Trading Devil Final: Backdoor attack via Stock market and Bayesian Optimization
Since the advent of generative artificial intelligence, every company and researcher has been rushing to develop their own generative models, whether commercial or not. Given the large number of users of these powerful new tools, there is currently no intrinsically verifiable way to explain from the ground up what happens when LLMs (large language models) learn. For example, those based on automatic speech recognition systems, which have to rely on huge and astronomical amounts of data collected from all over the web to produce fast and efficient results, In this article, we develop a backdoor attack called MarketBackFinal 2.0, based on acoustic data poisoning, MarketBackFinal 2.0 is mainly based on modern stock market models. In order to show the possible vulnerabilities of speech-based transformers that may rely on LLMs.
Code (0)
등록된 구현이 없습니다.
Tasks
Automatic Speech RecognitionBackdoor AttackBayesian OptimizationData Poisoningspeech-recognitionSpeech RecognitionSimilar Papers 제목 키워드 기반
Trading Devil RL: Backdoor attack via Stock market, Bayesian Optimization and Reinforcement Learning
With the rapid development of generative artificial intelligence, particularly large language models a number of sub-fields of deep learning have made significant progress and are now very useful in everyday applications…
Backdoor AttackBayesian OptimizationData Poisoningreinforcement-learning+3Trading Devil: Robust backdoor attack via Stochastic investment models and Bayesian approach
With the growing use of voice-activated systems and speech recognition technologies, the danger of backdoor attacks on audio data has grown significantly. This research looks at a specific type of attack, known as a Stoc…
Backdoor Attackspeech-recognitionSpeech RecognitionRevocable Backdoor for Deep Model Trading
Deep models are being applied in numerous fields and have become a new important digital product. Meanwhile, previous studies have shown that deep models are vulnerable to backdoor attacks, in which compromised models re…
CAT: Concept-level backdoor ATtacks for Concept Bottleneck Models
Despite the transformative impact of deep learning across multiple domains, the inherent opacity of these models has driven the development of Explainable Artificial Intelligence (XAI). Among these efforts, Concept Bottl…
Backdoor AttackExplainable artificial intelligenceExplainable Artificial Intelligence (XAI)Backdoor Attack is a Devil in Federated GAN-based Medical Image Synthesis
Deep Learning-based image synthesis techniques have been applied in healthcare research for generating medical images to support open research. Training generative adversarial neural networks (GAN) usually requires large…
Backdoor AttackData PoisoningFederated LearningImage Generation+2