5 Ways to Stop Cyberattacks and Digital Threats Using AI

5 Ways to Stop Cyberattacks and Digital Threats Using AI Cybercriminals are admirable in one aspect. They never stop in their efforts to increase the sophistication of their attacks. They infiltrate governments, businesses, and even individuals. They manage to keep cybersecurity players busy looking for ways to stop the threats. There is a great need for lasting solutions to cyberattacks. Yet, innovative technologies like Artificial intelligence (AI) may provide areas of vulnerability. Cybersecurity players fear that AI in the wrong hands can be catastrophic. Yet, such innovations may also provide the solution to cyber-attacks. Table of Content 1. Using Artificial Intelligence to Stop Cyberattacks 1.1. Threat Detection with Machine Learning 1.2. Managing Vulnerabilities with Artificial Intelligence 1.3. Biometric Authentication and Password Protection 1.4. Faster Response and Error-Free Cybersecurity 1.5. Endpoint Security Solutions 2. Final Thoughts Our article will explore 5 ways to stop cyberattacks and digital threats using AI. Using Artificial Intelligence to Stop Cyberattacks Artificial intelligence empowers machines to mimic human intelligence. Such machines can handle human tasks as well as make decisions. You will find the application in almost all industries and even within homes. It has managed to make inroads in sectors like the automobile industry. Others are medicine and even the beauty industry. Unfortunately, some of the beneficiaries include hackers. Social engineering and phishing are becoming major concerns for industry players. Security measures like installing SSL proxies, firewalls, and antivirus may not be effective. Cybercriminals can weaponize artificial intelligence to further sophisticate their attacks. The more advanced artificial intelligence becomes, the greater their vulnerabilities. Read More: Why Data Security Should Be A Top Priority For Businesses? So how can artificial intelligence help in combating cyber-attacks? Threat Detection with Machine Learning The issue of cybersecurity requires proactive and not reactive responses. It provides organizations a better chance at thwarting attacks. It is in such scenarios where machine learning can play a significant role. Correct implementation of artificial intelligence can generate excellent data. Such include new threats, breaches, or even cyber-attack threats. Artificial intelligence technology has the capability of picking up abnormalities within the network. By flagging such issues, the teams can take the necessary preventative steps. Machine learning can find correlations in data sets faster than human analysts. It provides the opportunity to block any behavior that could be malicious. It also allows for reducing the time any activity intruders have in the system. Unfortunately, all these have downsides. Collecting such data and storing them in one central server can make the job so much easier. Once they breach the server, they will have access to the information. Companies must invest in suitable security measures. Such must have more advanced features to deal with cybercriminals. Managing Vulnerabilities with Artificial Intelligence It will be difficult for humans to find all the possible areas of vulnerabilities. Many factors come into play. Imagine combing through websites to find hacker discussion groups. Identifying and getting more information on the hackers would even be more difficult. The increasing sophistication levels make it almost impossible to uncover the patterns. AI takes into consideration such factors to identify areas of vulnerabilities The company can then use such information to come up with relevant security policies. They can also use it to set up countermeasures. It saves on resources and time while ensuring better network security. Some companies Use machine learning to help with traffic management. Such include web application firewalls (WAF). They are effective in identifying threats. Also, the implementation of mitigation strategies against threats is faster. Features like advanced bot management capabilities increase security further. Bot management helps distinguish between machine and human users. It creates a barrier against any attacks on applications by bots. Biometric Authentication and Password Protection Weak passwords are a major concern when it comes to cybersecurity. Hackers find them easy to breach. Many people understand the importance of a strong password. Yet, few invest enough time in coming up with one. A typical fallback is birthdays, anniversaries, or even name combinations. To make it worse, the same password could control many accounts. Biometric authentication has made things a little bit better. And now, the use of AI is making it more effective. One of the forerunners of the technology is the Apple Face ID authentication. It uses neural engines and infrared sensors when processing facial features. It focuses on patterns and correlations from the users' faces. It means that biometric authentication will work all the time. Even with a change in hairstyle or facial hair it still recognizes the user. Faster Response and Error-Free Cybersecurity AI can process tons of data in a very short time. We get higher efficiency and better accuracy with the feedback. It also eliminates errors that may arise out of human fallibilities. AI can handle repetitive and mundane tasks without getting tired or bored. Machine learning (ML) learns behavior and patterns, resulting in faster response times. IBM has rolled out cybersecurity cognitive technologies that use AI. Companies use such to investigate, identify and respond to threats faster. The technology incorporates machine learning, natural language processing, and pattern recognition. Analysts get access to thorough insights from tons of data to uncover areas of concern. Looking to Hire AngularJS Development Company? Contact Now. See here Endpoint Security Solutions It is common to find application and user monitoring as separate technologies. But, the industry is starting to see an integration between the two. Take the example of Cloud technology. Any consolidated security platforms help with better prevention, investigation, and search for threats. Everything happens on a common cloud platform. The use of predictive technology and artificial intelligence is critical. It helps with learning and pattern identification. It becomes easier to know the source of the attacks and how they are evolving. Final Thoughts Artificial intelligence has a huge role to play in regards to cybersecurity. It is true that hackers can weaponize AI. It will increase their levels of sophistication with regard to attacks. The same also applies to cybersecurity industry players. The innovative technology offers great benefits for better online security. The use of data can help with detecting threats and areas of vulnerability. Companies can take appropriate pre-emptive action to deal with such. Other benefits include biometric authentication and endpoint Solutions. With AI, response time is fast and eliminates inaccuracies that may occur due to human error. There is a lot of potential for growth within the cybersecurity and AI field. We can expect high levels of innovation as players look for ways to outdo the hackers.