Search Results for author: Giovanni Vigna

Found 7 papers, 4 papers with code

Exploiting Unfair Advantages: Investigating Opportunistic Trading in the NFT Market

no code implementations5 Sep 2023 Priyanka Bose, Dipanjan Das, Fabio Gritti, Nicola Ruaro, Christopher Kruegel, Giovanni Vigna

Yet, there are sophisticated actors who turn their domain knowledge and market inefficiencies to their strategic advantage; thus extracting value from trades not accessible to others.

Invisible Image Watermarks Are Provably Removable Using Generative AI

1 code implementation2 Jun 2023 Xuandong Zhao, Kexun Zhang, Zihao Su, Saastha Vasan, Ilya Grishchenko, Christopher Kruegel, Giovanni Vigna, Yu-Xiang Wang, Lei LI

However, if we do not require the watermarked image to look the same as the original one, watermarks that keep the image semantically similar can be an alternative defense against our attack.

Image Denoising

TrojanPuzzle: Covertly Poisoning Code-Suggestion Models

1 code implementation6 Jan 2023 Hojjat Aghakhani, Wei Dai, Andre Manoel, Xavier Fernandes, Anant Kharkar, Christopher Kruegel, Giovanni Vigna, David Evans, Ben Zorn, Robert Sim

To achieve this, prior attacks explicitly inject the insecure code payload into the training data, making the poison data detectable by static analysis tools that can remove such malicious data from the training set.

Data Poisoning

VenoMave: Targeted Poisoning Against Speech Recognition

1 code implementation21 Oct 2020 Hojjat Aghakhani, Lea Schönherr, Thorsten Eisenhofer, Dorothea Kolossa, Thorsten Holz, Christopher Kruegel, Giovanni Vigna

In a more realistic scenario, when the target audio waveform is played over the air in different rooms, VENOMAVE maintains a success rate of up to 73. 3%.

Automatic Speech Recognition Automatic Speech Recognition (ASR) +3

Bullseye Polytope: A Scalable Clean-Label Poisoning Attack with Improved Transferability

1 code implementation1 May 2020 Hojjat Aghakhani, Dongyu Meng, Yu-Xiang Wang, Christopher Kruegel, Giovanni Vigna

Our attack, Bullseye Polytope, improves the attack success rate of the current state-of-the-art by 26. 75% in end-to-end transfer learning, while increasing attack speed by a factor of 12.

Transfer Learning

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