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Printable Handouts
Navigable Slide Index
- Introduction
- Cybersecurity awareness: Train or explain?
- Why target me (or my organization)?
- Today’s topics
- Social engineering (SE): It’s nothing new!
- Malicious social engineering techniques
- SE techniques
- The elevator ride
- Four phases of SE
- Two key elements of SE
- RESCAT
- Emotional characteristics of SE
- Routine activity theory (RAT)
- RESCAT and routine activity theory
- Success or failure of a socially engineered initiative
- Thought processes when reacting to information or directives
- Machine learning (ML)
- Artificial intelligence (AI)
- Realtime imaging with AI
- Realtime re-imaging with AI
- Productive uses of AI
- Negative impacts of AI
- Generative AI (GenAI)
- Three main analytical phases used by GenAI
- Challenges of detecting AI-created information
- Deepfakes
- Deepfakes and deep learning
- $25M deepfake Zoom scam
- What could have been done to prevent this scam?
- Impacts of malicious deepfakes
- Defending against scams
- Generative adversarial networks (GANs)
- Why does GANs matter?
- Reporting a cybercrime
- Reporting a cybercrime in the USA
- Reporting a cybercrime in Canada
- Reporting a cybercrime in the UK
- Recognizing our risks as users of technology (UoT)
- Other considerations to avoid scams
- Final considerations
- Conclusion
- Thank you
This material is restricted to subscribers.
Topics Covered
- Social engineering (SE)
- Malicious social engineering techniques
- Required elements for a social engineered cyber attack theory (RESCAT)
- Routine activity theory (RAT)
- Machine learning (ML)
- Generative AI (GenAI)
- Deepfakes and deep learning
- $25M deepfake Zoom scam
- Defending against scams
- Generative adversarial networks (GANs)
- Reporting a cybercrime
Links
Categories:
External Links
- Slide 26: Deepfake Video Detection: Challenges and Opportunities
- Slide 35: FBI’s Internet Crime Complaint Center (IC3)
- Slide 35: FBI Cyber (for Major Cyberattacks and Intrusions)
- Slide 35: Cybersecurity and Infrastructure Security Agency (CISA)
- Slide 36: Canadian Centre for Cyber Security
- Slide 36: (RCMP) National Cybercrime Coordination Centre (NC3)
- Slide 36: (Government of Canada) Canadian Anti-Fraud Centre
- Slide 36: Office of the Privacy Commissioner of Canada
- Slide 37: National Fraud Intelligence Bureau (Report Fraud)
- Slide 37: Gov.UK (London)
- Slide 42: Cybercrime Analytics
Talk Citation
Kayser, C.S. (2026, September 30). Psychological challenges of detecting AI-generated cyber scams [Video file]. In The Business & Management Collection, Henry Stewart Talks. Retrieved October 1, 2026, from https://doi.org/10.69645/VGDH1852.Export Citation (RIS)
Publication History
- Published on September 30, 2026
A selection of talks on Technology & Operations
Transcript
Please wait while the transcript is being prepared...
0:00
Hello, everyone.
I'm Chris Kayser,
founder of Cybercrime
Analytics Inc.,
based in Calgary,
Alberta, Canada.
I'm a cyber criminologist
involved in
many aspects of cybercrime
awareness and prevention,
a published researcher
and author of the book:
Cybercrime Through Social
Engineering: The New Global Crisis.
My research, presentations
and publications
frequently address the subject
of social engineering.
It is widely accepted
that greater than 90% of
all cyber attacks involve
some form of social engineering.
We will examine a
number of aspects of
social engineering in
this presentation,
and the advent of AI as
they relate to efforts to
manipulate our human nature and
curiosity and numerous emotions.
0:42
This slide sets the tone
for today's presentation.
This study suggests
that most people do not
retain cyber prevention
training for long.
It is not so much that
training is not valuable,
but that it could
be some time until
we experience a
malicious attack which,
by that time, can be
difficult to recognize.
I believe that the concepts
and characteristics of
cyber criminality can be
explained in simple terms;
we will be more inclined
to remember them
when we're confronted by
nefarious characters.
1:10
Whenever we or our
organization is hacked,
our first thought is often why?
The answer is simple.
Bad actors are
seeking information
that can be used for
illicit purposes.
Often we do not recognize
assets that cyber criminals
consider valuable.
As individuals, we
realize that our
Personal Identifiable
Information, or PII,
such as when we were born,
our mother's maiden
name and government
issued IDs can be
used by scammers.
But equally appealing
to bad actors are
social activities, political
opinions and preferences,
travel habits and other data
we share on social media sites.
Along with our PII, these
types of information
can be used to create
fake portrayals of us,
particularly when our images
and voice prints are acquired.
Organizations are
challenged to identify
which assets might be
attractive to a bad actor.
Sales and marketing materials,
intellectual property,
internal processes for
conducting business
can be used for a
ransomware attack,
sold to competitors,
or used for misleading
communications such as
fake websites that can
contain embedded viruses.
Most concerning is that
any acquired information
can be made available
instantly on the dark web,
and remain there for others
to purchase into perpetuity.
The risk-reward for
cyber criminals
is typically in their favor.
The odds of getting
caught remain low,
successful
prosecutions are rare,
and the rewards can
be significant.
While many hacks occur by
bypassing technology firewalls,