How Does Artificial Intelligence Reduce the Chance of a Cyber Breach?
In cybersecurity, artificial intelligence puts a smile on the faces of both security analysts and CEOs.
For one, automation requires fewer funds that have to be allocated towards cyber protection.
Also, it makes the work of analysts much more accurate and efficient when identifying and responding to cyber threats.
Today, artificial intelligence is more than helpful — it’s essential. According to Statista, 83% of US companies that have been surveyed agreed that they “would not be able to respond to cyberattacks without AI“.
One area in which AI has been widely used and integral for security is its management — the process that includes scoping the exposure, identifying critical risks, and mitigating threats or fixing flaws early.
Here, we take a closer look at AI-powered threat exposure management to show how it uses artificial intelligence to remediate and prevent problems.
Repeating Five Steps at All Times
Artificial intelligence allows the repetition (automation) of important steps that improve security. When it comes to threat exposure management, these actions are on a loop at all times:
- Mapping of the external and internal attack surfaces — all the internet-facing and internal software as well as leaked corporate intelligence
- Determining which assets are exposed — the infrastructure is searched for possible errors in configuration and other weaknesses that can allow the hacker into the network
- Prioritization of critical risks — highlighting the issues that are most likely to cause major incidents such as ransomware, successful phishing, or data breaches
- Evaluation of security tools — testing of the protective technology and people with simulated attacks to predict if they are ready for potential hacking attempts
- Taking action to improve security — using the data to strengthen the weak parts of cyber protection within the business
Automatically repeating this cycle of identifying the issues in the context of a specific business, testing layers of security and people involved with it, and remediation of possible threats is essential for thorough management.
AI enables teams to automate parts of security management (such as the testing component) as they see fit for the company. This frees up their schedule and opens up space to dedicate themselves to more complex issues.
Early Discovery of Old and New Threats
In cybersecurity, it’s essential to move fast — strengthen security and react to possible incidents within the infrastructure. If not discovered early, incidents put a major financial strain on companies.
The longer the security team waits, the more time hackers have to do damage within the system without being noticed. Also, the longer it takes the business to recover following the attack.
Threat exposure management cuts the time it takes to uncover the issue within the system and prevents hackers from exploiting weaknesses by locating critical flaws before threat actors do.
As a result, the program aids the teams to reduce the chance of a major cyber threat from both well-known risks and zero-day exploits.
Most previously known threats can be detected and mitigated automatically.
What about the malicious activity for which the company is not ready — such as zero-day attacks?
A threat exposure management program is designed to help cyber analysts to uncover signs of advanced threats. More sophisticated hacking is possible when bypassing security and requires teams to mitigate them manually.
Even more, this technology is connected to the MITRE ATT&CK Framework — a resource for cyber experts and companies who want to strengthen their security. The Framework depicts all of the latest hacking exploits that have endangered other organizations.
Threat exposure management uses it to test the security against new cybercriminal methods and cue the analysts in case of existing vulnerabilities.
Prioritization of Critical Risks
Security analysts can manage attack surfaces promptly if they have all the right data that aids them in making informed decisions.
For instance, threat exposure management utilizes AI to generate a report of the high-risk dangers that could affect the company.
It takes into consideration the map of all the assets and software that the company uses and a growing list of the old and new attacks that might threaten the infrastructure.
Teams that are overworked and lack staff have to manage their time wisely.
That is, they have to know which flaws are likely to compromise the system and dedicate their time to fixing them instead of focusing on low-impact issues that can wait for another round of patching up schedules.
Considering the Context of a Business
The same threat can significantly damage the finances of one business and not represent a high-risk problem for another.
It depends which assets and what part of the architecture is impacted by the hacker.
Threat exposure management scours the web to uncover leaked credentials that hackers can steal and get unauthorized access to the network.
Also, in the case of detected criminal activity within the system, it considers which critical data might be compromised as part of the cyber attack.
AI is used to connect the dots between the mapped assets and software and the newly logged types of threats that businesses have to keep an eye on.
The exact context of the business and the position of the data within the structure is everything— and it’s also something that hasn’t been considered before, with other AI-based tools.
AI Is the Key to Management in Security
Teams don’t have the time and resources to manually write reports and chase threats. Using AI is the standard considering the highest number of threats than ever before and the daily development of more and more sophisticated hacking methods.
Nowadays, there are too many threats and the infrastructure is rapidly changing.
Artificial intelligence gives businesses a fighting chance.
One aspect of security where this is visible the most is in management — which has to be repeated at all times to detect critical risks from one minute to the next.
AI-based technology such as threat exposure management shows the full capabilities of automation and continual learning and updates with the purpose of cutting the chances of expensive breaches and other hacking incidents.
