How AI is Changing the Landscape of IP Protection


In a world driven by digital transformation, Intellectual Property (IP) theft is a significant threat to companies. Today, countries worldwide are trying to achieve leadership in emerging technologies, while facing challenges from strategic competitors who recognise their economic and military benefits. Healthy competition is a necessity, but malicious actors are hurting strategic partnerships and global peace.

The issue of IP theft has practically spurred a massive trade war between two major countries in recent years, causing huge economic repercussions worldwide.

The Hefty Price Tag of IP Theft

Companies that rely on IP to generate value can face substantial losses due to theft. Note that IP not only means proprietary technology, but it can also encompass trade secrets, images, customer data, movies and much more. Today, tangible assets like machinery and real estate comprise just 16% of a company’s value, while IP rights and other intangible assets account for the remaining 84%.

In the US alone, IP theft saw companies lose $225 billion to $600 billion annually. IP theft can cost a company more than money; it can lead to lost customer relationships, increased costs to raise funds, and downward pressure on stock price. Remember the 2011 incident, where China-based company, Sinovel, stole the proprietary wind turbine technology of AMSC, formerly known as American Superconductor Inc? This led to a loss of 700 jobs and more than $1 billion in shareholder equity for AMSC. In the worst case, it can mean losing an entire business line to competitors or counterfeiters.

Companies must take urgent steps to scrutinise partners, suppliers and investors, while strengthening their cybersecurity programmes to ward off IP threats. Artificial Intelligence (AI) can help do just that.

Role of AI in Protecting IP Assets

IP theft is not new, but the increased use of digital technologies and the anonymous nature of the internet have made it harder to protect trade secrets. No longer are these thefts about a disgruntled employee stealing computer disks, prototypes or documents. The pool of IP thieves is huge today. They operate from anywhere, and can include current and former employees, foreign state actors, criminal and recreational hackers, and competitors.

They can steal IP as a primary motive, or it can be an opportunity in the wider scheme of things. If corporate data can be accessed and stolen in bulk, there is an increased risk that IP assets will be included as well.

AI in Data Deception

Manipulating attackers through data deception tools is not a new technique in the cybersecurity world. For instance, specialists can create false servers that contain fake data. Hackers can be tricked into using these assets and reveal their tactics. This is a “honey pot” tactic, effective but not powerful enough. IT workers face the tedious job of monitoring this maze of deception.

AI is automating data deception technologies, taking away a huge percentage of the workload. With machine learning technologies, automated products will continuously devise new methods of deceiving hackers, learning and developing through past experiences. So, if a system faces a threat at any time, it will develop capabilities to manipulate hackers more efficiently in the future.

The latest example of such a system is the one being developed by researchers at Dartmouth College's Department of Computer Science, in the US. The system, WE-FORGE, acts as a canary trap. It uses AI to create fake documents that can protect IP by confusing a hacker when they are enter a system. WE-FORGE creates millions of highly believable versions of the original document, forcing attackers to waste time looking for the right one. These hackers have limited time to accomplish their goals. By the end of their pursuit, they would have lower confidence in whether the document they stole was the original or not. Many of them would give up before stealing at all.

Threat Hunting Through AI

AI can be effective against threats that are yet undiscovered. For exanoke, companies can combine machine learning with static analysis to create viable scenarios of threats, while also formulating countermeasures. AI-based systems can detect and predict attacks that improve detection time too.

Underlying patterns can be revealed by scripts. An AI system can even predict when an attack can occur. So, it will be possible to provide advanced and proactive security remotely. Learning nodes will take proactive action and communicate with other nodes. The entire system learns and evolves to close attack channels at the same time.

Identifying Loopholes in Organisations

Vulnerability management is important for companies to ensure network security and compliance with regulatory requirements. This involves analysing the network for missed updates, incompatibilities and common weaknesses. Then, the detected vulnerabilities are prioritised for remediation. This makes it difficult for external actors to breach your business network./p>

AI improves multiple elements in the task of vulnerability management. For example, determining an exploitable vulnerability in an asset configuration can be more art than science. This process is prone to false positives. AI can reduce the number of false positives in the detection process. In short, it can “detect the misdetections.” As the AI system learns over time, its ability to accurately predict these false detections can improve. For a business owner, this means spending fewer resources on fixing areas that don’t need any interventions.

Every company is working to remediate these vulnerabilities daily, across multiple assets. Cloud-based vulnerability management products provide a huge benefit for data collection. However, this growing data source contradicts conventional vulnerability remediation priorities. Which assets are lower priority? Which assets pose greater risks for organisations’ bottom lines? Which assets are being patched frequently? By applying AI to vulnerability remediation data across companies, it is possible to gain valuable insights based on the collective judgement of thousands of IT experts.

Mediastalker Protects Your IP Assets with AI/ML-Based Technology Tools

Mediastalker uses AI and the vast experience of its security professionals to provide meaningful cybersecurity solutions.

We have a track record of rescuing over 2.1 million stolen media and restoring over 6,000 IP assets. Our expertise spans a wide range of companies, from major film studios to live-event firms. Trust us to understand your business model and suggest the best strategies for network-wide protection.

Choose a package that fits your assets. Contact Mediastalker today.