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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.

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.

Finding practical applications for quantum entanglement is a formidable endeavor to say the least, but a group of Chinese researchers overcame some of the fundamental challenges of open-air quantum teleportation by developing a highly accurate laser pointing and tracking system, as reported by Ars Technica. The team was able to teleport a qubit (a standard unit of data in quantum computing) 97 kilometers across a lake using a small set of photons without fiberoptic cables or other intermediaries.

The laser targeting device developed by Juan Yin and his team was necessary to counteract the minute seismic and atmosphere shifts that would otherwise break the link between the two remote locations. While the use of fiberoptic cables solves the point-to-point accuracy problems faced by open-air systems, using the cables to carry entangled photons — which in turn carry the data needed for quantum teleportation — can cause what’s known as “quantum decoherence,” or rather a corruption in the photon’s entanglement data.

In the grand spectrum of scientific achievement, Yin’s research is a small but crucial stepping stone on the path to a global quantum network, allowing for super-fast data transmission with high levels of encryption to take place. Yin and his team think that quantum repeater satellites could be used to build this network, but until scientists figure out a way to give qubits a few more microseconds of staying power, such a network is probably many years off.

During its ongoing Think 2023 conference, IBM today announced an end-to-end solution to prepare organisations to adopt quantum-safe cryptography. Called Quantum Safe technology, it is a set of tools and capabilities that integrates IBM’s deep security expertise. Quantum-safe cryptography is a technique to identify algorithms that are resistant to attacks by both classical and quantum computers.

Under Quantum Safe technology, IBM is offering three capabilities. First is the Quantum Safe Explorer to locate cryptographic assets, dependencies, and vulnerabilities and aggregate all potential risks in one central location. Next is the Quantum Safe Advisor which allows the creation of a cryptographic inventory to prioritise risks. Lastly, the Quantum Safe Remidiator lets organisations test quantum-safe remediation patterns and deploy quantum-safe solutions.

In addition, the company has also announced IBM Safe Roadmap, which will serve as the guide for industries to adopt quantum technology. IBM Quantum Safe Roadmap is the company’s first blueprint to help companies in dealing with anticipated cryptographic standards and requirements and protect systems from vulnerabilities.

The content of this post is solely the responsibility of the author. AT&T does not adopt or endorse any of the views, positions, or information provided by the author in this article.

Intro

In February 2022, Microsoft disabled VBA macros on documents due to their frequent use as a malware distribution method. This move prompted malware authors to seek out new ways to distribute their payloads, resulting in an increase in the use of other infection vectors, such as password-encrypted zip files and ISO files.

Play ransomware is notable for not only utilizing intermittent encryption to speed up the process, but also for the fact that it’s not operated on a ransomware-as-a-service (RaaS) model. Evidence gathered so far points to Balloonfly carrying out the ransomware attacks as well as developing the malware themselves.

Grixba and VSS Copying Tool are the latest in a long list of proprietary tools such as Exmatter, Exbyte, and PowerShell-based scripts that are used by ransomware actors to establish more control over their operations, while also adding extra layers of complexity to persist in compromised environments and evade detection.

Another technique increasingly adopted by financially-motivated groups is the use of the Go programming language to develop cross-platform malware and resist analysis and reverse engineering efforts.