Blog

CPO Magazine: Proactive vs Responsive AI: Which One Protects Against Major Modern Adversaries in Cybersecurity?

Blog, MixMode News, Third-Wave AI / By

MixMode CTO and Chief Scientist, Igor Mezic, recently contributed an article for CPO Magazine that examines the evolution of Machine Learning (ML) and Artificial Intelligence (AI) within cybersecurity, the three waves of AI, and the modern-day application of predictive AI in cybersecurity to protect against adversaries who are also utilizing AI technology.

Innovation During a Crisis: A story of PIE and Ice Cream

Blog, MixMode News, Third-Wave AI / By

Some of you may have seen the “funny” statistic in the last few months that during the pandemic, ice cream sales are way up while deodorant sales are way down. Let’s just say that, for me, it’s coffee ice cream. Dessert aside, this stat does lead one to think about what other trends occur during a pandemic or a crisis when we look back at events such as world wars, the Great Depression, the Global Financial Crisis (GFC) of 2007-08, etc.

Our Top 2020 Cybersecurity Insights

Blog, MixMode News, Network Baselines, Network Detection and Response, Network Security, Predictive AI, Self-Supervised AI, SIEM, SOC, Third-Wave AI, Webinar, Whitepaper / By

The transition from office to remote environments was abrupt and one of the most defining moments that the cybersecurity industry and professionals faced in 2020. We wrote about the top issues CISOs were facing throughout the year but also doubled down on sharing insights about the evolution of next-generation SOCs, the failure of SIEM platforms as organizations are experiencing them today, and how self-supervised AI fits into the equation.

Russian Hack of U.S. Federal Agencies Shine Spotlight on SIEM Failures in Cybersecurity

Adversarial AI, Blog, Data Breach, Network Baselines, Network Detection and Response, Network Security, Network Traffic Analysis, Predictive AI, Self-Supervised AI, SIEM, Third-Wave AI, Threat Detection / By

In what the New York Times is calling, “One of the most sophisticated and perhaps largest hacks in more than five years,” malicious adversaries acting on behalf of a foreign government, likely Russian, broke into the email systems of multiple U.S. Federal agencies including the Treasury and Commerce Departments.

MixMode in the Real World: Customers Turn to MixMode Frustrated and in Search of a Viable SIEM Alternative

Blog, SIEM, SOC, Threat Detection, Use Case / By

SIEM has failed to meet the needs of enterprises in the modern threatscape. One huge reason for this is that over time, most organizations will come to the sad realization that they will never achieve a full enterprise deployment of their SIEM. By its very nature, SIEM is always “in process.” It’s not unusual for an organization to have an SIEM in process for a full decade.

Techiexpert: How Predictive AI Protects Against Ransomware, GANs and More

Adversarial AI, Blog, MixMode News, Network Security, Predictive AI, Third-Wave AI, Threat Detection / By

MixMode CTO and Chief Scientist, Igor Mezic, recently contributed an article for Techiexpert that examines three modern AI adversarial attacks, the financial toll they are having on some of our most important systems (including healthcare), and how predictive, third-wave AI is the only future-proof cybersecurity solution to protect organizations from these intelligent attacks.

Featured Use Case: Why a Large US Utility Company Turned to MixMode to Address Utility Grid Vulnerabilities

Blog, Case Study, Network Security, SIEM, SOC / By

A large utility company approached MixMode with the following scenario: The enterprise SOC was utilizing a shared SIEM application that was being utilized by several stakeholders: the networking team, the SCADA team, the dev-ops team, the compliance team and cybersecurity teams for “basic search and investigation of log files to meet regulatory compliance requirements”.

Recent Ransomware Attacks on U.S. Hospitals Highlight the Inefficiency of Rules-Based Cybersecurity Solutions

Adversarial AI, Blog, Data Breach, Network Baselines, Network Detection and Response, Network Security, Network Traffic Analysis, Predictive AI, Self-Supervised AI, Third-Wave AI, Threat Detection / By

A number of recent high profile ransomware attacks on U.S. hospitals have demonstrated the urgency for organizations, municipalities, and critical services to take a proactive approach to protecting networks with a predictive AI solution.

How Vendors Capitalize on SIEM’s Fundamental Flaws

Blog, SIEM, SOC, Whitepaper / By

Because the fundamental nature of SIEM requires infinite amounts of data, security teams are forced to constantly wrangle their network data and faced with an unmanageable number of false positive alerts. This means they have to devise efficient ways to collect, organize and store data, resulting in an incredible investment in human and financial resources.

The Case Against Using a Frankenstein Cybersecurity Platform

Blog, Network Baselines, Network Detection and Response, Network Security, Network Traffic Analysis, Predictive AI, Self-Supervised AI, SIEM, SOC, Unsupervised AI / By

The cybersecurity market has, simply put, been cobbled together. A tangled web of non-integrated systems and alerts from siloed systems. Enterprises are now being forced to utilize a “Frankenstein” of stitched together tools to create a platform that might cover their security bases.

Improving on the Typical SIEM Model

Blog, Network Detection and Response, Network Traffic Analysis, SIEM, SOC / By

Despite its inherent flaws, today’s SIEM software solutions still shine when it comes to searching and investigating log data. One effective, comprehensive approach to network security pairs the best parts of SIEM with modern, AI-driven predictive analysis tools. Alternatively, organizations can replace their outdated SIEM with a modern single platform self-learning AI solution.

The Evolution of SIEM

Blog, Network Detection and Response, Network Security, Self-Supervised AI, SIEM, Whitepaper / By

It should be noted that SIEM platforms are exceptionally effective at what they initially were intended for: providing enterprise teams with a central repository of log information that would allow them to conduct search and investigation activities against machine-generated data. If this was all an enterprise cybersecurity team needed in 2020 to thwart attacks and stop bad actors from infiltrating their systems, SIEM would truly be the cybersecurity silver bullet that it claims to be.

Whitepaper: The Failed Promises of SIEM

Blog, Data Overload, False Positives, Regulations & Compliance, Self-Supervised AI, SIEM, SOC, Whitepaper / By

The fundamental SIEM flaws lie in the platform’s need for continual adjustment, endless data stores, and a tendency to create an overwhelming number of false positives. When organizations instead turn to a next-generation cybersecurity solution, which predicts behavior with an unsupervised (zero tuning) system, they are poised to save on both financial and human resources.

How Data Normalization in Cybersecurity Impacts Regulatory Compliance

Blog, Data Overload, Regulations & Compliance, SIEM, SOC, Whitepaper / By

Complying with privacy regulations requires all organizations to have access to data on demand, wherever it lives on a network. With the unfathomable amount of data managed by most organizations operating in the finance space today, it can become a significant challenge to locate specific data across legacy systems and networks with countless connections online and off.