Adversarial attacks on AI

Adversarial Attacks on AI

Artificial Intelligence or AI is used nowadays in almost every sector or industry like the military, healthcare, banks, automobile, and whatnot. It has made processes easy and efficient for humans. But with its use in every sector, it becomes vulnerable to adversarial attacks.

Let’s look at some adversarial attacks on AI.

Hijack Military Drones

By this adversarial attack, an attacker can take control over a military drone and attack at random unidentified targets that may cause loss of property, life, and putting the security of a military area at risk. This may look unrealistic but it is possible.

Reinforcement learning is used to develop robots, self-driven cars, drones, etc. These reinforcement models can be hijacked and modified and can be distracted from completing their original goals.

Alter Elections predictions

AI can modify the fake news detection systems used during the election to ensure fair elections. People trust these fake news detection systems and thus can be misleading if the detection systems are attacked by AI. Also, stats and opinion polls can be changed which can change the political disclosure. Thus, this adversarial attack can create false trends and alter election results.

Attack on the search engine’s autocomplete functionality

A company or product can be discredited by modifying their search engine’s autocompleting functionality. Attackers change the recommendations one gets when they search something on the search engine. For example, as soon as we write a company’s name, autocomplete function might recommend words like fraud, fake, etc. which might degrade the company’s reputation.

Hijacking home-assistants devices

Attackers can hijack home-assistants that work on voice commands like mobiles, tv, refrigerators by forging the voice of their original user. Attackers also leak forged phone calls involving high profile politicians and celebrities and blackmail them or defame them. This adversarial attack is common and is often experienced.

Alter the company’s AI systems

In this type of adversarial attack, attackers hijack a company’s AI system and leak their customer’s data to other rival companies. Also, data fed on AI systems can be altered that produces faulty trends and stats which might mislead the company. Making strategies on such forged data can lead to serious revenue loss and company defamation.

Adversarial attacks on AI

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