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June 13-14th, 2023
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2023 Featured Speakers

Adam Ely

Adam Ely

Fidelity
CISO

Shaun Marion

Shaun Marion

McDonald’s
VP, CISO

Kathy Wang

Kathy Wang

Discord
CSO

Lena Smart

Lena Smart

MongoDB
CISO

Jason Shockey

Jason Shockey

Cenlar FSB
SVP, CISO

Igor Varnava

Igor Varnava

Five9
SVP, CISO

Brian Markham

Brian Markham

EAB
CISO

Chris Castaldo

Chris Castaldo

Crossbean
CISO

Michael Piacente

Michael Piacente

Hitch Partners
Managing Partner

Evan Wolff

Evan Wolff

Crowell & Moring
Partner

Evan Wolff

Jonathan Jaffe

Lemondade
CISO

Lakshmi Hanspal

Lakshmi Hanspal

Amazon Devices and Services
Global CISO

Jim Routh

Jim Routh

MassMutual, American Express, DTCC & Aetna
Former CSO & CISO, & Board Advisor

2023 Agenda is Coming Soon

Designed for senior level cybersecurity leaders to discuss, share and learn innovative information security and risk management strategies, SecurityWeek’s CISO Forum, will take place in 2023 as a virtual event.

Throughout this two-day virtual event, sessions will have a strong focus on participation from CISOs in panel discussions along with talks from industry experts, analysts and other end users, and thought leadership, strategy and technical sessions.

Through a cutting-edge platform, attendees will be able to interact with speakers and sponsors, and visit networking lounges, subject-specific discussion areas, and sponsor booths in a virtual expo hall.


An Exclusive Executive Forum Focused on Cybersecurity Leadership and Strategy

Virtual Event – View Event Website

Throughout this two-day virtual event, sessions will have a strong focus on participation from CISOs in panel discussions along with talks from industry experts, analysts and other end users, and thought leadership, strategy and technical sessions.

Through a cutting-edge platform, attendees will be able to interact with speakers and sponsors, and visit networking lounges, subject-specific discussion areas, and sponsor booths in a virtual expo hall.

Previous CISO Forum Speakers

Adrian Stone

Adrian Stone

Peloton
VP, CISO

Anne Marie Zettlemoyer

Anne Marie Zettlemoyer

Mastercard
VP, Security Engineering

Caleb Sima

Caleb Sima

Robinhood
CISO

Allan Friedman

Allan Friedman

Cybersecurity and Infrastructure Security Agency (CISA)
SBOM Champion

Summer Craze Fowler

Summer Craze Fowler

Argo AI
CISO/CIO

Fredrick Lee

Fredrick ‘Flee’ Lee

Gusto
Chief Security Officer

Shaila Shankar

Shaila Shankar

Cisco
SVP and General Manager of Cisco Cloud Network and Security

Jonathan Jaffe

Jonathan Jaffe

Lemonade
CISO

Aanchal Gupta

Aanchal Gupta

Microsoft
VP, Azure Security

Lena Smart

Lena Smart

MongoDB
CISO

Sounil Yu

Sounil Yu

JupiterOne
CISO

Theresa Payton

Theresa Payton

Former White House CIO
Star of CBS TV series, “Hunted”, and Leading Cybersecurity Expert

Why AI Raises Your Risk of Cybercrime – And What to do About It

11/08/2018 0

The robots are coming. It has become conventional wisdom that artificial intelligence (AI) and machine learning (ML) will increasingly determine our lives going into the future. By 2020, according to an estimate from Capterra, about 85% of customer-business interactions will take place with AI, without a human involved. 47% of organizations with advanced digital practices have a defined AI strategy, based on data from Adobe. But for IT and security executives and professionals who must protect against cybercrime, AI poses both a promise and threat.

The industry is looking toward the promise of AI tools to stay a step ahead of the cybercriminals. Experian’s 2018 annual Data Breach Preparedness Study found just 31% of respondents were confident in their organization’s ability to recognize and minimize spear phishing incidents, and just 21% were confident in their organization’s ability to deal with ransomware. Malware and cyberattacks evolve over time. ML uses data from previous cyberattacks, leveraging what it knows and understands about past attacks and menaces to identify and respond to newer, similar risks. The thinking also goes that AI and ML will help save time for overburdened IT departments.

The threat comes from the bad guys also employing AI to create more sophisticated attacks, enhancing traditional hacking techniques like phishing scams or malware attacks. For example, cybercriminals could use AI and ML to make fake e-mails look authentic and deploy them faster than ever before. Criminals could apply AI to develop mutating malware that changes its structure to avoid detection. AI could scrub social media for personal data to use in phishing cons. Data poisoning is another danger, in which attackers find out how an algorithm is set up, then introduce false data that misleads on which content or traffic is legitimate and which is not.

A lesser threat comes from within the industry, as companies rush to market with so-called AI cyber security tools. There is a difference between AI and machine learning. ML algorithms train on large data sets to “learn” what to look for on networks and how to respond to various scenarios. Generally, ML needs new training data to calculate and reach new conclusions, while a true AI system does not.
Some products are based on “supervised learning,” requiring the data sets that algorithms are trained on to be chosen and labeled, by tagging malware code and clean code, for example. Some vendors are using training information that hasn’t been thoroughly scrubbed of erroneous data points, which means the algorithm won’t catch all attacks. Hackers could switch tags so that some malware is designated as clean code, or simply figure out the code the ML is using to flag malware and delete it from their own, so the algorithm doesn’t detect it.

Given the fast-changing landscape, here are some tips to realize the enormous potential of AL and ML and still protect your organization.

Resist the hype. AL and ML are the hot buzzwords and technologies of the moment. But there’s also a great deal of confusion. According to ESG Research, just 30% of cybersecurity professionals feel they are very knowledgeable about AI and ML and their application to cybersecurity analytics. When purchasing an AI or ML tool, try to do your research and understand what you’re buying so that it’s an effective and appropriate solution for your organization.

Keep a human involved in the process. There used to be an old IT truism of bad data in, bad data out. The “intelligence” in AI is based on data inferences and correlations, which need to be checked and monitored so the model is addressing risks appropriately and evolving as you need. ML systems shouldn’t be totally autonomous. They should be set up with a human in the loop, and the ML should know to ask for help with presented with an unfamiliar situation.

Have a strong data breach plan. According to Experian’s Data Breach Preparedness Study, 88% of organizations have a data breach response plan in place, but less than half (49%) think it is effective or highly effective. If you have a plan, it shouldn’t just sit on a shelf. Make sure that it is robust, with buy-in from all the key departments of your company, and drill on it early and often. If you need to get started on a plan or refine it, Experian’s updated Data Breach Response Guide can serve as a resource.

AI and ML are the wave of the future. But the cyber threats are real now, and so are the limitations of the technology as a foolproof protection tool. Be aware, both of what’s ahead from the cybercriminals and how you’re applying AI solutions, so you’re not lulled into a false sense of security.

 

About the Author: Michael Bruemmer, Experian Michael Bruemmer is Vice President of Experian Data Breach Resolution, which helps businesses mitigate consumer risk following data breach incidents.


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