Hacking with Artificial Intelligence

Hacking with Artificial Intelligence

Artificial intelligence (AI) have entered the everyone’s life, and we can see many AI-related products everywhere, such as Siri, AI camera, AI photoshop tool, and etc. It refers to the creation and application of algorithms to build dynamic computing environments in order to simulate the foundations of human intelligence processes. In other word, the goal of artificial intelligence is to make computers think and act like humans. AI is such a helpful tool to improve our lives and work though, do you know what we would experience when it is applied in cyberattacks?

According to SC Media,

“The amplified efficiency of AI means that, once a system is trained and deployed, malicious AI can attack a far greater number of devices and networks more quickly and cheaply than a malevolent human actor. Given sufficient computing power, an AI system can launch many attacks, be more selective in its targets and more devastating in its impact.”

There is no doubt that AI will be used by attackers to conduct the malicious utilization and drive the next major upgrade in cyber weaponry! The Emotet trojan, a contemporary malware, is a prime example of an AI cyberattack. Based on the existed AI cyberattacks, we can summarize that there are three types of attacks using AI so far:

• AI-boosted/based Cyberattacks:
The irregular user and system activity patterns can be figured out by AI algorithms and repurposed for attacks that are determined by AI prediction model. Example: DeepLocker, an encrypted ransomware decrypting and leasing based on a face recognition algorithm.

• AI-facilitated Cyberattacks:
AI is used mostly in the attacker’s environment though, AI algorithms is not applied in the malicious code and the malware running on the victim’s machine. Example: Info-stealer, a spyware without AI algorithms uploading personal information to the C&C server. Then the uploaded information would be clustered and classified as interesting based on Natural Language Processing (NLP) algorithms.

• Adversarial Attacks:
Malicious AI algorithms is used to damage the benign AI algorithms by using the algorithms and techniques that are built into a traditional machine learning algorithm. Through reverse engineering the algorithm, the benign AI algorithms could be broken by the malicious AI algorithms.


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