Category: computer

29
Sep
2020
Posted in computer

Locked-up computer systems only part of ‘terrifying’ ransomware scourge



a circuit board


© Provided by The Canadian Press


TORONTO — A shadowy group of cyber criminals that attacked a prominent nursing organization and Canadian Tire store has successfully targeted other companies with clients in governments, health care, insurance and other sectors.

Posts on their NetWalker “blog” indicate the recent infiltration of cloud-services company Accreon and document company Xpertdoc, although only the College of Nurses of Ontario has publicly acknowledged being victimized.

Experts say NetWalker surfaced about a year ago but its attacks took off in March as the criminals exploited fears of COVID and people working remotely. The ransomware, like similar malware, often infiltrates computer networks via phishing emails. Such messages masquerade as genuine, prompting users to provide log-in information or inadvertently download malware.

Earlier ransomware attacks focused on encrypting a target’s files — putting them and even backups out of reach. Increasingly, attackers also threaten to publish data stolen during their “dwell time,” the days or weeks spent inside an exploited network before encryption and detection.

The intruders promise to provide a decryption key and to destroy stolen records if the organization pays a ransom, often based on what the attackers have learned about its finances, by a given deadline.

To underscore the extortion, NetWalker criminals publish tantalizing screen shots of information they have, such as personnel, financial, legal and health records.

“The data in these cases is extremely sensitive,” said Brett Callow, a Vancouver Island-based threat analyst with cyber-security firm, Emsisoft. “Lots of companies choose not to disclose these incidents, so the individuals and (third-party) organizations whose data have been compromised never find out.”

In an interview, Richard Brossoit, CEO of Montreal-based Xpertdoc, said this month’s attack was a “little terrifying” at first. Fortunately, he said, damage was limited and no confidential client or personal information was compromised, although some

29
Sep
2020
Posted in computer

Forgot your Mac’s password? Here’s how to get back into your locked-down computer

Dusting off and powering up an old MacBook only to realize you can’t remember the password is a frustrating experience. Each failed login attempt can cause confusion and even panic. Don’t worry, though. Apple knows that a forgotten password situation is a personal hell that many of us run into, which is why the MacOS software includes built-in features for this exact situation. 

There are a few different tools you can use, and the road you take to unlock your Mac without a password could depend on whether or not you linked your Apple ID to your user account on your Mac during setup. If you didn’t, that’s OK, there’s still another option to reset your account password. Here’s how to get started regaining control over your Mac computer.

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Getting locked out of your Mac is annoying. But don’t get too frustrated. 


Óscar Gutiérrez/CNET

Use your Apple ID to reset your password

Ideally, you’ll have linked your Apple ID to your user account on your Mac during the initial setup, which will make it possible to reset your user password with just a few clicks. 

After entering the wrong user password three times, you’ll be asked if you want to reset the password using your Apple ID, if it’s linked to your account. If you don’t see the message after your third attempt, your account isn’t linked to your Apple ID and you’ll need to use the method outlined below. 

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Using your Apple ID to reset your Mac password is an easy process. 


Jason Cipriani/CNET

Here’s what to do:

Enter your Apple ID email address and password, and follow the rest of the prompts to create a new password. When you change the password, you’ll see a prompt letting you know a new login keychain — what MacOS uses to

29
Sep
2020
Posted in computer

New Brain-Computer Interface Transforms Thoughts to Images

TheDigitalArtist/Pixabay

Source: TheDigitalArtist/Pixabay

Achieving the next level of brain-computer interface (BCI) advancement, researchers at the University of Helsinki used artificial intelligence (AI) to create a system that uses signals from the brain to generate novel images of what the user is thinking and published the results earlier this month in Scientific Reports.

“To the best of our knowledge, this is the first study to use neural activity to adapt a generative computer model and produce new information matching a human operator’s intention,” wrote the Finnish team of researchers.

The brain-computer interface industry holds the promise of innovating future neuroprosthetic medical and health care treatments. Examples of BCI companies led by pioneering entrepreneurs include Bryan Johnson’s Kernel and Elon Musk’s Neuralink.  

Studies to date on brain-computer interfaces have demonstrated the ability to execute mostly limited, pre-established actions such as two-dimensional cursor movement on a computer screen or typing a specific letter of the alphabet. The typical solution uses a computer system to interpret brain-signals linked with stimuli to model mental states. Seeking to create a more flexible, adaptable system, the researchers created an artificial system that can imagine and output what a person is visualizing based on brain signals. The researchers report that their neuroadaptive generative modeling approach is “a new paradigm that may strongly impact experimental psychology and cognitive neuroscience.”

The University of Helsinki researchers used a combination of a generative neural network with neuroadaptive brain interfacing to create a new BCI paradigm. Neuroadaptive generative modeling is the estimation of a person’s intentions via adapting a generative model to neural activity. To expand capabilities and not be limited to pre-defined categories, the researchers based the solution on a generative adversarial network (GAN) to generate novel information from a latent representation of an input space.

Generative adversarial networks are a relatively recent