Quantum computers are now a reality, although they are still too rudimentary to factor numbers of more than two digits. But it is only a matter of time until quantum computers threaten Internet encryption.
Nature caught up with Shor to ask him about the impact of his work — and where Internet security is heading.
Nature talks to Peter Shor 25 years after he showed how to make quantum computations feasible — and how they could endanger our data.
Hundreds of American hospitals are being targeted in cyberattacks by the same Russian hackers who American officials and researchers fear could sow mayhem around next week’s election.
The attacks on American hospitals, clinics and medical complexes are intended to take those facilities offline and hold their data hostage in exchange for multimillion-dollar ransom payments, just as coronavirus cases spike across the United States.
“We expect panic,” one hacker involved in the attacks said in Russian during a private exchange on Monday that was captured by Hold Security, a security company that tracks online criminals.
Code-execution bug has severity rating of 9.8 out of 10; little skill needed to exploit.
BOSTON (AP) — Federal agencies warned that cybercriminals are unleashing a wave of data-scrambling extortion attempts against the U.S. healthcare system designed to lock up hospital information systems, which could hurt patient care just as nationwide cases of COVID-19 are spiking.
In a joint alert Wednesday, the FBI and two federal agencies warned that they had “credible information of an increased and imminent cybercrime threat to U.S. hospitals and healthcare providers.” The alert said malicious groups are targeting the sector with attacks that produce “data theft and disruption of healthcare services.”
The cyberattacks involve ransomware, which scrambles data into gibberish that can only be unlocked with software keys provided once targets pay up. Independent security experts say it has already hobbled at least five U.S. hospitals this week, and could potentially impact hundreds more.
Certain cyber-artificial intelligence attacks could pose an existential threat to the US and the West, former US cyber command chief, Maj.-Gen. (ret.) Brett Williams said on Tuesday.
Speaking as part of Cybertech’s virtual conference, Williams said, “artificial intelligence is the real thing. It is already in use by attackers. When they learn how to do deepfakes, I would argue this is potentially an existential threat.”
But what about nuclear? Are we at risk of cyber-induced meltdowns or releases of radiation?
No.
Fortunately, while the Russians may be able to disrupt electricity transmission in general, and electricity generation from many power plants like natural gas and wind farms, they can’t hack into nuclear power plant operations. Nuclear plants are still mostly analog and not connected to the Internet.
‚The innocuous microwave on a shelf in a laboratory at the U.S. Department of Energy’s Pacific Northwest National Laboratory (PNNL) in Richland, Wash., is anything but ordinary.
“Weird,” is how Penny McKenzie, a cybersecurity engineer at the laboratory, describes the device.
The microwave arrived at PNNL with the capability to be controlled through a smart speaker connected to the internet, a connection McKenzie and her colleagues declined when they plugged it into the wall.
Tuomas Sandholm, a computer scientist at Carnegie Mellon University, is not a poker player—or much of a poker fan, in fact—but he is fascinated by the game for much the same reason as the great game theorist John von Neumann before him. Von Neumann, who died in 1957, viewed poker as the perfect model for human decision making, for finding the balance between skill and chance that accompanies our every choice. He saw poker as the ultimate strategic challenge, combining as it does not just the mathematical elements of a game like chess but the uniquely human, psychological angles that are more difficult to model precisely—a view shared years later by Sandholm in his research with artificial intelligence.
“Poker is the main benchmark and challenge program for games of imperfect information,” Sandholm told me on a warm spring afternoon in 2018, when we met in his offices in Pittsburgh. The game, it turns out, has become the gold standard for developing artificial intelligence.
Tall and thin, with wire-frame glasses and neat brow hair framing a friendly face, Sandholm is behind the creation of three computer programs designed to test their mettle against human poker players: Claudico, Libratus, and most recently, Pluribus. (When we met, Libratus was still a toddler and Pluribus didn’t yet exist.) The goal isn’t to solve poker, as such, but to create algorithms whose decision making prowess in poker’s world of imperfect information and stochastic situations—situations that are randomly determined and unable to be predicted—can then be applied to other stochastic realms, like the military, business, government, cybersecurity, even health care.
…BIOS is doing pretty much the same thing as Neuralink — only in many respects better.
Elon Musk’s Neuralink wants to hack the brain – here are the European neurotechnology startups that are doing the same with a lot less funding.
Microsoft, in collaboration with MITRE research organization and a dozen other organizations, including IBM, Nvidia, Airbus, and Bosch, has released the Adversarial ML Threat Matrix, a framework that aims to help cybersecurity experts prepare attacks against artificial intelligence models.
With AI models being deployed in several fields, there is a rise in critical online threats jeopardizing their safety and integrity. The Adversarial Machine Learning (ML) Threat Matrix attempts to assemble various techniques employed by malicious adversaries in destabilizing AI systems.
AI models perform several tasks, including identifying objects in images by analyzing the information they ingest for specific common patterns. The researchers have developed malicious patterns that hackers could introduce into the AI systems to trick these models into making mistakes. An Auburn University team had even managed to fool a Google LLC image recognition model into misclassifying objects in photos by slightly adjusting the objects’ position in each input image.