Today’s topic is how Artificial intelligence plays a role in cybersecurity. New technologies are usually accompanied by positive and negative effects. In the cyber world, continuously evolving technologies bring more risks. New technologies will also provide cyber attackers with more opportunities for cyber attacks. Organizations have developed counter-attack and response strategies, cyber attackers will always be one step ahead in causing damage and sabotaging critical systems.
With the help of advanced smart technologies in network security, organizations can expend resources to protect vulnerable networks and data. This is where artificial intelligence technology comes into play. When used in combination, artificial intelligence can bring additional capabilities, provide immediate insights, predict existing threats, and reduce response time.
Matt Gyde, CEO of NTT’s Security Division, noted: “Automation and artificial intelligence provide scalability to protect today’s growing attack surface. A good example is an interaction between automated detection and mitigation. For example, AppSec monitoring web application firewall, which can provide real-time risk mitigation measures.
According to Capgemini’s survey, 69% of organization executives believe that artificial intelligence is a necessary technology to deal with cyber threats in the context of rapid industrial development. 80% of telecommunications companies hope to use artificial intelligence technology to help identify threats. Besides, research firm Gartner predicts that with a compound annual growth rate of 9.1%, IT risk and management investment will grow to $175 billion in 2023.
- Fill in the gaps in security measures;
- Form a next-generation security team;
- Deploy a safety culture in the organization;
- Automate repetitive tasks;
- Bring humanity and environmental factors to safety;
- Enable 24/7 threat monitoring and reporting.
By accessing faster Internet services (including Wi-Fi and public hotspots), the number of IoT devices has grown exponentially. The infrastructure that supports cloud computing and BYOD reduces the pressure on organizations to build and operate internally deployed IT structures.
IT systems are now digitized and can be used anywhere. This transformation reduces business constraints and isolates consumers, data, and equipment from the boundaries of the organization, resulting in increasing cyber threats. Cyber attackers have been able to exploit insecure systems and compromised user equipment. Also, due to the lack of network security personnel, organizations in various industries face more serious challenges.
- In October 2020, Software AG, the second-largest software developer in Germany, was attacked by the CLOP ransomware. His confidential documents were stolen and demanded a ransom of 23 million US dollars. The company is still restoring its systems and databases to resume operations.
- In October 2020, the Sopra Steria service of Frech IT was also attacked by ransomware. The virus was confirmed as the new Ryuk ransomware, and cybersecurity professionals did not know about ransomware before. Ryuk ransomware also attacked US defense contractor EWA and Spanish logistics company Prosegur.
- In October 2020, Seyfarth Shaw, a global legal service provider headquartered in Chicago, was also attacked by malware. The attack completely paralyzed the company’s email system. As a precaution, the law firm shut down its email system.
- In September 2020, the Messenger application Telegram was hijacked. Hackers use Signaling System 7 to access some messenger and email data in the cryptocurrency business. Their purpose is to obtain cryptocurrency. Also, such attacks are very common in the cryptocurrency community.
- In August 2020, Carnival, the world’s largest cruise operator, detected a ransomware attack that destroyed and encrypted an IT infrastructure of its brand. Cyber attackers stole the confidential information of their customers, employees, and crew.
- In December 2020, SolarWinds, a major US information technology provider, suffered the most serious cyberattack so far. SolarWinds has become the target of cyberattacks. Its attack range has been extended to all its customers, and it has not been discovered for several months. Hackers use this vulnerability to carry out espionage activities against organizations such as the network security provider FireEye, and government agencies including the US Department of Homeland Security and the US Department of the Treasury.
Cybersecurity is very important because many organizations own and operate sensitive information, personally identifiable information (PII), protected health information (PHI), knowledge data, personal information, and industry information systems. Therefore, cybercrime is becoming one of the biggest challenges facing government agencies and enterprises.
According to reports, cybercriminals disclosed information on 2.8 billion users in 2018, valued at more than $654 billion. Also, in the research report on the annual cost of cybercrime released in 2019, the cumulative value at risk of global cybersecurity in the next five years is estimated to be US$5.2 trillion. This survey report describes automation, predictive analysis, and security intelligence in response to the increasing costs of detecting threats. That’s why Artificial intelligence plays a role in cybersecurity.
Cybersecurity experts have thought artificial intelligence has the industry’s potential, how to overcome its challenges.? In addition to being a viable solution, artificial intelligence can also become a huge challenge for organizations. Artificial intelligence is very useful in checking user habits, inferring trends, and identifying various network irregularities or interruptions. With this information, it is easier to find network weaknesses.
Matt Gyde, CEO of NTT’s Security Department, said, “There are already examples of successful use of artificial intelligence for malicious activities. We may see this situation as consistent with the development speed of artificial intelligence. Just as we can apply artificial intelligence to Like detecting malicious activities, cyber attackers can also use artificial intelligence to find weak links and avoid detection.”
