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At Stobaugh Group, We also specialize in Prompt Engineering and VAPT for artificial intelligence (AI) systems, Large Language Models, etc. As AI technology continues to evolve and become more integrated into our daily lives, it's crucial to ensure that these systems are secure and can be trusted to perform their intended functions without compromising the privacy or safety of individuals and/or organizations.
We use unique and ever evolving techniques to analyze and test LLM & AI systems, identify potential weaknesses, and develop solutions to mitigate any security risks. We also work closely with clients to understand their specific security needs and provide customized recommendations and solutions to ensure the integrity and safety of their AI implementations.
why security research into a.i. is so critical
why security research into a.i. is so critical
Continued Security Research into AI, natural language processing technologies & LLM's is massively crucial to our future security because they are becoming increasingly integrated into our daily lives. These technologies have the potential to revolutionize industries and improve our quality of life, but they also come with new security risks and vulnerabilities.
Bad guys are constantly looking for ways to exploit these new technologies and gain unauthorized access to sensitive information, manipulate etc - Without proper security measures and ongoing research, these technologies can be used to spread disinformation, launch cyber attacks, violate privacy & human rights among much more.
Conducting security research on these developing technologies allows us to identify and mitigate potential vulnerabilities and protect against emerging threats. This helps to ensure that these technologies are used safely and responsibly and that they can continue to benefit society without putting individuals or organizations at risk.
Here are just a handful of examples of examples in which AI systems can be used nefariously:
Adversarial attacks on image recognition: Researchers have shown that by making small changes to an image, such as adding imperceptible noise, an AI system can be tricked into misclassifying the image. This can be used to deceive security systems that rely on image recognition, such as facial recognition systems.
Voice recognition attacks: AI systems that rely on voice recognition can also be hacked by attackers who use recorded or synthesized voices to trick the system into accepting unauthorized commands.
Autonomous vehicle hacks: Autonomous vehicles use AI systems to make decisions and navigate the environment. Hackers could potentially manipulate the AI systems to cause accidents or take control of the vehicle.
Spam and phishing attacks: AI systems can be used to generate large volumes of spam and phishing messages that are tailored to individual recipients, making them more convincing and harder to detect.
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