How LightCyber Quickly Stops Targeted Attacks & Data Breaches

LightCyber Prevents Targeted Attacks & Data Breaches Before Theft And Damage Typically Occurs

In the past, traditional security systems hardly focused on detecting attacks before they reached a network. However, to match up with the rising demand for highly effective security systems, especially among tech startups in NYC, network security experts had to come up with options to solve the challenge of detecting an attacker before the actual theft or damage to assets in a network occurs. While this concept seemed a far-fetched idea decades ago, an Israeli startup in NYC came up with a solution: LightCyber – an ultramodern security technology. But, how does LightCyber actually integrate such a high-level cyber security system in NYC startup networks? Read on to find out how.

Machine Learning to Learn Behavioral Profiles of Network Users

LightCyber utilizes a technical approach by profiling all devices and users on a particular network by using machine learning to learn the behavioral profiles of the devices and users on the network and establishes a record of known behavior. This way, it’s easy to detect attack anomalies since the behavioral model is constantly updated in order to efficiently detect the anomalies, especially within NYC startup networks. This focusing on behaviors yields a high level of accuracy, further minimizing the number of alerts; a role that is efficiently achieved with the Magna platform as outlined here:

The Magna Platform

Magna is a behavioral platform that detects attacks, malware, and insider threats. LightCyber, an Israeli Startup company based in NYC, created this platform with the knowledge that an attacker can circumvent a prevention system and still access network resources. Therefore, the Magna platform is able to identify compromised entities in the attack cycle, which makes this platform the best security system in the market that integrates both endpoint and network contexts. NYC startups no longer need to suffer the pain of depending on traditional systems that produce false positives. The end result of using the Magna platform is accessing accurate alerts with investigative data aimed at stopping the attackers before damage occurs.

Magna Architecture

The major components of a Magna platform include:

Magna Master and Detector

The Magna master manages multiple magnate probes and detectors in an organization and incorporates identity and security services to allow one-click remediation. The Magna detector, on the other hand, is a network or virtual appliance that inspects network traffic and aggregates the data from Magna probe and Magna pathfinder. By monitoring protocols, sources, and destinations, the detector builds a profile of device and user’s activity on the network making it easy to identify an anomaly. Both the Magna master and Magna detector, run on the same hardware.

Magna Pathfinder

The Magna pathfinder is a software subscription service that reveals the cause of the attack and automates the findings. This component helps realize the full potential of the Magna platform by incorporating the endpoint context into attack detection.

Magna Probe and the Magna Cloud Expert System

Magna Probe is an optional appliance that allows security visibility across separate networks. The Magna probe inspects the network and extracts the metadata, but first sends the metadata to the Magna detector for attack detection. The Magna cloud expert system applies malware analysis and threat intelligence into Magna to detect an attack. The analysis involves comparing the files uncovered by pathfinder and the anti-virus hashes and analyzing them with an antivirus scanner. The results are then run in a sandbox.

Significance of Magna’s automatic system

LightCyber, an Israeli Startup company based in NYC, created the Magna platform to be fully automated so tech startups in NYC will not need to create a policy, configuration or any form of algorithmic tuning. This model of automation architecture allows the platform to deliver straightforward attack alerts without having to contact a data scientist to interpret what could be happening. Additionally, Magna gives details of what was flagged and why by creating an attack alert together with reasons why that particular attack was flagged. This makes it easy for the users to see the actual event that caused a trigger. This feature of explaining ’why’ offers tech startups in NYC automatic research and accuracy in making security systems more effective and efficient.

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For more information see the LightCyber infographic below.