The increase in cybercrime has put the spotlight on data security. Many criminals are turning to AI to perpetrate their crimes, and in order for businesses to protect their data, they’ll have to adopt AI to test and secure networks.
For anyone that’s been monitoring the headlines, it’s clear that cybercriminals are working overtime to gain access to business and consumer data. In fact, according to research conducted by secure payment solutions provider, PCI Pal, almost half (44 percent) of US consumers have suffered the negative consequences of a security breach.
This isn’t surprising when you think about the spike in attacks targeted at high profile companies. In 2018 alone, hackers managed to break into the networks of companies including Under Armour, Adidas, Facebook, Ticketfly and MyHeritage (to name a few), to gain access to data ranging from contact information, passwords, and payment information.
More recently, the travel industry has been a focus, with global airlines, such as British Airways and Cathay Pacific suffering huge valuation losses following hacks which compromised the personal data of millions of consumers.
The same research found that 83 percent of consumers will stop spending on a business for several months following a security breach and 21 percent will never return. As of now, no sign indicates that cybercrime rates will decline, and businesses should prepare themselves for this.
The reputational and financial damage that results from a data breach is reason enough. Additionally, companies are storing more data than ever. Thus, malicious cyber activity will continue to proliferate.
The Double-Edged Sword called AI
Cybercriminals are getting smarter. They’re bypassing organizational defenses at alarming rates and successfully stealing data while remaining undetected. Using new advancements in technology, such as AI, hackers’ tactics are becoming more intelligent and effective.
During the world’s first all-machine cyber hacking tournament in 2016, it was proven possible to fully automate cybersecurity elements, such as exploit generation, attack launch, and patch generation. DARPA’s Cyber Grand Challenge definitively marked the beginning of the era of fully automated cybersecurity.
In response, and in order to combat the growing sophistication of cyberattacks, many organizations are also looking to leverage machine learning (ML) and artificial intelligence (AI) to protect themselves and their users. Businesses are strengthening their security capabilities by using AI-powered tools early and across several stages, including:
- Defensive development posture
- Intrusion detection
- Vulnerability discovery and prioritization
- Exploitation and post-exploitation discovery
In an effort to prevent reputation (and revenue) damaging data breaches or theft, there are four primary ways in which AI can bolster defenses and mitigate vulnerabilities:
1. Applying AI to Development
Applying AI to different layers ensures that companies can defend its applications and networks. For Application Security Testing (AST), AI can be used to address security at the production level. **Security practitioners and developers are able to use AI to automate and create functional test multipliers much faster and more efficiently than what a human could manually do.**
As a result, DevOps and DevSecOps teams are able to develop and deploy secure applications with minimal friction, enabling organizations to scale without putting data at risk. By incorporating AI in the development phase, “fail fast†methodology is controlled, and applications are better prepared to defend against AI enabled hackers.
2. Applying AI to Intrusion Detection
Traditionally, intrusion detection was done by humans monitoring networks for anomalies. However, the growth of network bandwidth and the spike in cyber activity within today’s digital organizations have made this process a time-consuming and resource-intensive task.
Subsequently, security teams are using AI to automatically monitor networks for suspicious activity and indicators of compromise. By analyzing data, AI is able to find correlations in cyber activity that link seemingly unrelated events together that would otherwise go undetected.
3. Applying AI to Vulnerability Discovery and Prioritization
Today, enterprises are collecting data at rapid speeds. This creates an expanding risk surface for criminals to penetrate. Organizations are also dealing with third parties and insider threats, and as a result, vulnerabilities have become so pervasive that identifying them manually has become impossible.
Therefore, it has become more important than ever to find and patch vulnerabilities in applications and networks ahead of hackers, or risk being exploited. Using the appropriate algorithms, security practitioners are able to apply AI to effectively identify vulnerabilities, prioritize the urgency of each, and ultimately prevent an exploit.
4. Fortifying Defenses with AI
The speed and scale of today’s businesses make it difficult for a human to make sense of all the relevant security data effectively and quickly. And with cybercriminals becoming increasingly cunning, organizations must utilize AI-powered tools across security processes to keep up with the evolving security landscape.
By doing so, security teams are empowered to automatically analyze relevant data, protect it across integrations, and enable humans to be more effective. **Ultimately, in this new era of automated cybersecurity, AI will increasingly be able to not just find vulnerabilities open to potential exploitation but also identify which data is most significant in the event of a breach.**
For organizations adopting AI to help test and secure their networks, the result will be ever-greater visibility into the current and potential future threats they face. Businesses slower to adapt will very quickly find themselves too far behind the speed of threat innovation to respond.