In cybersecurity, artificial intelligence puts a smile on the faces of both security analysts and CEOs.
For one, automation requires fewer funds that have to be allocated towards cyber protection.
Also, it makes the work of analysts much more accurate and efficient when identifying and responding to cyber threats.
Today, artificial intelligence is more than helpful — it’s essential. According to Statista, 83% of US companies that have been surveyed agreed that they “would not be able to respond to cyberattacks without AI“.
One area in which AI has been widely used and integral for security is its management — the process that includes scoping the exposure, identifying critical risks, and mitigating threats or fixing flaws early.
Here, we take a closer look at AI-powered threat exposure management to show how it uses artificial intelligence to remediate and prevent problems.
Repeating Five Steps at All Times
Artificial intelligence allows the repetition (automation) of important steps that improve security. When it comes to threat exposure management, these actions are on a loop at all times:
- Mapping of the external and internal attack surfaces — all the internet-facing and internal software as well as leaked corporate intelligence
- Determining which assets are exposed — the infrastructure is searched for possible errors in configuration and other weaknesses that can allow the hacker into the network
- Prioritization of critical risks — highlighting the issues that are most likely to cause major incidents such as ransomware, successful phishing, or data breaches
- Evaluation of security tools — testing of the protective technology and people with simulated attacks to predict if they are ready for potential hacking attempts
- Taking action to improve security — using the data to strengthen the weak parts of cyber protection within the business
Automatically repeating this cycle of identifying the issues in the context of a specific business, testing layers of security and people involved with it, and remediation of possible threats is essential for thorough management.
AI enables teams to automate parts of security management (such as the testing component) as they see fit for the company. This frees up their schedule and opens up space to dedicate themselves to more complex issues.
Early Discovery of Old and New Threats
In cybersecurity, it’s essential to move fast — strengthen security and react to possible incidents within the infrastructure. If not discovered early, incidents put a major financial strain on companies.
The longer the security team waits, the more time hackers have to do damage within the system without being noticed. Also, the longer it takes the business to recover following the attack.
Threat exposure management cuts the time it takes to uncover the issue within the system and prevents hackers from exploiting weaknesses by locating critical flaws before threat actors do.
As a result, the program aids the teams to reduce the chance of a major cyber threat from both well-known risks and zero-day exploits.
Most previously known threats can be detected and mitigated automatically.
What about the malicious activity for which the company is not ready — such as zero-day attacks?
A threat exposure management program is designed to help cyber analysts to uncover signs of advanced threats. More sophisticated hacking is possible when bypassing security and requires teams to mitigate them manually.
Even more, this technology is connected to the MITRE ATT&CK Framework — a resource for cyber experts and companies who want to strengthen their security. The Framework depicts all of the latest hacking exploits that have endangered other organizations.
Threat exposure management uses it to test the security against new cybercriminal methods and cue the analysts in case of existing vulnerabilities.
Prioritization of Critical Risks
Security analysts can manage attack surfaces promptly if they have all the right data that aids them in making informed decisions.
For instance, threat exposure management utilizes AI to generate a report of the high-risk dangers that could affect the company.
It takes into consideration the map of all the assets and software that the company uses and a growing list of the old and new attacks that might threaten the infrastructure.
Teams that are overworked and lack staff have to manage their time wisely.
That is, they have to know which flaws are likely to compromise the system and dedicate their time to fixing them instead of focusing on low-impact issues that can wait for another round of patching up schedules.
Considering the Context of a Business
The same threat can significantly damage the finances of one business and not represent a high-risk problem for another.
It depends which assets and what part of the architecture is impacted by the hacker.
Threat exposure management scours the web to uncover leaked credentials that hackers can steal and get unauthorized access to the network.
Also, in the case of detected criminal activity within the system, it considers which critical data might be compromised as part of the cyber attack.
AI is used to connect the dots between the mapped assets and software and the newly logged types of threats that businesses have to keep an eye on.
The exact context of the business and the position of the data within the structure is everything— and it’s also something that hasn’t been considered before, with other AI-based tools.
AI Is the Key to Management in Security
Teams don’t have the time and resources to manually write reports and chase threats. Using AI is the standard considering the highest number of threats than ever before and the daily development of more and more sophisticated hacking methods.
Nowadays, there are too many threats and the infrastructure is rapidly changing.
Artificial intelligence gives businesses a fighting chance.
One aspect of security where this is visible the most is in management — which has to be repeated at all times to detect critical risks from one minute to the next.
AI-based technology such as threat exposure management shows the full capabilities of automation and continual learning and updates with the purpose of cutting the chances of expensive breaches and other hacking incidents.
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