Friday, September 30, 2022

How Artificial Intelligence Helps in Cyber Security in the Era of Digital Transformation

Cyber security threats exploit the vulnerabilities they find in a company. Any loophole due to hardware weakness, compromised procedures, or software are potentially critical vulnerabilities. Some of them get detected after the attack has happened. A resilient and reliable digital transformation is achieved through the foundation of strong cyber security protocols. 

AI actively works behind the scenes to detect and neutralize cyber security threats more effectively. It can analyze large chunks of data and help to detect any vulnerabilities in the business systems. AI provides a wide array of cyber security benefits in the digital transformation era. 

Top cyber security attacks in the US in 2021/2022

Data by Check Point Research shows that cyber-attacks have been increasing by 50% from one year to the next. On a global scale, organizations recorded an average of 925 attacks weekly in 2021. At least 30,000 websites experience cyber-attacks weekly. The total loss due to the data breach in 2021 averages $4.24 million. Data released by ITRC (Identity Theft Resource Center) show the US recorded 1,291 major data breaches. 

The main security risk factors in 2021 were ransomware, undetected security gaps, and third-party vulnerabilities. The external third-party attacks included a high number of attacks from business email compromise (BEC). AI cyber security technologies help organizations combat BEC through the latest machine learning-based anti-BEC technology

The biggest cyber security attacks recorded in 2021/2022 targeted major US companies with a global influence. Top on the least were companies such as:

  • Microsoft: It was attacked in January 2021 and the impact affected 30,000 organizations in the US. The effect extended to 60,000 organizations globally. Microsoft has one of the largest email exchange servers globally, but hackers were able to take advantage of coding errors. 
  • Facebook: Facebook experienced a major cyber-attack in April 2021, leaving 530 million users exposed. The attack was due to a data leak that was not quickly detected. The hackers scrapped users’ profiles. 
  • JBS USA Holdings: JBS USA Holdings is a leading food processor in the US. The company was attacked in May 2021 by a ransomware attack that led to a serious downtime in its meat processing plants. They had to pay an $11 million ransom in bitcoin. One of the ways to protect a business from attacks is outsourcing a business process from established outsourcing organizations. 
  • Civicom: Civicom is based in New York and provides online services such as video conferencing and market analysis. In February 2022, the company faced a major breach that exposed 8 terabytes of sensitive data. It was due to vulnerabilities caused by the wrong cloud storage configuration. 

The role played by AI in preventing cyber security attacks

The cyber security landscape is changing globally, with new types of threats being experienced by organizations. Hackers and scammers today target not only companies but also their clients too. They trick clients into buying goods, thinking they are buying from their preferred supplier. Due to this, organizations must change their approach to fighting cyber security threats. AI has proved to be a highly effective weapon in this war. 

Use of AI in countering cybersecurity threats

Not long ago, countering cyber threats was a lengthy, manual process. Experts would recognize a new threat, analyze its properties and add it to the list of threats. This process proved ineffective as the number of threats increased and evolved. It was necessary to train protection systems to detect new threats and develop counterattack solutions before they happen. 

The AI subfields were critical in achieving this process fast. These included machine learning, planning, NLP, expert systems, and neural networks. These fields play a key role in this cybersecurity paradigm shift. They do not entirely provide all solutions needed, but they are useful in creating automated decision-making processes. They quickly identify strange patterns in the system or changes in data structure and automatically take corrective action. 

The AI algorithms are first taught from real data such as impersonation, application vulnerabilities, cloud vulnerabilities, third-party exposures, and configuration mistakes. Teaching AI these patterns helps it recognize them and take action before attacks happen. Each of its sub-branch plays a unique role in suspicious pattern detection and shielding. A lot of data is required to effectively teach the AI algorithms all cyber security threats, vulnerabilities, and prevention. 

Uses of AI in cybersecurity

AI learns through three main components, namely learning, reasoning, and self-correction. It first acquires new knowledge/skills and then draws logical conclusions based on that knowledge or experience. Its last phase of learning involves developing abilities to identify and correct errors/threats. 

Machine learning and deep learning help AI automatically detect data and classify it. This includes anomaly detection or suspicious network activities. In return, AI acts to reduce security breaches and enhance the overall security structure. It keeps learning from both historical data and new data to improve its effectiveness. As new threats evolve, AI evolves too, and it can accurately make future attack predictions. 

AI is successfully used to detect various forms of data, such as fraud detection, process behaviors analysis, and suspicious behaviors in the systems. It keeps in check websites and domains, ensuring their reputation is highly valued. AI helps detect similar website addresses, emails, applications, social media accounts, and payment solutions. Organizations use the technology to do system security scans, detect vulnerabilities and generate comprehensive reports. 

Advantages of using AI in cybersecurity

AI provides faster detection and response time due to the use of automated processes. It can handle large volumes of data and process it in real time. The technology is always engaged in continuous learning to help it detect new threats. It can effectively identify unknown threats and stop them. Compared to human beings, AI is better at managing threats and vulnerabilities. An organization eliminates duplicate processes common in manual threats and vulnerability management. 

Conclusion

When organizations integrate digital technology in all their departments, it becomes more efficient and productive. On the other hand, the possibility of cyber-attacks increases too. AI allows organizations to detect and neutralize potential threats faster and more effectively. The technology can analyze large volumes of data which reduces the need for highly trained IT specialists. 

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