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Home»Technology»MLSec could be the answer to adversarial AI and machine learning attacks 
Technology

MLSec could be the answer to adversarial AI and machine learning attacks 

October 25, 2022No Comments4 Mins Read
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With analysis exhibiting that non-public funding in AI reached roughly $93.5 billion in 2021, it’s no secret that many organizations are implementing AI and machine studying to enhance their companies, but it surely’s straightforward to miss the safety dangers created by AI adoption. 

Each AI and ML mannequin that a company makes use of could be a potential goal for cyber assaults. Though the excellent news is {that a} rising variety of suppliers are recognizing these fashions as a part of the trendy enterprise assault floor.

One such supplier is HiddenLayer, which at the moment introduced the launch of the HiddenLayerMLSec Platform designed to detect adversarial machine studying assaults. The announcement comes sizzling on the heels of elevating $6 million in seed funding earlier this yr. 

HiddenLayer makes use of a mannequin scanner to research machine studying mannequin occasions in real-time to establish malicious exercise with out straight accessing a company’s ML fashions. 

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AI and ML fashions as a part of the assault floor 

As AI adoption continues to extend, it’s turning into more and more clear that ML fashions themselves are a part of the assault floor. Based on McKinsey, 63% of enterprises cite cybersecurity as an AI threat, essentially the most acknowledged threat related to AI adoption.

These considerations are properly based, notably when vulnerabilities in AI or ML fashions can present cybercriminals with an entry level into an surroundings, as a part of Adversarial Machine Studying (AML) assaults.

One of the infamous examples of this occurred in 2019, after Skylight researchers found a vulnerability in Cylance’s AI-based antivirus product.

In a weblog put up outlining the occasion, “AI based mostly merchandise provide a brand new and distinctive assault floor. Specifically, in case you may actually perceive how a sure mannequin works, and the kind of options it makes use of to achieve a call, you’d have the potential to idiot it persistently, making a common bypass.” 

Consequently, any enterprise that leverages AI should be ready to defend it from risk actors, which Hidden Layer does with automated detection and response capabilities. 

“The one largest concern about persevering with the funding and growth into AI/ML is cybersecurity, per McKinesey’s State of AI Report. The HL MLSec Platform supplies the trade’s first scalable and real-time safety suite and to allow organizations and governments to increase using AI/ML with out threat to their complete safety posture,” stated CEO of HiddenLayer, Christopher Sestito. 

“Additional, each trade has embraced synthetic intelligence in some type of trend, serving to them develop their income or save prices within the trillions of {dollars}. As with all new expertise, it’s vulnerable to cybersecurity assaults,” Sestito stated. 

The distributors addressing adversarial machine studying 

With consciousness over adversarial machine studying assaults rising as AI adoption will increase, there are a selection of distributors trying to scale back the possibility of malicious exploitation of AI and ML fashions. 

One such supplier is Strong Intelligence, which supplies a platform for testing, monitoring and bettering machine studying fashions. The answer can’t solely detect vulnerabilities in machine studying fashions that risk actors can exploit but in addition stress take a look at fashions earlier than deployment. 

Final yr, Strong Intelligence raised $30 million as a part of a Collection B funding spherical. One other competitor is Calypso.ai, which most just lately raised $13 million in funding in 2020, for an AI stress testing answer with risk modeling and mannequin hardening capabilities. 

Nonetheless, Sestito argues that one of many key differentiators between HiddenLayer and different suppliers is that its answer doesn’t require entry to personal knowledge or mannequin IP. 

“There are numerous corporations centered on MLOps to assist operationalize AI, however not on safety. Conventional cybersecurity corporations are centered on legacy threats like malware, spam, phishing, and so forth that assault pc techniques. We’re the primary firm to deal with cybersecurity threats focusing on AI,” Sestito stated.

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