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Category: encryption – Page 16

The term “virtual private network,” or VPN for short, has become almost synonymous with “online privacy and security.” VPNs function by creating an encrypted tunnel through which your data may transit as it moves over the internet. They are designed to protect your privacy and make it impossible for anyone to monitor or access your activity while you are online. But what happens if the same instrument that was supposed to keep your privacy safe turns out to be a conduit for attacks? Introduce yourself to “TunnelCrack,” a frightening discovery that has sent shockwaves across the world of cybersecurity. Nian Xue from New York University, Yashaswi Malla and Zihang Xia from New York University Abu Dhabi, Christina Popper from New York University, and Mathy Vanhoef from KU Leuven University were the ones that carried out the study.

Two serious vulnerabilities in virtual private networks (VPNs) have been discovered by a research team. These vulnerabilities had been dormant since 1996. It is possible to leak and read user traffic, steal information, or even conduct attacks on user devices by exploiting these vulnerabilities, which are present in practically every VPN product across all platforms. TunnelCrack is a combination of two common security flaws found in virtual private networks (VPNs). Even though a virtual private network (VPN) is designed to safeguard all of the data that a user sends, these attacks are able to circumvent this security. An enemy, for example, may take advantage of the security flaws to steal information from users, read their communications, attack their devices, or even just spill it all. Regardless of the security protocol that is utilized by the VPN, the uncovered flaws may be exploited and used maliciously.

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An interdisciplinary team of mathematicians, engineers, physicists, and medical scientists have uncovered an unexpected link between pure mathematics and genetics, that reveals key insights into the structure of neutral mutations and the evolution of organisms.

Number theory, the study of the properties of positive integers, is perhaps the purest form of mathematics. At first sight, it may seem far too abstract to apply to the natural world. In fact, the influential American number theorist Leonard Dickson wrote ‘Thank God that number theory is unsullied by any application.’

And yet, again and again, number theory finds unexpected applications in science and engineering, from leaf angles that (almost) universally follow the Fibonacci sequence, to modern encryption techniques based on factoring prime numbers. Now, researchers have demonstrated an unexpected link between number theory and evolutionary genetics.

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Through a scattering medium such as ground glass? Traditionally, this would be considered impossible. When light passes through an opaque substance, the information carried within the light becomes “jumbled up”, almost as if undergoes complex encryption.

Recently, a remarkable scientific breakthrough by Professor Choi Wonshik’s team from the IBS Center for Molecular Spectroscopy and Dynamics (IBS CMSD) has unveiled a method to leverage this phenomenon in the fields of optical computing and machine learning.

Machine learning is a subset of artificial intelligence (AI) that deals with the development of algorithms and statistical models that enable computers to learn from data and make predictions or decisions without being explicitly programmed to do so. Machine learning is used to identify patterns in data, classify data into different categories, or make predictions about future events. It can be categorized into three main types of learning: supervised, unsupervised and reinforcement learning.

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An interdisciplinary team of mathematicians, engineers, physicists, and medical scientists has discovered a surprising connection between pure mathematics and genetics. This connection sheds light on the structure of neutral mutations and the evolution of organisms.

Number theory, the study of the properties of positive integers, is perhaps the purest form of mathematics. At first sight, it may seem far too abstract to apply to the natural world. In fact, the influential American number theorist Leonard Dickson wrote “Thank God that number theory is unsullied by any application.”

And yet, again and again, number theory finds unexpected applications in science and engineering, from leaf angles that (almost) universally follow the Fibonacci sequence, to modern encryption techniques based on factoring prime numbers. Now, researchers have demonstrated an unexpected link between number theory and evolutionary genetics.

Read more | >

The Abyss Locker operation is the latest to develop a Linux encryptor to target VMware’s ESXi virtual machines platform in attacks on the enterprise.

As the enterprise shifts from individual servers to virtual machines for better resource management, performance, and disaster recovery, ransomware gangs create encryptors focused on targeting the platform.

With VMware ESXi being one of the most popular virtual machine platforms, almost every ransomware gang has begun to release Linux encryptors to encrypt all virtual servers on a device.

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Various reports say the claim is far from true.

Russian scientists are claiming that they have created the most powerful quantum computer in the history of their nation. They even presented the computer to Russian President Vladimir Putin, who visited the exhibition of quantum technology achievements by Rosatom, the State Nuclear Energy Corporation.

But as per a report, the claim is far from true and the computer won’t be breaking modern encryption codes anytime soon.

Rosatom.

They even presented the computer to Russian President Vladimir Putin, who visited the exhibition of quantum technology achievements by Rosatom, the State Nuclear Energy Corporation.

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Quantum computing holds the potential to tackle complex issues in fields like material science and cryptography, problems that will remain out of reach even for the most powerful conventional supercomputers in the future. However, accomplishing this feat will likely necessitate millions of high-quality qubits, given the error correction needed.

Progress in superconducting processors advances quickly with a current qubit count in the few hundreds. The appeal of this technology lies in its swift computational speed and compatibility with microchip fabrication. However, the requirement for extremely low temperatures places a limit on the processor’s size and prevents any physical access once it is cooled down.

A modular quantum computer with multiple separately cooled processor nodes could solve this. However, single microwave photons—the particles of light that are the native information carriers between superconducting qubits within the processors—are not suitable to be sent through a room temperature environment between the processors. The world at room temperature is bustling with heat, which easily disturbs the microwave photons and their fragile quantum properties like entanglement.

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Managing Director of Cyber Security Consulting at Verizon.

It’s no surprise firewalls and encryption are instrumental to help defend against cyberattacks, but those tools can’t defend against one of the largest cybersecurity threats: people.

Social engineering—manipulating individuals to divulge sensitive information—is on the rise, even as organizations increasingly implement cybersecurity education and training. While social engineering already poses a challenge for organizations, AI might make it even more of a threat.

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Basic, or “elementary,” cellular automata like The Game of Life appeal to researchers working in mathematics and computer science theory, but they can have practical applications too. Some of the elementary cellular automata can be used for random number generation, physics simulations, and cryptography. Others are computationally as powerful as conventional computing architectures—at least in principle. In a sense, these task-oriented cellular automata are akin to an ant colony in which the simple actions of individual ants combine to perform larger collective actions, such as digging tunnels, or collecting food and taking it back to the nest. More “advanced” cellular automata, which have more complicated rules (although still based on neighboring cells), can be used for practical computing tasks such as identifying objects in an image.

Marandi explains: “While we are fascinated by the type of complex behaviors that we can simulate with a relatively simple photonic hardware, we are really excited about the potential of more advanced photonic cellular automata for practical computing applications.”

Marandi says cellular automata are well suited to photonic computing for a couple of reasons. Since information processing is happening at an extremely local level (remember in cellular automata, cells interact only with their immediate neighbors), they eliminate the need for much of the hardware that makes photonic computing difficult: the various gates, switches, and devices that are otherwise required for moving and storing light-based information. And the high-bandwidth nature of photonic computing means cellular automata can run incredibly fast. In traditional computing, cellular automata might be designed in a computer language, which is built upon another layer of “machine” language below that, which itself sits atop the binary zeroes and ones that make up digital information.

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