Lifeboat Foundation

AirTag competitor Tile today announced a new Anti-Theft Mode for Tile tracking devices, which is designed to make Tile accessories undetectable by the anti-stalking Scan and Secure feature.

Scan and Secure is a security measure that Tile implemented in order to allow iPhone and Android users to scan for and detect nearby Tile devices to keep them from being used for stalking purposes. Unfortunately, Scan and Secure undermines the anti-theft capabilities of the Tile because a stolen device’s Tile can be located and removed, something also possible with similar security features added for AirTags.

Here is a list of some of the most popular quantum algorithms highlighting the significant impact quantum can have on the classical world:

Shor’s Algorithm

Our entire data security systems are based on the assumption that factoring integers with a thousand or more digits is practically impossible. That was until Peter Shor in 1995 proposed that quantum mechanics allows factorisation to be performed in polynomial time, rather than exponential time achieved using classical algorithms.

Check out all the on-demand sessions from the Intelligent Security Summit here.

Massachusetts-headquartered Dynatrace, which provides an intelligence layer to monitor and optimize application development, performance and security, today announced key updates for its core platform, including a new AutomationEngine that enables teams to streamline monitoring and other activity across a variety of workflows.

Developers, security specialists, operations personnel and even business users can tap into the platform. The company made the announcement at its annual cloud observability conference in Las Vegas.

Security researchers are seeing threat actors switching to a new and open-source command and control (C2) framework known as Havoc as an alternative to paid options such as Cobalt Strike and Brute Ratel.

Among its most interesting capabilities, Havoc is cross-platform and it bypasses Microsoft Defender on up-to-date Windows 11 devices using sleep obfuscation, return address stack spoofing, and indirect syscalls.

Like other exploitation kits, Havoc includes a wide variety of modules allowing pen testers (and hackers) to perform various tasks on exploited devices, including executing commands, managing processes, downloading additional payloads, manipulating Windows tokens, and executing shellcode.

Check out all the on-demand sessions from the Intelligent Security Summit here.

Generative AI has been all the rage in the recent months, but it is typically generic and not specifically focused on the specific needs of any one company.

San Francisco based startup Jasper is aiming to help make generative AI less generic. The company made a series of announcements today at its Gen AI conference.

Check out all the on-demand sessions from the Intelligent Security Summit here.

Self-healing endpoint platform providers are under pressure to create new solutions to help CISOs consolidate tech stacks while improving cyber-resiliency. CISOs see the potential of self-healing platforms to reduce costs, increase visibility and capture real-time data that quantifies how cyber-resilient they are becoming. And reducing costs while increasing cyber-resilience is the risk profile their boards of directors want.

A self-healing endpoint is one that combines self-diagnostics with the adaptive intelligence to identify a suspected or actual breach attempt and take immediate action to stop it. Self-healing endpoints can shut themselves off, complete a re-check of all OS and application versioning, and then reset themselves to an optimized, secure configuration — all autonomously with no human intervention.

Check out all the on-demand sessions from the Intelligent Security Summit here.

Generative AI, which is based on Large Language Models (LLMs) and transformer neural networks, has certainly created a lot of buzz. Unlike hype cycles around new technologies such as the metaverse, crypto and Web3, generative AI tools such as Stable Diffusion and ChatGPT are poised to have tremendous, possibly revolutionary impacts. These tools are already disrupting multiple fields — including the film industry — and are a potential game-changer for enterprise software.

All of this has led Ben Thompson to declare in his Stratechery newsletter to declare generative AI advances as marking “a new epoch in technology.”

Check out all the on-demand sessions from the Intelligent Security Summit here.

Hyperbole aside, we have only scratched the surface of what the new technology may eventually become. ChatGPT has the markings of artificial narrow intelligence (ANI). That is, AI that is designed to perform specific tasks.

SUMMARY Researchers at the George Washington University, together with researchers at the University of California, Los Angeles, and the deep-tech venture startup Optelligence LLC, have developed an optical convolutional neural network accelerator capable of processing large amounts of information, on the order of petabytes, per second. This innovation, which harnesses the massive parallelism of light, heralds a new era of optical signal processing for machine learning with numerous applications, including in self-driving cars, 5G networks, data-centers, biomedical diagnostics, data-security and more.

THE SITUATION Global demand for machine learning hardware is dramatically outpacing current computing power supplies. State-of-the-art electronic hardware, such as graphics processing units and tensor processing unit accelerators, help mitigate this, but are intrinsically challenged by serial data processing that requires iterative data processing and encounters delays from wiring and circuit constraints. Optical alternatives to electronic hardware could help speed up machine learning processes by simplifying the way information is processed in a non-iterative way. However, photonic-based machine learning is typically limited by the number of components that can be placed on photonic integrated circuits, limiting the interconnectivity, while free-space spatial-light-modulators are restricted to slow programming speeds.

THE SOLUTION To achieve a breakthrough in this optical machine learning system, the researchers replaced spatial light modulators with digital mirror-based technology, thus developing a system over 100 times faster. The non-iterative timing of this processor, in combination with rapid programmability and massive parallelization, enables this optical machine learning system to outperform even the top-of-the-line graphics processing units by over one order of magnitude, with room for further optimization beyond the initial prototype.