BSIDES CPT 2019 - How machine learning and AI can help reduce the cyber- attacks - Silent Dzikiti

Title: How the application of machine learning and AI can help reduce the cyber-security attacks.

Abstract:
According to Global cyber security company Kaspersky Lab South Africans have once again been warned to be careful in cyberspace with a 22% increase in malware attacks in the country in the first quarter of this year. It seems that every presentation from every security vendor begins with an introductory slide explaining how the number and complexity of attacks an organization faces have continued to grow exponentially.

Of course, everyone from security operations center (SOC) analysts, who are drowning in alerts, to chief information security officers (CISOs), who are desperately trying to make sense of the trends in security, is acutely aware of the situation. The question is how do we, collectively, solve the problem of overwhelmed security teams?

The answer in many cases now involves machine learning (ML) and artificial intelligence (AI). Instead of looking at ML tasks and trying to apply them to cybersecurity, let’s look at the common cybersecurity tasks and machine learning opportunities. There are three dimensions (Why, What, and How).

The first dimension is a goal, or a task (e.g., detect threats, predict attacks, etc.).
• prediction;
• prevention;
• detection;
• response;
• monitoring.

The second dimension is a technical layer and an answer to the “What” question (e.g., at which level to monitor issues).
• network (network traffic analysis and intrusion detection);
• endpoint (anti-malware);
• application (WAF or database firewalls);
• user (UBA);
• process (anti-fraud).
The third dimension is a question of “How” (e.g., how to check security of a particular area):
• in transit in real time;
• at rest;
• historically;
• etc.

There is no doubt that AI and Machine learning enabled technologies are already a critical part of many security teams application and I will show how they are being applied.
Speaker: Silent Dzikiti

Twitter: @SilentDzikiti
Speaker Bio:
My name is Silent Dzikiti. I am a Data Scientist and i am studying Computer Science.
I am a Zimbabwean. I stay in Muizernberg, Cape Town. South Africa. I have
researched and applied the knowledge I will share on your highly esteemed
conference.

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