Data Overload Problem: Data Normalization Strategies Are Expensive

Financial institutions spend five to ten million dollars each year managing data. A recent Computer Services Inc (CSI) study reveals that most banks expect to spend up to 40 percent of their budgets on regulatory compliance cybersecurity, often adoptin… Continue reading Data Overload Problem: Data Normalization Strategies Are Expensive

Recommendations to enhance subscriber privacy in 5G

There are clear benefits of 5G SIM capabilities to protect the most prominent personal data involved in mobile communications, according to the Trusted Connectivity Alliance. Addressing privacy risks The IMSI, known as a Subscription Permanent Identifi… Continue reading Recommendations to enhance subscriber privacy in 5G

Whitepaper: The Data Overload Problem in Cybersecurity

The very nature of data is its infinite capacity for growth. For security teams at large, highly integrated and complex enterprises like financial services institutions, that growth can quickly become unwieldy when the approach is to store, normalize a… Continue reading Whitepaper: The Data Overload Problem in Cybersecurity

Guide: How to Choose an AI-Based Cybersecurity Platform

Most cybersecurity vendors today tout some form of “Artificial Intelligence” as an underlying mechanism for the differentiation of their product among the market. But if everyone is saying they have AI, and everyone is also claiming theirs … Continue reading Guide: How to Choose an AI-Based Cybersecurity Platform

NTA and NDR: The Missing Piece

Most SIEM vendors acknowledge the value of network traffic data for leading indicators of attacks, anomaly detection, and user behavior analysis as being far more useful than log data. Ironically, network traffic data is often expressly excluded from S… Continue reading NTA and NDR: The Missing Piece

Why Training Matters – And How Adversarial AI Takes Advantage of It

The following is an excerpt from our recently published whitepaper, “Self-Supervised Learning – AI for Complex Network Security.” The author, Dr. Peter Stephenson, is a cybersecurity and digital forensics expert having practiced in th… Continue reading Why Training Matters – And How Adversarial AI Takes Advantage of It

Machine Learning, Deep Learning and Neural Networks, Oh My!

Deep learning makes decisions based upon the data it sees and the data that it doesn’t see but infers from what it does see. This became useful in the AV industry when the adversary introduced polymorphic viruses. These are viruses that change th… Continue reading Machine Learning, Deep Learning and Neural Networks, Oh My!

4 Challenges of Stand-Alone SIEM Platforms

While SIEM is undoubtedly a step up from unmonitored network environments, the inherent nature of today’s SIEM software often falls short in several important ways. SIEM is an outdated solution for adequately protecting networks within the modern… Continue reading 4 Challenges of Stand-Alone SIEM Platforms

Whitepaper: Self-Supervised Learning – AI For Complex Network Security

Artificial Intelligence – or AI – has become a buzzword since it emerged in the 1950s. However, all AI systems are not created equal. In our white paper, “Self-Supervised Learning – AI For Complex Network Security,” Dr. Pe… Continue reading Whitepaper: Self-Supervised Learning – AI For Complex Network Security