A few weeks ago, Best Buy revealed its plans to deploy generative AI to transform its customer service function.
Best Buy's initiative is a harbinger of generative AI deployment in enterprise settings, aiming to increase productivity and improve efficiencies.
A PwC survey reported 73% of U.S. companies have adopted AI to some extent within their operations, and a whopping 54 percent of survey respondents have implemented generative AI specifically in various areas of their business.
With the benefits of generative AI come risks, and adversaries are quick to innovate and act.
Already they are starting to deploy attacks on LLM platform providers in the form of prompt scraping and reverse proxy threats.
Enterprise websites are also in the cross-hairs, as adversaries deploy sophisticated generative AI-based scraping attacks.
Below, I share up-to-the-minute, detailed insights on the risks we're observing through our threat research unit, ACTIR, and while working right alongside the most recognizable companies in the world as they trailblaze uses for generative AI and, in lockstep, protection for consumers.
With the advent of generative AI, scraping techniques have become more advanced and accessible.
Generative AI technologies have transformed scraping from a specialized task requiring significant technical know-how into a more straightforward process.
Another emerging threat vector facilitated by generative AI is the use of illegal reverse proxy services to conduct LLM platform abuse.
These services allow attackers to bypass geo-restrictions and conceal their activities, making it challenging for AI platform providers and regulatory authorities to track and mitigate malicious actions.
Abuse using reverse proxy services is a threat vector that is escalating at such an alarming speed that my upcoming blog is completely dedicated to this type of attack.
To combat these sophisticated threats, our Arkose Bot Manager platform deploys a blend of bot detection capabilities along with workflow anomaly and API instrumentation detection features.
By analyzing traffic patterns and anomalies, our cybersecurity teams are able to effectively pinpoint emerging threat vectors and trends.
Our customer's cybersecurity teams are able to use the data to help in developing long-term strategies to not just stop immediate threats, but also dismantle the networks behind these malicious activities.
The emerging role of computer vision technologies in cybersecurity is in just about every discussion we're having with prospective customers.
Here at Arkose Labs, we harness AI to secure AI against cyber attacks, including AI-based threats, that adversaries are using.
We constantly evaluate our suite of challenges against advanced computer vision models including generative AI platforms.
Defending against these threats requires businesses to perform a balancing act: harnessing the power of generative AI while mitigating its vulnerabilities.
Enterprises will be better equipped to protect themselves and their consumers from the growing wave of AI-driven threats before they can make an impact.
This Cyber News was published on securityboulevard.com. Publication date: Wed, 15 May 2024 19:28:08 +0000