Archive for the ‘privacy’ category: Page 5

Dec 17, 2022

An AI-based platform to enhance and personalize e-learning

Posted by in categories: privacy, robotics/AI

Researchers at Universidad Autónoma de Madrid have recently created an innovative, AI-powered platform that could enhance remote learning, allowing educators to securely monitor students and verify that they are attending compulsory online classes or exams.

An initial prototype of this platform, called Demo-edBB, is set to be presented at the AAAI-23 Conference on Artificial Intelligence in February 2022, in Washington, and a version of the paper is available on the arXiv preprint server.

“Our investigation group, the BiDA-Lab at Universidad Autónoma de Madrid, has substantial experience with biometric signals and systems, behavior analysis and AI applications, with over 300 hundred published papers in last two decades,” Roberto Daza Garcia, one of the researchers who carried out the study, told TechXplore.

Dec 5, 2022

Scientists create AI neural net that can unlock digital fingerprint-secured devices

Posted by in categories: information science, mobile phones, privacy, robotics/AI, security

Computer scientists at New York University and Michigan State University have trained an artificial neural network to create fake digital fingerprints that can bypass locks on cell phones. The fakes are called “DeepMasterPrints”, and they present a significant security flaw for any device relying on this type of biometric data authentication. After exploiting the weaknesses inherent in the ergonomic needs of cellular devices, DeepMasterPrints were able to imitate over 70% of the fingerprints in a testing database.

An artificial neural network is a type of artificial intelligence comprising computer algorithms modeled after the human brain’s ability to recognize patterns. The DeepMasterPrints system was trained to analyze sets of fingerprint images and generate a new image based on the features that occurred most frequently. This “skeleton key” could then be used to exploit the way cell phones authenticate user fingerprints.

In cell phones, the necessarily small size of fingerprint readers creates a weakness in the way they verify a print. In general, phone sensors only capture a partial image of a print when a user is attempting to unlock the device, and that piece is then compared to the phone’s authorized print image database. Since a partial print means there are fewer characteristics to distinguish it than a full print, a DeepMasterPrint needs to match fewer features to imitate a fingerprint. It’s worth noting that the concept of exploiting this flaw is not unique to this particular study; however, generating unique images rather than using actual or synthesized images is a new development.

Nov 29, 2022

Whole Foods shoppers can now pay with palm scans

Posted by in categories: food, mobile phones, privacy

Amazon is bringing its palm print-scanning biometric payment technology to several Whole Foods locations.

Biometrics: Every person has measurable physical characteristics that are unique to them — and because these attributes are unique and measurable, they can be used to verify our identity.

Biometric technologies — like the one that probably unlocks your phone — automate this verification, analyzing a face, fingerprint, or palm for distinct identifiers linked to a specific person.

Nov 10, 2022

AI Researchers At Mayo Clinic Introduce A Machine Learning-Based Method For Leveraging Diffusion Models To Construct A Multitask Brain Tumor Inpainting Algorithm

Posted by in categories: biotech/medical, information science, privacy, robotics/AI

The number of AI and, in particular, machine learning (ML) publications related to medical imaging has increased dramatically in recent years. A current PubMed search using the Mesh keywords “artificial intelligence” and “radiology” yielded 5,369 papers in 2021, more than five times the results found in 2011. ML models are constantly being developed to improve healthcare efficiency and outcomes, from classification to semantic segmentation, object detection, and image generation. Numerous published reports in diagnostic radiology, for example, indicate that ML models have the capability to perform as good as or even better than medical experts in specific tasks, such as anomaly detection and pathology screening.

It is thus undeniable that, when used correctly, AI can assist radiologists and drastically reduce their labor. Despite the growing interest in developing ML models for medical imaging, significant challenges can limit such models’ practical applications or even predispose them to substantial bias. Data scarcity and data imbalance are two of these challenges. On the one hand, medical imaging datasets are frequently much more minor than natural photograph datasets such as ImageNet, and pooling institutional datasets or making them public may be impossible due to patient privacy concerns. On the other hand, even the medical imaging datasets that data scientists have access to could be more balanced.

