A new forecast estimates there will be 41.6 billion connected IoT devices, generating 79.4 zettabytes of data in 2025. Today, more than 7 million IoT devices are powered up daily and the weaponization of IoT devices is proliferating rapidly as more devices are integrated into networks. Threats from botnets and DDoS for hire services are almost ubiquitous, with high competition and wages as low as $5 per hour. As a result, smart cities are increasingly on their defense by a variety of threats, including sophisticated cyber attacks on critical infrastructure, industrial control systems, connected devices and sensors, or privacy sensitive data.
Prevailing cyber security solutions can protect against malicious network attacks, but can only attain partial network visibility, at the cost of hundreds of monitoring appliances. The leading provider of network visibility solutions is NETSCOUT, with security appliances designed to protect individual network devices, costing up to $100,000 per monitoring device. Moreover, each appliance is limited by processing specifications to 40 gigabytes per second, which quickly become obsolete as connected networks are constantly evolving; in size and traffic rates, as well as in their architecture, migration to cloud and hybrid environments. As a result, CISOs of smart cities are forced to compromise on their network’s security visibility accordingly.
Changing the paradigm is Israeli startup Cynamics, coming off the heels of a seed funding round and newly invented machine learning technology to holistically monitor network traffic without any appliance, and at scale. “Cynamics can monitor your entire network’s traffic with only a 1% sample of the network traffic in order to provide 100% network visibility and security for threat detection” said the startup’s CTO and technology inventor Dr. Aviv Yehezkel. Their new approach to network security and performance grants smart cities and governments unmatched network visibility and super-early prediction of attacks, long before they affect the network, at scale and cost effectively.
The startup was founded by Eyal Elyashiv and Dr. Aviv Yehezkel in early 2019 to coalesce the pair's expertise in network security and artificial intelligence. Elyashiv, CEO, is a seasoned executive with vast experience in the US local government and municipality sector and was COO of public safety and security startup Carbyne 911. Yehezkel, CTO, is an alumnus of Israel’s military Naval Intelligence and unit 8200 as a research captain, and led AI research at NICE Systems. An expert in big data and machine learning, he earned his PhD in Computer Science from the Technion at the age 24, the youngest faculty ever.
“Legacy solutions require thousands of appliances, and only provide partial visibility at best” explained Yehezkel. “Typically, prevailing solutions require all traffic to be constantly forwarded to the network visibility appliance, which analyses the network packets for visibility inside the network and provides alerts in case of a threat. While this approach was well-suited for past networks that had a small amount of network devices and simple architecture, it is no longer relevant or feasible in today’s complex networks. A bottleneck arises in the ability to watch the entire network, which is limited to the number of visibility appliances. Legacy networks, public clouds, private clouds combine together to form one large network that cannot be monitored at all.”
