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Innovation in the Cybersecurity Industry

In the contemporary world, organizations have been subjected to new threats emanating from advancements in technologies. Cybersecurity is essential for safeguarding computer systems and networks in an online space. As new computer crimes continue to emerge, cybersecurity innovation is required to counteract vulnerabilities in the Information Technology (IT) environment (Lezzi et al., 2018). Cyber attacks are getting more complex, and current skills and capabilities do not answer them effectively. This paper explains the role of innovation in the cybersecurity industry, identifies the major developers related to inventions, and also outlines how technology innovations influence risk management in the cyber defense domain.

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Innovation plays a crucial role in cybersecurity because new ways of combating computer crimes are constantly needed. Innovative ideas help experts level the playing field in the fight against cybercrime. The primary areas of cybersecurity innovation are visibility and automation, and as such, organizations should focus on the fundamentals and not ignore the human factor of security (Li et al., 2019). Examples of activities that benefit from innovation are the removal of the redundant network and access privileges, data movement monitoring, and Software running privilege distribution (Mahdavifar & Ghorbani, 2019). In addition, Innovation-driven automation makes it easier to implement changes consistently across the entire network.

Today, a large number of organizations are developing cybersecurity-related inventions. Examples of these firms are Microsoft, International Business Machines (IBM), Cisco Lockheed Martin, and CyberArk Software. Some individuals have contributed greatly to the field’s development. Kevin Mitnick, Joanna Rutkowska, and Tsutomu Shimomura have a monumental impact in the field of computer security (Mahdavifar & Ghorbani, 2019). In essence, research and development will enable the IT domain to continue finding new ways of improving cybersecurity techniques.

Today, there are numerous ways in which technology innovations can shape risk management in the cybersecurity space. First, real-time visibility has become more available, thereby allowing organizations to uncover threats and develop a response strategy. Also, the component of automation is essential in aiding a corporation to maintain a superior level of security. Moreover, risk management in cybersecurity is influenced by current technologies because of the introduction of securer devices. As such, new strategies for securing data, including facial recognition and fingerprints, are used (Sun et al., 2018). These approaches have minimized risk since information can only be accessed by authorized individuals.

In conclusion, researchers should continue to develop their studies to gain further insights into the emerging threats facing the IT space. Innovation is extremely important for cybersecurity as it provides new ways to fight cybercrime. The major developers of cybersecurity-related inventions, such as Kevin Mitnick, Joanna Rutkowska, and Tsutomu Shimomura, have a great impact in this sphere. At the same time, risk and risk management the cybersecurity are impacted by technology innovations through such tools as real-time visibility, automation, and biometric techniques. Microsoft, Amazon, IBM, Cisco, and other monumental firms have immensely contributed to building cybersecurity techniques. As technology continues to advance, new threats will also keep emerging, which will need to be answered preemptively. Therefore, cybersecurity experts must find new ways of addressing such threats.

References

Lezzi, M., Lazoi, M., & Corallo, A. (2018). Cybersecurity for Industry 4.0 in the current literature: A reference framework. Computers in Industry, 103, 97–110. Web.

Li, L., He, W., Xu, L., Ash, I., Anwar, M., & Yuan, X. (2019). Investigating the impact of cybersecurity policy awareness on employees’ cybersecurity behavior. International Journal of Information Management, 45, 13–24. Web.

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Mahdavifar, S., & Ghorbani, A. A. (2019). Application of deep learning to cybersecurity: A survey. Neurocomputing, 347, 149–176. Web.

Sun, N., Zhang, J., Rimba, P., Gao, S., Zhang, L. Y., & Xiang, Y. (2018). Data-driven cybersecurity incident prediction: A survey. IEEE Communications Surveys & Tutorials, 21(2), 1744–1772. Web.

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