Emerging technologies put cybersecurity at risk. Even the new advancements in defensive strategies of security professionals fail at some point. Besides, as offensive-defensive strategies and innovations are running in a never-ending cycle, the complexity and volume of cyberattacks have increased.

Combining the strength of artificial intelligence (AI) with cybersecurity, security professionals have additional resources to defend vulnerable networks and data from cyber attackers. After applying this technology, it brought instant insights, resulting in reduced response times. Capgemini recently released a report based on AI in cybersecurity, which mentions that 42% of the companies studied had seen a rise in security incidents through time-sensitive applications. It also revealed that two out of three organizations are planning to adopt AI solutions by 2020.

Data security is now more vital than ever. Updating existing cybersecurity solutions and enforcing every possible applicable security layer doesn’t ensure that your data is breach-proof. But, having a strong support of advanced technologies will ease the task of security professionals.

Challenges and Promises of Artificial Intelligence in Cybersecurity

While cybersecurity experts have accepted AI as the future of the industry, finding solutions to its problems are still not adequately addressed. Apart from being a solution, it is a considerable threat to businesses.

AI can efficiently analyze user behaviors, deduce a pattern, and identify all sorts of abnormalities or irregularities in the network. With such data, it’s much easier to identify cyber vulnerabilities quickly. Contrarily, the responsibilities which are now dependent on human intelligence will then be susceptible to malicious cyber programs imitating legitimate AI-based algorithms.

Several organizations are rushing into getting their machine-learning-based products out in the market. With this behavior, they might overlook the algorithms are creating a false sense of security. Relying on “supervised learning” is another threat. Under this, the algorithms label the data sets as per their nature. It could be malware, clean data, or some other tag. Cybercriminals, if they get access to the security firm, can alter the label as per their convenience. Also, routine tasks relying on AI can be manipulated by advanced hacking campaigns through the use of machine learning.

In spite of being a security risk to the businesses, AI will continue to minimize the routine security responsibilities with high-quality results. AI automation will be able to identify recurring incidents and even remediate them. It will also be able to manage insider threats and device management.

Present-Day Cybersecurity and its Future with AI

Today, organizations pay close attention to their network security. They are aware of the massive impact of every small- to large-scale cyber-attack. To secure this infrastructure, organizations use multiple lines of defense. This multi-layered security system usually starts with the best suitable firewall capable of controlling and filtering out the network traffic.

After this layer, the second line of defense consists of antivirus (AV) software. These AV tools scan through the system to find and eliminate malicious codes and files. With these two lines of defense, organizations regularly run backups as a part of a disaster recovery plan.

For now, setting up firewall policies, managing backups, and many such tasks require a professional, but AI will change the traditional approach.

  • Organizations will be able to monitor and respond to security incidents by using advanced tools.
  • The next-generation firewalls will have in-built machine learning technology that could find a pattern in network packets and block them automatically if flagged as a threat.
  • Predictably, the natural language capabilities of AI will be used to understand the origination of cyber-attacks. This theory can be put into practice by scanning data across the internet.

Improved Cybersecurity with AI and Machine Learning (ML)

Complicated hacking techniques, such as obfuscation, polymorphism, and others, make it a real challenge to identify malicious programs. Besides, security engineers with domain-specific workforce shortage is another issue. With AI stepping into cybersecurity, experts and researchers are trying to use its potential to identify and counteract sophisticated cyber-attacks with minimal human intervention. AI networks and machine learning, a subset of AI, has enabled security professionals to learn about new attack vectors.

Machine learning in cybersecurity is much more than a mere application of the algorithms. It can be used to analyze cyber threats better and respond to security incidents. There are a few other significant benefits of machine learning, which includes –

  • Detects malicious activities and stops cyber attacks
  • Analyzes mobile endpoints for cyber threats – Google is already using machine learning for the same
  • Improves human analysis – from malicious attack detection to endpoint protection
  • Uses in automating mundane security tasks
  • No zero-day vulnerabilities

AI Adopters Inspiring to Make a Shift

AI has already been adopted to strengthen the security infrastructure of organizations. There are numerous real-life examples where AI-powered solutions are significantly improving cybersecurity.

Soon, the AI-powered systems will be an integral part of cybersecurity solutions. It will also be used by cybercriminals to harm organizations. This will leave AI using automated programs susceptible to advanced threats. Like any other cybersecurity solution, AI is not 100% foolproof. It is a double-edged sword with the ability to limit cyber-attacks and automate mundane routine tasks, and yet, it’s a blessing. The automation wave will take over everyday tasks while the same technology will increase the chances of fewer human errors and negligence.

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