As the new year starts to settle in, and, for those of you in the northeast, warm yourself from the recent cold, it’s also a good time to reflect on past cybersecurity trends that will continue into this year, and further attempt to erode the security of your network.
In today’s digital age, the rise of cyber attacks and data breaches has made it imperative for organizations to invest in robust cybersecurity measures. The threat landscape is rapidly evolving, and organizations must be proactive in protecting their assets and data from cyber attacks. One of the most critical components of an organization’s security posture is its network traffic. Network traffic refers to the flow of data in and out of an organization’s network and includes all the devices, applications, and services that make up the network.
Let’s look at three cybersecurity trends you should pay attention to in 2023 and understand how to take advantage of network flow data to gain greater visibility to thwart cybercriminals’ efforts.
Endpoint behavior and risk
Endpoints are the gateways to an organization’s network, and they are often the primary targets for cybercriminals. Endpoints can be laptops, smartphones, servers, or other devices that access the network. Endpoint behavior refers to how these devices interact with the network, and this behavior can be monitored to identify potential threats. Network traffic analytics can help organizations detect anomalies in endpoint behavior that may indicate a security risk. For example, if an endpoint begins communicating with known malicious IP addresses or accessing sensitive data, the organization can take action to prevent a potential breach.
According to a recent Ponemon report, 68% of organizations have experienced an endpoint attack, while 32% of employees use unapproved communication and collaboration tools. These trends indicate that companies are especially vulnerable to endpoint attacks, and unsecured devices could be part of the issue.
The good news is that 97% of businesses, according to a report by Okta, have or plan to initiate zero-trust policies, so while the risk is real, the willingness to reduce the risk is very high among businesses.
Cloud traffic and workflows
As organizations adopt cloud computing, they must also be aware of the potential security risks that come with it. 60% of organizations have a multi-cloud infrastructure, which means a myriad of risk surfaces as those clouds and internal systems communicate. Network traffic analytics can help organizations monitor cloud traffic and identify potential threats. For example, if an organization’s cloud traffic is communicating with known malicious IP addresses, it can take action to prevent a potential breach.
With advanced machine learning, these capabilities can be further extended to help businesses detect cloud-based security incidents. Per Venafi, 81% of businesses experience such incidents and many could be easily detected and resolved with the appropriate network data.
Many organizations have complex infrastructure challenges as would be expected from a multi-cloud environment, but solving this security complexity is exactly what network flow data and machine learning is meant to solve.
Early ransomware detection
Ransomware is a type of malware that encrypts an organization’s data and demands payment in exchange for the decryption key. Ransomware attacks can cause significant damage to an organization, and early detection is critical to preventing a successful attack. In 2022, there were 236 million ransomware attacks globally and they cost businesses an average of 4.54 million dollars.
Network traffic data can help organizations detect ransomware by monitoring for unusual behavior and traffic patterns and by monitoring network traffic, organizations can proactively identify and mitigate potential security risks, including those posed by endpoint behavior, cloud traffic, and ransomware. Deep network observability (DNO) provides organizations with real-time visibility into their network, which is crucial in detecting and responding to potential threats. Additionally, DNO can help organizations prioritize their security efforts and allocate resources where they are needed most.
Deep network observability is a critical tool for organizations looking to enhance their security posture. By providing real-time visibility into network traffic, organizations can proactively detect and respond to potential threats, including those posed by endpoint behavior, cloud traffic, and ransomware. Investing in deep network observability is an essential step in protecting an organization’s assets and data from cyber attacks. To learn more about Plixer’s DNO platform, book a demo today.