Guest Article by Cybernews.com.
Cybercriminals are more sophisticated than ever. While many attempt to breach complex cybersecurity measures, the best VPN services continue to offer a robust line of defense, especially when combined with AI-powered tools.”
It’s a good thing that the increasing sophistication of artificial intelligence (AI) and machine learning (ML) technology has also elevated protection against cyber threats.
Let’s take a look at how AI and ML combat cyber crimes.
But first, how bad is the online security problem?
According to the 2022 Official Cybercrime Report, the cost of cybercrime is expected to reach $8 trillion this year. By 2025, this number is expected to balloon to $10.5 trillion.
The report recommended better security resilience, as it seems there will be no end to cyber threats.
The FBI’s Internet Crime Complaint Center report states that it received 847,376 cybercrime complaints in 2021. Some $6.9 billion was lost from these instances.
It must be noted that the actual number of cyber attacks is much higher—many companies don’t report cyber crimes at all, likely because getting the authorities involved will take precious time from company operations. The incorporation of AI in cybersecurity can help address these challenges and offer several benefits.
Here are some of the most common cyber threats:
Cybercriminals are also leveraging AI and ML technology in their attacks.
According to the European law enforcement agency Europol, cyber criminals adapt emerging technology into their strategies very quickly. It shouldn’t be surprising that they quickly familiarized themselves with AI and now use it in their nefarious activities.
AI has reportedly been used in guessing passwords, breaking CAPTCHA, and cloning human voices to breach cybersecurity measures.
Fortunately, security experts have devised ways to use AI to protect against cyber crimes.
AI has become essential in discovering cyber threats. Machine learning, which is a subset of AI, has automated the process of identifying them.
With sophisticated algorithms, ML can process large amounts of data to not only determine threats but even predict them as well.
So how does AI detect threats?
AI has the ability to distinguish good and bad elements in real-time. It doesn’t just identify threats; it does so quickly too. The human factor or delay is eliminated, which means attacks are easily blocked and threats removed.
Learning from previous incidents helps AI identify threats before they occur. This way, the cybersecurity team can find the best solutions to address the potential problem.
AI’s predictive intelligence also allows for predictive response in case similar threats are detected again.
Some cybersecurity systems are now powered by AI, which means they are providing protection using cutting-edge cybersecurity technology. The implication is that the AI understands the latest global and industry-specific threats by combing through information on the internet. Because of this, the security system is smart enough to detect and even eliminate the most sophisticated threats that are also powered by AI.
By nature, AI becomes smarter as time passes. It will continuously improve its protection and security measures to work against cyber attacks.
Some of the biggest companies in the world use AI to combat cyber threats. Here are some case studies:
Two of the most recognizable brands in the world, IBM and Wimbledon, partnered in 2017 in the name of cognitive security. That year, Wimbledon hosted a digital experience to open the grand slam tournament to a large number of people.
Wimbledon ensured fans had a great experience with the event even if they couldn’t watch the games courtside. Part of the challenge was the increase in the risk of cyber crimes.
AI technologies were leveraged to efficiently identify and analyze threats in many events throughout the tournament.
IBM Watson, the brand’s data analytics processor, completed security threat investigations 60 times faster than manual analysis. Not a single attempted security breach was successful during the event.
Siemens is a 175-year-old German multinational conglomerate. Part of the reason it has sustained such popularity and credibility is that it knows how to adapt to industry changes. Unsurprisingly, it has tapped Amazon Web Services (AWS) for its machine learning needs against cyber threats.
Part of the Siemens charter is to protect its clientele from viruses, malware, intellectual property theft, and other forms of cyber threats. In 2017, the company received around 200,000 malware samples. It was important that not a single breach would threaten the company—an AI-driven security platform was key to that.
AWS Machine Learning evaluates 60,000 threats per second for Siemens, and each forensic analysis does not slow down the system’s performance at all. Only 12 employees manage AI-powered cybersecurity, which is incredibly cost-effective.
Identifying and classifying network traffic data allows organizations to identify security breaches and detect system failures. A Fortune 500 telco complained that it took too long to label data, and it was difficult to recognize changing data distributions.
Moreover, the company had to use multiple tools to cover data processing, from exploration to labeling and analysis.
Using Snorkel Flow, a data-centric AI platform, the telco was able to deliver highly accurate machine learning models to do network data application in an instant. The AI was 77.3% more accurate when put against a rules-based approach and 10% better than the baseline model.
Now that network traffic data classification has been a success, the company is moving on to using AI to identify real-time anomalies over time-series data.
As cyber threats become more sophisticated, so does cybersecurity. Companies must invest in AI-powered cybersecurity and machine learning systems to detect and prevent security breaches that could cost millions of dollars and tarnish their reputations. Customers don’t want to hear that their trusted company cannot contain cyber threats.
With where things are going, it will be a battle of AI technologies. It all depends on an entity’s ability to leverage technology on whether good (security and privacy) triumphs over evil (cyber criminals).