Cyber Defense

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Cyber Threats meet Artificial Intelligence

Traditional perimeter defense and alert-driven strategies cannot withstand attackers' latest stealth technologies. Cyber defense is a never-ending arms race to find emerging and unknown threats.

Plenty of narrow point solutions provide a myopic perspective on security events and leave humans alone to piece a holistic picture together.

We all know, that there is no silver bullet, but consolidating our fight against cyber threats is of high priority. Security Operations and Analytics Platform Architecture (SOAPA) is a strong indicator that things are improving already.

Predictive Works' offers a fine-grained approach for SOAPA. AI blueprints provide the ability to see ahead and the agility to change tactics to keep pace with cyber threats.

Does your cyber arsenal look like this?

Two ways to defend unknown threats

Traditional Approach

1

Establish AI project team

2

Discover use case

3

Perform feasibility study

4

Fine-tune project planning

5

Develop data model

6

Implement prototype

7

Make production ready

8

Advise security analysts

9

Detect unknown threats

Blueprint Approach

1

Search market place and find matching problem description

2

Select recommended blueprints and load into orchestrator

3

Orchestrate blueprints to match project needs

4

Upload blueprints to data fabric and fine-tune before execution

5

Execute blueprints and detect unknown threats

Use Case: Threat Hunting

Most companies have accepted that adversaries with a seemingly endless supply of attack vectors will infiltrate even the best defended networks.

Threat hunting lets analysts take a proactive approach to security, as it offers ways to search for attackers that are already in a network.

Hunting requires collecting and analyzing reams of endpoint and network events. Revealing all elements of an advanced attack is a time-consuming task, needs consecutive hunts and is often too demanding for security analysts.

Threat hunting is ambitious and Predictive Works does not claim that artificial intelligence replaces security experts. However, AI blueprints run at scale, significantly simplify work and make hunting more attainable for all organizations.

Suppose, you are a security analysts and need to identify malicious network traffic: Visit the blueprint market place, select a network profiler that supports your monitoring tools and pick an anomaly detector to reduce your huge amount of data to traffic anomalies.

Then, select a threat intelligence feed to remove legit traffic from your anomalies, choose the anomaly graph as your data destination and arrange these components into a data workflow.

Feed Predictive Works' big data fabric with this blueprint and execute it. Now, you are ready to explore the anomaly graph and hunt for indicators of an advanced attack.

This is AI blueprint powered threat hunting.

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