In addition to the downside, artificial intelligence will also minimize daily security responsibilities through quality results. Artificial intelligence automation will detect and resolve repetitive incidents.
Artificial intelligence and machine learning are playing an increasingly important role in cybersecurity. It can help identify cyber-attacks, identify trends, and reduce response time. When evaluating large-scale data, the use of artificial intelligence in cybersecurity can improve results, speed up response times, and improve the performance of defense teams that often lack resources.
Artificial intelligence collects, stores, evaluates and processes large amounts of structured and unstructured data. Deploying technologies such as machine learning and deep learning, artificial intelligence can continuously develop and enhance its awareness of cybersecurity challenges and cyber risks. A good example is an artificial intelligence marking mode, which can detect cyber threats in real-time. This more insightful detection will pave the way for machine learning. Therefore, the organization will have an AI-driven system to continuously learn, adapt and improve.
Deepak Patel, director of cybersecurity technology at PerimeterX, said: “Users create an astonishing amount of data each year, and novel algorithms are necessary to differentiate user behaviors to solve new use cases. Website owners need a new defensive machine learning drive. The method, complex behavior modeling, and continuous real-time feedback loop to achieve this goal.
Artificial intelligence plays a role in cybersecurity in business to improve the security infrastructure of organizations. In real-life situations, artificial intelligence technology can greatly enhance network security. For example, biometric login is used to protect input by scanning fingerprints, retinas, or palm prints. Artificial intelligence technologies such as facial recognition software can protect personal information security.
Artificial intelligence also plays a key role in ensuring the expansion of consumer interaction in social networks. Some industry-leading artificial intelligence software companies are looking for new ways of artificial intelligence engineering and its realization to take advantage of the power of technology.
* Google’s Gmail uses machine learning technology to block about 100 million spam messages every day. It establishes a framework for filtering emails and effectively cleans up spam. Google also uses deep learning artificial intelligence on Cloud Video Intelligence. The video saved by the server will be tested according to the quality and meaning, and the artificial intelligence algorithm will submit a warning when an abnormal situation is detected.
- IBM’s Watson Cognitive Training uses machine learning to identify cyber-attacks.
- Balbix uses artificial intelligence-based risk prediction to protect IT networks from data leakage and destruction.
- Darktrace focuses on machine learning to build its cybersecurity products.
- Ipreo, a financial technology provider, uses the corporate security system to detect risks through a global network.
The product uses unsupervised machine learning and artificial intelligence to track users and devices and uses workflows to understand operations in the modern world, thereby ensuring that businesses are protected from ransomware.
The most important thing is to ensure the security of corporate IT resources. Therefore, it is not surprising that network security has become the primary challenge facing organizations. These organizations are hiring artificial intelligence consultants and using top suppliers of machine process automation (RPA) to build advanced technologies to have a solid and in-depth defense mechanism. Gyde emphasized the importance of collaboration. He said: “Network security is closely related to building trust with customers. Therefore, the skills and knowledge of experts need to be carefully adjusted to provide more value to our customers.”
- The coronavirus epidemic has accelerated the organization’s demand for adaptive security, brought opportunities for the development of social engineering techniques, and brought pressure on organizations for business continuity, travel restrictions, and remote work.
- The new and sophisticated TTPS targets business continuity-cyber attackers targeting platforms such as Microsoft Exchange and OWA conduct malicious activities.
- Covered or noisy cyber attacks complicate detection-cyber threat actors often associate existing tools with off-site technology to complicate detection and attribution.
- Ransomware provides material for profitable and scalable businesses-In addition to finding new ways to infect companies with ransomware, cyber attackers are also looking for new ways to get victims to pay.
- Connectivity has consequences-powerful technology and the Internet can achieve greater connectivity and expose critical systems that cyber attackers are looking for new ways to exploit.
- “Anytime, Anywhere” thinking-protect all users, devices, and network traffic consistently with the same effectiveness.
- Transparency-enable users to access the content they need when they need it.
- Stimulate calmness and confidence-use empathy and compassion to make organizational security leaders a catalyst for change to respond more quickly.
- Simplify where possible-consider hosting services and automate where reasonable.
- Enhance resilience-with the support of appropriate resources and investment, make business continuity and crisis management plans suitable for the purpose.
The integration of Artificial intelligence plays a role in cybersecurity will provide additional protection for enterprises. It will enable organizations to prepare for any type of cyber attack, protect and even align with cyber attackers. However, they must also remain vigilant, so as not to allow cyber attackers to use artificial intelligence technology to attack weak links. Using appropriate machine learning and deep learning techniques, organizations can train models to monitor upcoming threats and prevent or mitigate these threats without causing serious damage.