Email Security in A World of Breaches

In this webinar, we will talk about how to get started as a Women in CyberSecurity (WiCyS) Student Chapter and share ideas on activities, funding, sustainability, competitions, and resources.

AI and ML are playing an outsize role in myriad fields. However, in cybersecurity, it hasn’t had the same share as in several other areas, despite high potential and a growing need. The security companies have been focused more on the core problems and industry experts generally tend to believe that AI will make further foray into various aspects of the security ecosystem. In this webinar, we will discuss the role of AI in different realms of security products and services, such as identity & access management, malware detection and incident response & forensic analysis.

Key takeaways:
- How should enterprises look at leveraging AI to improve their security posture
- Which areas are more likely to see higher adoption of AI and where vendors should place their bets
- What challenges have to be overcome for broader adoption of AI

Speakers:
MuckAI Girish, Chief Business Officer, Appnomic and CEO, Muck.AI
Rohini Kasturi, Chief Development Officer, Pulse Secure

Machine learning platforms are one of the fastest growing services of the public cloud. ML, an approach and set of technologies that use Artificial Intelligence (AI) concepts, is directly related to pattern recognition and computational learning. Early adopters of AI have now rolled out cloud-based services that are bringing AI to the masses.

How are AI, deep learning, machine learning, big data, and cloud related? Can machine learning algorithms enable the use of an individual’s comprehensive biological information to predict or diagnose diseases, and to find or develop the best therapy for that individual? How is Quantum Computing in the Cloud related to the use of AI and Cybersecurity?

Join this webinar to learn more about:
- Machine Learning, Data Discovery and Cloud
- Cloud-Based ML Applications and ML services from AWS and Google Cloud
- How to Automate Machine Learning

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This session will take a practical approach to IT risk management and discuss multi cloud, Verizon Data Breach Investigations Report (DBIR) and how Enterprises are losing ground in the fight against persistent cyber-attacks. We simply cannot catch the bad guys until it is too late. This picture is not improving. Verizon reports concluded that less than 14% of breaches are detected by internal monitoring tools.

We will review the JP Morgan Chase data breach were hackers were in the bank’s network for months undetected. Network configuration errors are inevitable, even at the largest banks as Capital One that recently had a data breach where a hacker gained access to 100 million credit card applications and accounts.

Viewers will also learn about:
- Macro trends in Cloud security and Micro trends in Cloud security
- Risks from Quantum Computing and when we should move to alternate forms of encryption
- Review “Kill Chains” from Lockhead Martin in relation to APT and DDoS Attacks
- Risk Management methods from ISACA and other organizations

Speaker: Ulf Mattsson, Head of Innovation, TokenEx

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Join BrightTALK's LinkedIn Group for IT Security Insights: http://bit.ly/2IsbauU

Artificial Intelligence, machine learning, and deep learning are the raves in network security. It's perceived as the only practical approach to staying ahead of today's cyberthreats.

The various steps used by Artificial Intelligence is not so different than a physician’s approach to treating a patient. You must first understand the patient (or device), monitor and assess that all organs (or components) are behaving as intended, and proactively treat (or remediate) viruses and other harm.

In this session, Dr. May Wang will explore:
- The latest advancements in AI for IoT security using healthcare as an example
- The top security threats to healthcare organizations and how to address them.

With the increasingly connected world revolving around the revolution of internet and new technologies like mobiles, smartphones, and tablets, and with the wide usage of wireless technologies, the information security risks have increased. Both individuals and organizations are under regular attacks for commercial or non-commercial gains. The objectives of such attacks may be to take revenge, malign the reputation of a competitor organization, understand the strategies and sensitive information about the competitor, simply have fun of exploiting the vulnerabilities. Hence, the need to protect information assets and ensure information security receives adequate attention.

In this session, Dr. Umesh Rao Hodeghatta will discuss:
- How AI and Machine Learning can be applied in detecting, predicting and preventing cyber security / information security vulnerabilities
- The benefits of using Machine Learning and AI
- Tools available to perform the same.

The chief problem with cybersecurity is that most of our tools and workforce is geared to waiting for adverse events, detecting those events (sometimes months after the fact), investigating the breach that has already occurred, and then cleaning up. This slow and reactive process ensures breaches happen and security staff us overwhelmed under the noise.

This talk will focus on automation and machine learning techniques that can proactively identify threats seen in the wild based on the latest academic research. This techniques allow organizations to identify suspect infrastructure before it is used to attack them. The key to making this work is infusing machine learning with knowledge of how actual attacks work and the threat landscape. Machine learning without intelligence is merely gussied up mensa math exercises.

It isn't enough to know what the attacker will use to attack, however. Armed with this knowledge, organizations now need to safely automatically block these attacks before they occur so breaches never happen to begin with. The goal of automation must be to stop attacks before they are launched, not merely speeding up incident response. Several case studies will be discussed showing how this all can work together in the real world.

Takeaways:
- How to use machine learning and why it is essential to use strong intelligence to create models
- Techniques to use automation to block attacks before they are launched against a victim organization
- Cost-effective and safe ways to whitelist and blacklist infrastructure to insure against false positives

Time and talent are key factors in preventing a data breach. Join Vectra, the leader in AI powered Network Detection & Response (NDR) to explore how enterprises are evolving their security capabilities to become more agile, efficient, and dramatically reduce attacker dwell time through the application of AI.

Join this session to learn:
- How should we balance defensive controls against a need to build detection and response capabilities?
- How is cloud adoption impacting security architectures?
- What roles should automation play within security operations?

What does it mean to be protected and safe? You need the right people and the right technology. This presentation is going to go into the broad introduction of security principles in general. This will include some of the main aspects of security, including defining the terms that you must know, if you hope to have a good grasp of what makes something secure or not. We’ll be talking about the scope of security, including threats, vulnerabilities, and attacks – and what that means in real storage terms. In this live webcast we will cover:

•Protecting the data (Keeping “the bad” out)
•Threat landscape, Bad actors/hackers
•Attack vectors, attack surfaces, vulnerabilities
•Physical security issues
•Layers of protection (encryption – last line of defense)
•Remediation after a breach/incident