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Cybersecurity refers to the preventative techniques used to protect the integrity of networks, programs and data from attack, damage, or unauthorized access.
Why Cybersecurity Is Required?
At its core, cybersecurity involves protecting information and systems from cyberthreats. Cyberthreats take many forms, such as application attacks, malware, ransomware, phishing and exploit kits. Recent technological advancements have opened up new possibilities for cybersecurity, but unfortunately, adversaries have benefited from these advancements, as well. Taking advantage of automation, attackers can deploy large-scale attacks at significantly reduced costs. Further, the cybercrime economy makes sophisticated attacks easy to deploy and available to a wide variety of motivated adversaries. Cybersecurity tools and technologies should incorporate automation, machine learning and shared threat intelligence to help organizations get ahead and stay on the cutting edge to combat advanced threats, such as:
DNS tunneling: Domain Name System is a protocol that translates human-friendly URLs into machine-friendly IP addresses. Cybercriminals know that DNS is widely used, trusted and often unmonitored. DNS tunneling exploits the protocol to transfer malware and other data through a client-server model.
Ransomware: Ransomware is the focus of a criminal business model that installs malicious software on a device and holds valuable files, data, or information ransom. With its low barrier to entry and high revenue potential, ransomware is the largest threat facing organizations today.
How to Maintain Effective Cybersecurity？
Historically, organizations and governments have taken a reactive, point product approach to fighting cyberthreats, cobbling together individual security technologies to protect their networks and data. However, this method is expensive as well as complex, and stories of devastating breaches continue to dominate headlines, indicating this approach is ineffective.
Enabling automation, machine learning and shared threat intelligence in their security architecture will help organizations keep pace with the growth of sophisticated cyberattacks. Machine learning can help accurately identify variations of known threats, recognize patterns, predict the next steps of an attack, and inform automation tools to create and implement protections across the organization, all in near-real time. With shared threat intelligence, anything one user sees, identifies or prevents benefits all other members of the shared community. More comprehensive prevention, attainable more quickly, reduces overall cybersecurity risk to something easier to manage.
Organizations should consider a natively integrated, automated security platform specifically designed to provide consistent, prevention-based protection for endpoints, data centers, networks, public and private clouds, and software-as-a-service environments.