In other words, the volume of medical imaging data for patients with specific pathologies is significantly lower than for patients with common pathologies or healthy people. Using insufficiently large or imbalanced datasets to train or evaluate a machine learning model may result in systemic biases in model performance. Synthetic image generation is one of the primary strategies to combat data scarcity and data imbalance, in addition to the public release of deidentified medical imaging datasets and the endorsement of strategies such as federated learning, enabling machine learning (ML) model development on multi-institutional datasets without data sharing.

Nov 7, 2022

Quantum Cryptography Is Unbreakable. So Is Human Ingenuity

Posted by in categories: business, computing, encryption, government, internet, mathematics, privacy, quantum physics, security

face_with_colon_three circa 2016.

Two basic types of encryption schemes are used on the internet today. One, known as symmetric-key cryptography, follows the same pattern that people have been using to send secret messages for thousands of years. If Alice wants to send Bob a secret message, they start by getting together somewhere they can’t be overheard and agree on a secret key; later, when they are separated, they can use this key to send messages that Eve the eavesdropper can’t understand even if she overhears them. This is the sort of encryption used when you set up an online account with your neighborhood bank; you and your bank already know private information about each other, and use that information to set up a secret password to protect your messages.

The second scheme is called public-key cryptography, and it was invented only in the 1970s. As the name suggests, these are systems where Alice and Bob agree on their key, or part of it, by exchanging only public information. This is incredibly useful in modern electronic commerce: if you want to send your credit card number safely over the internet to Amazon, for instance, you don’t want to have to drive to their headquarters to have a secret meeting first. Public-key systems rely on the fact that some mathematical processes seem to be easy to do, but difficult to undo. For example, for Alice to take two large whole numbers and multiply them is relatively easy; for Eve to take the result and recover the original numbers seems much harder.

Continue reading “Quantum Cryptography Is Unbreakable. So Is Human Ingenuity” »

Oct 24, 2022

The Future of Voice Assistants

Posted by in categories: privacy, robotics/AI

Latest breakthroughs in AI, voice biometrics, and speech recognition are paving the way to the exciting future of intuitive voice interaction with smart technologies!

Oct 5, 2022

FBI, CISA, and NSA Reveal How Hackers Targeted a Defense Industrial Base Organization

Posted by in category: privacy

FBI, CISA and NSA have disclosed information on how multiple nation-state hacker groups targeted the network of a Defense Industrial Base.

Sep 26, 2022

New report offers blueprint for regulation of facial recognition technology

Posted by in categories: law, privacy, robotics/AI, surveillance

A new report from the University of Technology Sydney (UTS) Human Technology Institute outlines a model law for facial recognition technology to protect against harmful use of this technology, but also foster innovation for public benefit.

Australian law was not drafted with widespread use of facial recognition in mind. Led by UTS Industry Professors Edward Santow and Nicholas Davis, the report recommends reform to modernize Australian law, especially to address threats to and other human rights.

Facial recognition and other remote biometric technologies have grown exponentially in recent years, raising concerns about the privacy, mass and unfairness experienced, especially by people of color and women, when the technology makes mistakes.

Sep 25, 2022

Brain-Computer Interfaces Could Raise Privacy Concerns

Posted by in categories: computing, neuroscience, privacy

Brain-computer interfaces may have a profound effect on people with limited mobility or other disabilities, but experts say they also introduce privacy issues that must be mitigated.

Aug 24, 2022

Algorithms can prevent online abuse

Posted by in categories: finance, information science, privacy, robotics/AI

Millions of children log into chat rooms every day to talk with other children. One of these “children” could well be a man pretending to be a 12-year-old girl with far more sinister intentions than having a chat about “My Little Pony” episodes.

Inventor and NTNU professor Patrick Bours at AiBA is working to prevent just this type of predatory behavior. AiBA, an AI-digital moderator that Bours helped found, can offer a tool based on behavioral biometrics and algorithms that detect sexual abusers in online chats with children.

And now, as recently reported by Dagens Næringsliv, a national financial newspaper, the company has raised capital of NOK 7.5. million, with investors including Firda and Wiski Capital, two Norwegian-based firms.

Page 5 of 30First23456789Last