Security Sales & Integration May 2023 - 36

Systems Integration
AI as Ally vs. Adversary
data collected and processed through the AI
system useless.
Another type of AI cyber-attack is AI model
extraction. Th is is where there is the intent to
steal the AI module and reconstruct the data to
respond alternatively to the way it was intendAdversarial
machine
learning,
a technique that
attempts to fool
models with
deceptive data,
is a growing
threat in AI.
ed to respond.
At the top of the list for dangerous potential
targets of compromised AI are autonomous
weapons systems, next brain-computer interfaces
(BCI), self-driving vehicles, 3D printing,
facial recognition, augmented reality, swarm
intelligence, in addition to the already alluded
to deepfakes and bots.
Distinctions need to be made between systems
referred to as automated versus autonomous.
Automated systems perform repetitive
processes that reduce human interaction yet
are still governed by processes and relationships
managed by humans. Autonomous systems (especially
those that rely on AI) can adjust and
modify outcomes without governance or human
interaction.
Defending Against Exploits
Using strong digital encryption
and cybersecurity best practices
must always be top of mind
in the shadow of defending
against the formidable capabilities
and power of AI.
Using strong digital encryption and cybersecurity
best practices must always be top
of mind in the shadow of defending against
the formidable capabilities and power of AI.
Governing the use of AI by the government,
as well as public and private organizations, is
not too far off .
Th e military perspective against weapons of
war is to establish international guidance and
laws of how, when, and under what conditions
AI can be used in confl ict.
Th e U.S. Department of Defense's " Unmanned
Systems Integrated Roadmap " sets out
a concrete plan to develop and deploy weapons
with ever-increasing autonomy in the air, on
land, and at sea in the next 20 years. A defi ning
feature of these autonomous weapons systems
(AWS) is precisely their ability to operate autonomously:
" robotic weapons ... once activated,
can select, and engage targets without
further human intervention. "
As we seek to have greater nonmilitary privacy
controls and protection of personally
identifi able information (PII), there are specifi c
methods that can be implemented to secure and
train AI models. One such process is known as
Privacy Preserving Machine Learning (PPML).
Another involves code obfuscation techniques
that incorporate face blurring with computer
vision recognition models.
Making sure that AI is fully and completely
aligned to human goals is surprisingly diffi cult
and takes careful programming. AI with ambiguous
and ambitious goals are worrisome, as we
don't know what path it might decide to take to
its given goal.
One thing is certain ... we saw it coming! SSI
DARNELL WASHINGTON (dwashington@
securexperts.com) is President and CEO of
SecureXperts.
36
Security Sales & Integration MAY 2023
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Security Sales & Integration May 2023

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