI deepfakes and explicit emails, triggering national privacy concerns.

Validated on patients with Parkinson’s disease, the intelligent keyboard enables early diagnosis via behavioral biometrics.

In an era where data privacy concerns loom large, a new approach in artificial intelligence (AI) could reshape how sensitive information is processed.

Researchers Austin Ebel and Karthik Garimella, Ph.D. students, and Assistant Professor of Electrical and Computer Engineering Brandon Reagen have introduced Orion, a novel framework that brings fully homomorphic encryption (FHE) to deep learning—allowing AI models to practically and efficiently operate directly on encrypted data without needing to decrypt it first.

The implications of this advancement, published on the arXiv preprint server and scheduled to be presented at the 2025 ACM International Conference on Architectural Support for Programming Languages and Operating Systems, are profound.

Hackers exploit CSS in emails to bypass spam filters and track user actions, raising privacy concerns.

The future of warfare starts in your mind. Understand how Neuroscience, Technology/AI and the OODA loop affects your flow. The world is changing, and cognitive warfare is at the forefront. In our latest podcast episode, we sit down with James Giordano, PhD, a Navy veteran and an expert in neurocognitive science, to delve into the world of cognitive warfare.
Stay in the Loop: https://www.aglx.com/newsletter-signup-north-america.
From the impact of emotions on decision-making to the integration of artificial intelligence and human cognition, this episode challenges your perspective on the battlefield. Join us as we explore the ethical implications of genetic modifications, the transformative effects of psychedelics, and the complexities of data usage in the digital age. Get ready to reimagine the relationship between technology, culture, and language. Don’t miss out on this opportunity to gain valuable insights from our thought-provoking conversation with Dr. Giordano. Tune in now to stay ahead of the curve on the evolving landscape of warfare!

00:00 — Understanding the OODA loop: A Neuroscience Perspective.
09:11 — Exploring Fifth Generation Warfare and Liminal Warfare.
16:06 — The Long Game: China’s Strategic Plan.
22:19 — Understanding Cognitive Warfare and Human-Machine Teaming.
25:52 — The Evolution of Human-Machine Teaming.
29:11 — Human Involvement in AI Decision Making.
36:01 — The Ethics of Paternalistic AI Systems.
40:43 — Technology’s Impact on Cognitive Engagement.
45:13 — Exploring Technologies for Human Performance Enhancement.
55:59 — Diving Into Attacking Mode and Ethics.
56:24 — Hacking the Human Genome.
59:37 — Epigenetic Modification and Phenotypic Shift.
1:04:54 — The Psychedelic Revolution.
1:11:18 — Revisiting Alcohol and Caffeine: Benefits and Burdens.
1:19:18 — Impact of Technology on Cognitive Capacity.
1:23:33 — Information Overload and Burdens.
1:27:02 — Ownership and Security of Personal Data.
1:31:56 — Identifying Predispositional Traits.
1:33:49 — Data Manipulation and Biometrics.
1:40:13 — Cultural Impact of Technology.
1:48:55 — The Role of Education in Integrating Science, Technology, Ethics, and Policy.
1:54:30 — Major Threats and Concerns in Today’s World.

Researchers discovered 49,000 misconfigured and exposed Access Management Systems (AMS) across multiple industries and countries, which could compromise privacy and physical security in critical sectors.

Access Management Systems are security systems that control employee access to buildings, facilities, and restricted areas via biometrics, ID cards, or license plates.

Security researchers at Modat conducted a comprehensive investigation in early 2025 and discovered tens of thousands of internet-exposed AMS that were not correctly configured for secure authentication, allowing anyone to access them.