DARPA prototypes ‘breakthrough’ cyber attack ‘on the hunt’ technology


DARPA and BAE Systems are prototyping a new AI is competent cybersecurity technology to fight new waves of highly sophisticated cyber attacks designed specifically to work around the current best defense.

The program, called Cyber Hunt Scale (CHASE), used the computer, automation, advanced algorithms and a new caliber of the processing of the speed tracking large amounts of data in real-time, allowing the human cyber hunters to search advanced attacks otherwise hidden or buried in massive amounts of incoming data.

DARPA information explains the technology as “adaptive data collection” be able to conduct real-time investigations by sifting through large amounts of information is not “guarded” by human defenders.

“The CHASE program seeks to develop automated tools to detect and characterize novel attack vectors, the collection of appropriate contextual data and the spreading of a protective measure for both within and between enterprises,” DARPA CHASE, Program Manager, Jennifer Roberts said in a written statement.

Works in conjunction with DARPA, BAE Systems, scientist says the potential promise of these advanced techniques is very important, because often there is just not enough storage and memory to check almost 80 percent of human trafficking data notice in large corporate networks.

“Cyber hunting teams are currently massively overloaded and can only look at a small percentage of the data collected with the help of filters. Advanced opponents to take advantage of this,” Sam Hamilton, BAE Systems Chief Scientist, told the Warrior Maven in an interview. “Advanced adversaries understand today is the cyber defense chain very well and are building things to defeat it.”

DARPA’s CHASE Broad Agency Announcement emphasises this challenge and explains that large enterprise networks generate more data than is available for storage.

“…the group of cyber data that are stored in distributed databases is still larger than the analysis capabilities. The research proposed should focus on a dynamic approach to accelerate cyber hunting through extraction of the right data from the right device at the right time,” the DARPA BAA writes.

Hamilton also stated that, in an increasingly stronger opponents are the development of methods of the hide of the attack of “footprints”, or weave them in a stream are not likely to be marked a high priority for cyber defenders.

CHASE makes use of “devil-proof” machine learning developers to explain; the aim of machine learning is the construction of automation, organization, and analysis of new information by identifying patterns, the placing of things in context, and comparing new data against very large historical databases.

As part of the technology, new methods of computer automation will also be used for “the spread of protective measures,” DARPA information and explanations.

The program is currently in the first phase of a three-phase process which aims to have an operational technology to the U.S. military services in about three years, on condition that the technology properly matures.

“CHASE wants to prototype components that enable network owners to configure, sensors,…at the machine speed with the right levels of human oversight,” Roberts writes.

“We use advanced modeling to detect and defeat cyber threats that currently go unnoticed in large enterprise networks,” Hamilton explained.

Cyber defenders usually categorize in high-and low-priority area of data-flow, because they are forced to leave large amounts of traffic, are deemed to be lower priority, not examined. CHASE is built track attack paths usually are not marked as high priority, he said.

“Data are needed to confirm these categories or tracing of their effects are rarely stored long-term for potential forensic investigation as a result of the massive data storage requirements,” Hamilton added.

This beginning of the effort seeks to make use of the principle advantage of AI-enabled machine learning, namely that the computer automation, process an exponentially greater volume of information, while also placing data in the right context. This is done, at least in part, by the use of algorithms to analyze data – at times, in milliseconds.

“Machine learning to dynamically reconfigures sensor deployment, so that you are capturing much more detail that you otherwise would not be able to do,” Hamilton said.

The concept is not only thwart used malware, phishing, and denial-of-service attacks, but also the defeat much more sophisticated, advanced types of attacks.

“An advanced piece of malware can be a program that is designed to hide in the memory of the computer or on a router,” Hamilton explained.

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