Data privacy and security have become significant concerns in today's digital era, especially with the increasing use of cloud services. Traditionally, encrypted data must be decrypted before processing, posing a potential security risk. Apple is introducing a solution to this problem with the open-source Swift package called swift-homomorphic-encryption. Homomorphic encryption allows computations on encrypted data…
As corporations' use of Artificial Intelligence (AI) increases, so too does their risk of security breaches. Hackers could potentially manipulate AI into revealing crucial corporate or consumer data, a genuine concern for leaders of Fortune 500 companies developing chatbots and other AI applications. Lakera AI, a start-up in the field of GenAI security, addresses this…
The field of software vulnerability detection has seen significant strides thanks to the integration of deep learning models. These models assess code to unearth patterns and irregularities that could point to vulnerabilities. Despite their efficacy, these models are not invulnerable to attacks. In particular, adversarial attacks that manipulate input data to trick the model pose…
When working with AI development, AWS customers often need to restrict outbound and inbound internet traffic due to the sensitive data they work with. Transmitting data across the internet is typically not secure enough for highly sensitive data; hence, accessing AWS services without leaving the AWS network can enhance security. AWS users can enhance the…
Despite remarkable advances in large language models (LLMs) like ChatGPT, Llama2, Vicuna, and Gemini, these platforms often struggle with safety issues. These problems often manifest as the generation of harmful, incorrect, or biased content by these models. The focus of this paper is on a new safety-conscious decoding method, SafeDecoding, that seeks to shield LLMs…