Artificial intelligence (AI) and machine learning (ML) have become fundamental to cybersecurity. Artificial Intelligence has the amazing capacity for use to protect as well as to do harm. In the wrong applications, AI has a tremendous capacity to render security systems useless. Grasping the scope of AI’s capabilities and strengths and how it can help protect information is, therefore, essential for any firm concerned with data security.
While AI performs defensive tasks with software, it can similarly be used for offensive hacking. They would be able to compose emails that have the same tone as the company’s CEO by eavesdropping on vulnerable ports. Hackers may also get into the company’s system and change the code, reversing the positives and negatives for the AI. The problem this poses is the difficulty in labeling data on malware of attacks, making it difficult for machines to learn the pattern. Hackers are sophisticated adversaries and can develop viruses or threats that the AI may not be able to detect.
These tools are particularly useful when the AI is trained with a high volume of data from the relevant industry and used by people who are familiar with both AI and the company’s own software. AI often provides analytics for this software, resulting in higher efficiency and value. Sometimes they are placed as helper apps for already existing security software but can also be partnered with security operations and analytics platform architecture (SOAPA).
Machine learning is most effective when it is given a specific set of tasks rather than a wide array of assignments. An important example of this could be detecting irregularities in data or procedures. If a user usually checks their email in Washington, AI can tell there’s an anomaly if the user checks their email in a faraway state or nation. Through understanding repeated tasks and behaviors, it can establish a baseline and notify users or companies should there be any deviation.
While AI provides defensive measures for software, it can also be used offensively by cybercriminals. They would be able to compose emails that have the same tone as the company’s CEO by eavesdropping on vulnerable ports. Hackers may also get into the company’s system and change the code, reversing the positives and negatives for the AI. The problem this poses is the difficulty in labeling data on malware of attacks, making it difficult for machines to learn the pattern. Hackers are sophisticated adversaries and can develop viruses or threats that the AI might not be able to detect.
To help increase an application or software’s defenses against cyberattacks, AI must fully understand their intended state through the help of highly trained developers that possess a thorough understanding of the company’s software and procedures.
Once the AI understands its “goodware” and malware, it can achieve cyberhygiene and help secure modern IT environments, by constantly improving and maintaining online security. By nature, cybersecurity is an ever-evolving field with newer threats and increasingly complex solutions.
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