By Yashin Manraj, CEO — Pvotal Technologies
As emerging technologies like artificial intelligence continue entering the mainstream, new security challenges inevitably arise. That said, it’s also not uncommon for industry leaders to collaborate in search of solutions to those problems.
The blockchain and cryptocurrency industries, for example, have a number of associations that bring together industry experts to contribute to healthy growth, seeking to strengthen the industry as a whole by developing solutions that benefit every company.
The AI industry could benefit from such collaboration aimed at addressing emerging security concerns. However, there are several hurdles standing in the way of that type of collaboration.
AI security concerns
Data security is one of the top concerns for the AI industry. Training AI models requires gathering, storing, and safeguarding vast amounts of data, which frequently includes sensitive information, thus making that data a high-priority target for hackers.
While data security is not a new challenge, key characteristics of the AI industry introduce new factors that make it even more difficult to address, not the least of which is the volume of data used for AI training. The dynamic nature of AI systems, which require a constant flow of new data, also adds to security difficulties.
The AI industry is also facing a number of new attack vectors that must be understood, analyzed, and addressed. Adversarial attacks, for example, focus on inserting corrupted data into AI models to undermine their accuracy. Adversarial attacks often have subtle signs and impacts, making them particularly difficult to detect and defend against.
Data poisoning attacks are somewhat related to adversarial attacks in that they are unique to AI. Rather than corrupting the model with false data, however, data poisoning seeks to manipulate the data used to train AI models, leading to perpetuated bias in the AI model or negatively affecting its ability to carry out assigned tasks.
Model extraction is another unique attack targeting a company’s proprietary AI models. The attack seeks to reverse-engineer the model by gathering and analyzing a wide range of query outputs. Hackers use this attack to steal intellectual property or misuse the model for their own purposes.
AI security collaboration challenges
Marketplace competition is the key challenge preventing AI companies from collaborating to develop security solutions. Consumers are looking for AI platforms that are relevant, reliable, and secure. A recent survey showed that nearly 90 percent of consumers are worried that AI could negatively impact the security of their identity.
With so many in the marketplace afraid of the impact of ineffective security, companies with solutions have an advantage. The only caveat is that while collaborating to share those solutions with their competitors may improve the overall security of the industry, it eliminates that critical advantage.
Lack of trust is another key issue that often stands in the way of effective collaboration. The AI industry is still in its early stages of development, which means few companies have a history that can testify to their trustworthiness. As a result, those committed to collaboration must take a risk as they begin engaging with other companies to share their expertise and insights.
If collaboration is to become a reality, AI companies must adopt a long-term view of success focused on creating industry-wide security and stability. While it may require giving up a short-term advantage, collaboration can set the stage for ongoing development that creates a larger market and leads to more opportunities.
Collaboration will also require relationship building. As ongoing interactions lead to higher levels of trust, AI companies can begin to come together and foster the synergy needed to develop effective security solutions.
About the Author
Yashin Manraj, CEO of Pvotal Technologies, is a former computational chemist in academia turned engineer working on novel challenges at the nanoscale, and a thought leader building more secure systems at the world’s best engineering firms. His deep technical knowledge from product development, design, business insights, and coding provides a unique nexus to identify and solve gaps in the product pipeline. The Pvotal mission is to build sophisticated enterprises with no limits that are built for rapid change, seamless communication, top-notch security, and scalability to infinity. Pvotal’s products and services create Infinite Enterprises that give business leaders total control and peace of mind over their technology systems and their businesses.
