The US military is now deploying a covert AI sabotage tactic, data poisoning, to corrupt enemy machine-learning systems before combat, exploiting backdoor attacks and human espionage for strategic dominance in AI-based warfare.
By injecting adversarial data into adversaries’ AI training sets, the US can force misclassifications, such as drones mistaking American vehicles for allies, mirroring the Cold War’s espionage, but this time through digitalization.
The AI evolution is redefining military action, taking it from drone exploration to precise targeting. But as machine learning reliance takes a different form, a new frontier in war exists that’s not based on gunpower or troops on the ground. Modern warfare has become a subtle subversion of information.
Nowadays, conflicts are not only won by whoever develops the most sophisticated AI, but by those that can secretly taint enemy information and sabotage their AI systems well ahead of battle.
Through clandestine access of training data poisoning AI warfare, an enemy AI can be tricked into committing fatal mistakes, labeling threats incorrectly, or exaggerating topography and the extent of forces.
The backdoor, adversarial data poisoning sabotages enemy AI foundations, spreading like a virus, and it doesn’t happen by spreading distrust in every target, map, and strategic recommendation their systems produce.
Through this technology, the US seeks victory by making its adversaries question their own machines’ judgments. Meaning wars are won even before they start, with a backdoor entry into machine learning platforms.
It’s an approach of data poisoning that is solely based on adding adversarial data to machine learning databases affecting AI models’ actions. Label flipping or a LLM backdoor attack, embedding triggers are techniques that can force adversary systems to create misclassification of US assets or misread battlefield situations.
Analysts believe tainting enemy AI training data can trick drones into misidentifying US assets as friendly targets. It’s a modern twist on asymmetric warfare. Reminiscent of the Second World War’s (WWII) cryptographic sabotage, these US Code Title 50 covert ops can deliver gains with plausible deniability.
Cyber Weapons Meet Human Tradecraft
While most data poisoning is done online, the most effective methods include human facilitation through spies, academics, or foreign contract agents. Spies can infiltrate enemy labs or data repositories, leaving long term manipulations or trigger-based backdoors that do not activate except under specific conditions.
According to Four Battlegrounds: Power in the Age of AI, Paul Scharre, China produces the largest pool of AI talent, yet many of its researchers remain abroad an opportunity for covert exploitation. These intelligence tradecraft tactics, also mirroring Cold War-era human intelligence (HUMINT) operations espionage but target digital systems rather than physical ones.
To be carried out lawfully and morally, these covert trigger-based poisoning actions fall within the authorities of covert action in Title 50, through presidential approval and congressional approval. The Department of Defense, in coordination with intelligence agencies, can support such data poisoning as covert weapon operations with technical advice and cyber infrastructure.
A War of Data Poisoning
US rivals, China and Russia are developing their own data poisoning capabilities, employing countermeasures like adversarial training, anomaly detection, and blockchain data sanitization validation to safeguard against AI poisoning.
US defenses are vulnerable as military AI leans on open-source data – tainted data could corrupt intelligence, surveillance and reconnaissance (ISR) terrain analysis or cause logistics software to deprioritize critical supply chains.
The Law of Armed Conflict (LOAC) principles of distinction, proportionality, and necessity, ensure operations hit military targets while avoiding civilian harm.
Quietly sabotaging rival AI before deployment will be the ways wars happen and win. Title 50 data poisoning can influence conflicts without bullets, but data poisoning also risks misfire and blowback.
Military dominance may depend not on superior AI, but rather who best infiltrates and manipulates the hidden data streams feeding it.
In this new kind of warfare, the quietest disruption may prove to be the deadliest.
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