Almost every day, we hear news reports of how hackers obtained access to certain networks, how credit card information from a major company was comprised, or how identity theft is on the rise. Every business, large and small, every arm of any government, and everyone connected to the World Wide Web is at risk of a cyber attack. While attacks on some have greater consequences than others, all have one thing in common: a reason to fear. In the last decade, the security industry has witnessed an evolution in the attitudes of most businesses. While many organizations did not feel threatened by possible attacks in the past, the growing public pressure, regulatory consequences, and financial repercussions of falling victim to a hacker’s malicious intentions has forced companies to adopt a more proactive approach toward network and data security. As a result, the industry of securing sensitive data is evolving and producing the next generation of tools to combat threats, including scalable container platforms like Twistlock.
Industry Standardization
Although not exactly a tool, industry standardization is creating an environment where collaboration is possible. Think about it this way: the development of protocols, or standards, made the internet revolution possible. When companies worked together and created agreements on how to communicate, the ability to connect private networks evolved to a point where a network of networks became possible, ultimately evolving to what we now call the internet. If collaboration made possible one of the greatest creations in the history of mankind, could it also help in protecting a problem caused by its creation? In this area, Cisco is making great strides in the development of a concept called sensitive data identity tagging. The idea behind this concept is to tag private data as such, thus forcing all network-based security systems to enforce protocols that protect the information. For this concept to be successful, influential companies like Microsoft, Apple, and others need to agree on standards.
The Best Defense is a Great Offense
Another evolution in the attitude of companies is to operate under the assumption that information within their networks and computer systems is compromised. When organizations shift the behavior and work under this premise, defensive tactics turn to offensive tactics. This concept is called foundational security, and the shift allows companies of any size to drop the aspect of pride and assume that breaches have taken place. Therefore, information technology (IT) experts and security professionals work together to hunt attackers within their network infrastructure. This requires a new type of tool. Instead of focusing on defense mechanisms and protection, companies use software to actively search for breaches.
Artificial Intelligence and Machine Learning
Another area of great evolution is the integration of Artificial Intelligence (AI) into the realm of cybersecurity. Although experts disagree on the terminology used, security companies are beginning to develop programs and tools that use Machine Learning (ML). In layman terms, the concept refers to a computer system or algorithm that adapts to new knowledge. In cybersecurity, these systems learn how attacks are taking place and adapt to prevent them. ML algorithms learn by training on examples of malware. The analysis provides the systems with an idea of what to look for. Instead of looking for signatures, as is the case with antivirus and anti-malware software, the tools search for characteristics and techniques.
The improvement of cybersecurity systems reflects the situation that the world is in. Organizations and government can no longer wait for a security breach to react. Instead, the new environment requires proactivity and adaptive learning. More so, none of the next generation tools that companies are producing are a stop-all, unique, and singular solution. Instead, each tool forms part of the toolkit that all companies need to remain competitive in a risky environment.
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