New talks at The Standoff: adversarial machine learning, 5G vulnerabilities, and COVID-19 effects on security

We are approaching The Standoff, a global information security event. We already presented the first group of speakers who will give their talks at our online conference.

Today we present the second group of speakers whose presentations have been included in The Standoff discussion section. Here is what they will talk about.

Adversarial machine learning

John Bambenek, cyberdetective and President of Bambenek Labs, will talk about adversarial machine learning and how it applies to cybersecurity models. Adversarial machine learning is typically how malicious actors fool image classification systems, but the discipline also applies to cybersecurity machine learning.

Some recent attacks will be shown, along with how to protect against and mitigate them.

Introduction to electromagnetic FI. How to use it to break into Android MDM

In his talk "Introduction to electromagnetic FI. How to use it to break into Android MDM," IoT security researcher Arun Magesh will explain how to use electromagnetic FI to break into Android MDM.

The speaker will cover theory behind electromagnetic FI and various methods for building a very cheap EMFI device. The speaker will also talk about various methods of attacking devices using EMFI, including demo of breaking into Android MDM.

COVID-19 effects on information security

Muslim Koser, cofounder and Head of Products & Technology at Volon will analyze how COVID-19 has affected the threat landscape. Remote working has become acceptable and even preferred in a way that was unheard of pre-pandemic. This has also opened doors for adversaries: now there is no corporate perimeter. In many cases, all that remains between the end user and attacker is a home broadband router.

In the last six months, attacks have increased by a factor of several times compared to the same period last year. Threat actors have also used innovative techniques to carry out their attacks. Discussion will include: examples of these attacks; how threat actors have capitalized on COVID-19 anxieties; new attack TTPs observed during this period; how novel cybersecurity technologies are emerging to tackle these threats; and industry best practices to remain protected.

How to protect 5G networks from hacks

How dependency on previous generations affects the 5G stand-alone deployment and the security of new infrastructure.

5G networks heavily depend on previous-generation networks—all security challenges stay in the new era. In order to demonstrate and prove that 5G should not be considered secure by default, it is important to understand why dependency on previous generations affect the 5G stand-alone deployment and that new architecture is not yet a silver bullet.

Heuristic methods of detecting malware

In his report "Stopping a serial killer: predicting the next strike" malware researcher Raman Ladutska will show how to apply heuristics to the world of malware by using the example of the Dridex botnet.

Take a city map, mark the spots of previous crimes, and you will likely find the pattern and even the likely location of the next crime. Raman and his team will take Dridex, one of the most prevalent botnets today, and mark the previous crime scenes, build the map, and predict where the next strike will come. Raman will show by-the-numbers evidence of the usefulness of this approach and explain how to apply this idea in other real-world cases.