Over the past two quarters, MixMode partners, clients, and internal team members have worked together to develop extensive whitepaper and case study resources to share the research, technology, and successes associated with the MixMode platform. 

Here are 4 that you may have missed:

Whitepaper: Unsupervised AI – AI for Complex Network Security

Dr. Stephenson has been practicing in the security, forensics, and digital investigation fields for over 55 years, has earned a Ph.D. in computing from Oxford Brookes University, and is working on his second Ph.D. in cyberspace jurisdiction at Norwich University. In “Unsupervised AI – AI for Complex Network Security,” he explains the most recent progress in Wave-3 (Unsupervised) AI and details its strengths in cybersecurity. He also points out the most commonly–targeted areas that malware is currently attacking.

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Whitepaper: The Evolution of “Next-Generation” Manufacturing and the Need for Network Security

The new MixMode & RAVENii whitepaper, “The Evolution of ‘Next-Generation’ Manufacturing and the Need for Network Security,” is a comprehensive look at how third-wave AI is improving modern network security across connected manufacturing networks and beyond. 

Today’s hyper-connected world is changing the way we work, live, and communicate. 

The manufacturing sector, in particular, has experienced a significant evolution thanks to so-called Internet 4.0 connectivity. Plant managers can oversee production, change specifications remotely, and connect with employees from anywhere. Smart Internet 4.0 networks can self-adjust to changing environmental conditions, automate shipping functions, and control the actions of factory robots.

Unfortunately, for all the promise offered by this next generation of the industrial revolution, connected devices are inherently vulnerable to network security threats. These threats are just as worrisome as traditional network security risks, but both management and SecOps teams tend to overlook internet 4.0 vulnerabilities.

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Case Study: MixMode AI Detects Attack not Found on Threat Intel

In October, 2019 a MixMode customer experienced an incident where an external entity attacked a web server located in their DMZ, compromised it, and then pivoted internally through the DMZ to attempt access of a customer database. While the attacker was successful in penetrating the customer’s network, MixMode was able to detect the event before they were successful in penetrating the customer database.

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Featured MixMode Client Success Story: Nisos

Established by former officers from the U.S. intelligence community and based in Washington, DC, Nisos, provides technology-enabled cybersecurity services and investigations. The company is a trusted partner to many Fortune 500 firms that need to secure their on-premise and Cloud-based assets to avoid existential threats to their businesses.

After suffering a possible breach, a client approached the team at Nisos for help evaluating the security of their AWS environment. The client was concerned about possible malicious activity on the part of a former employee who had maintained an AWS Identity and Access Management (IAM) account after being separated.

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MixMode Articles You Might Like:

How a Massive Shift to Working From Home Leaves an Enterprise’s Cybersecurity Vulnerable

In Case You Missed It: MixMode Integrations of 2020

New Video: How does MixMode’s context-aware AI build a network baseline?

Whitepaper: Actionable Anomalies – How MixMode AI Makes Your Security Data Smarter

Hackers Use Coronavirus Panic to Push Phishing Email Scams

Integrating MixMode with DeepInstinct

New Video: Why is network data the best source for actionable data in cybersecurity?

5 Cloud Security Challenges Facing Enterprises Today