With the number of cyber-attacks continuing to increase at an exponential rate, CISOs need to develop strategies to effectively safeguard their network infrastructure. Hence, it is crucial for the leaders to be updated with all the new network security trends that will influence cybersecurity security and network infrastructure.
The past couple of years have been one of the busiest years for cybersecurity professionals. Enterprises failing to take the necessary security precautions to protect their network infrastructure in an attempt to accelerate their digital transformation resulted in the explosion of cyber-attacks. As per the “2020 Q3 Report Data Breach Overview” from RiskBased Security, data breaches exposed 36 billion records in the first half of 2020 alone. Additionally, as per IBM Security’s “Cost of Data Breach Report 2020,” the average cost of a data breach was USD 3.86 million in 2020.
While enterprises have begun to take steps towards prioritizing security, the advancement in the techniques employed by threat actors means that it will be a long time before will be able to keep up with their cyber threats. Even though enterprises may not be able to fully prevent cyber-attacks, they can still take necessary security measures to protect their network. To effectively address them, enterprises should keep track of the network security trends that will provide them insights into the current state of the network infrastructure and the necessary steps they can take to strengthen them. Here are three network security trends CISOs should look out for in 2022:
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Threat to the network continue to grow more sophisticated
‘Businesses and governments are in a vulnerable state,”
says Eyal Elyashiv, CEO and Co-Founder, Cynamics. He adds, “With cyber-attacks proliferating in every industry and at greater speed, scale and sophistication, organizations need to make bold moves to succeed in this fight. Cybercriminals are opportunistic and during the pandemic, they were able to capitalize on the fact that critical infrastructure had to move operations online nearly overnight. Organizations need to utilize protection capabilities to bridge that gap created in the rapid transition to the cloud during COVID-19.”
Eyal Elyashiv believes that attackers, terrorist groups and political activists are going to be using advanced technological capabilities to progress their agendas and carry out more sophisticated and widespread attacks than when business and the global economy were in survival mode. “In the coming year, we’ll see more of this taking place. Cybercrime is an iterative process; just as our solutions and technologies get smarter, so do the very criminals who seek to take down corporations and governments for ransom,” adds Eyal Elyashiv.
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Bad actors will take greater advantage of AI
“Just like organizations are using AI to cut through the noise and provide predictive rules – curating intelligence beyond what the human brain is capable of – cybercriminals are also taking advantage of this technology,” says Eyal Elyashiv. He adds, “AI can be found on both sides of the coin; AI is arming opportunistic bad actors with the intelligence needed to study and target organizations through things like random memory attacks, identification of specific vulnerabilities, exposing weaknesses, and launching custom attacks that go undetected due to no actual misconfiguration. Organizations need to fight machines with machines to overcome, outsmart, and dead end these attackers.”
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The biggest trends in network detection and response
“Traditionally, network detection and response (NDR) solutions have utilized deep packet inspection (DPI) to manually process traffic across the network,” Dr. Aviv Yehezkel, CTO and Co-Founder, Cynamics.
“This was sufficient decades ago, but with today’s landscape and increasing connectivity, it’s nearly impossible for organizations and governments to adequately monitor the volume and variety of network traffic. Going forward, next-gen NDR solutions must use pattern inspection to analyze and monitor network traffic. Organizations will start capitalizing on AI and ML to digest traffic behavior, comparing historical values and trends to identify and predict suspicious patterns. Solutions that offer sample-based tools to support multi-architecture and multi-environment will gain in popularity as these can collect data from every network device and provide a flow summarization of 100% of the network packets. This lowers processing costs, requires no changes to the network, and imposes no additional risk on organizations,” he adds.
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