{"type":"ScholarlyArticle","title":"DiffStega: Towards Universal Training-Free Coverless Image Steganography with Diffusion Models","authors":[{"name":"Yiwei Yang","slug":"yiwei-yang","given":"Yiwei","family":"Yang","affiliation":"Shanghai Jiao Tong University"},{"name":"Zheyuan Liu","slug":"zheyuan-liu","given":"Zheyuan","family":"Liu","affiliation":"Shanghai Jiao Tong University"},{"name":"Jun Jia","slug":"jun-jia","given":"Jun","family":"Jia","affiliation":"Shanghai Jiao Tong University"},{"name":"Zhongpai Gao","slug":"zhongpai-gao","given":"Zhongpai","family":"Gao","affiliation":"United Imaging Intelligence"},{"name":"Yunhao Li","slug":"yunhao-li","given":"Yunhao","family":"Li","affiliation":"Shanghai Jiao Tong University"},{"name":"Wei Sun","slug":"wei-sun","given":"Wei","family":"Sun","affiliation":"Shanghai Jiao Tong University"},{"name":"Xiaohong Liu","slug":"xiaohong-liu","given":"Xiaohong","family":"Liu","affiliation":"Shanghai Jiao Tong University"},{"name":"Guangtao Zhai","slug":"guangtao-zhai","given":"Guangtao","family":"Zhai","affiliation":"Shanghai Jiao Tong University"}],"abstract":"Traditional image steganography focuses on concealing one image within another, aiming to avoid steganalysis by unauthorized entities. Coverless image steganography (CIS) enhances imperceptibility by not using any cover image. Recent works have utilized text prompts as keys in CIS through diffusion models. However, this approach faces three challenges: invalidated when private prompt is guessed, crafting public prompts for semantic diversity, and the risk of prompt leakage during frequent transmission. To address these issues, we propose DiffStega, an innovative training-free diffusion-based CIS strategy for universal application. DiffStega uses a password-dependent reference image as an image prompt alongside the text, ensuring that only authorized parties can retrieve the hidden information. Furthermore, we develop Noise Flip technique to further secure the steganography against unauthorized decryption. To comprehensively assess our method across general CIS tasks, we create a dataset comprising various image steganography instances. Experiments indicate substantial improvements in our method over existing ones, particularly in aspects of versatility, password sensitivity, and recovery quality. Codes are available at https://github.com/evtricks/DiffStega.","doi":"10.24963/ijcai.2024/175","url":"https://ijcai.org/proceedings/2024/175","pdf":"https://ijcai.org/proceedings/2024/0175.pdf","markdown":"https://ijcai.org/proceedings/2024/175.md","bibtex":"https://ijcai.org/proceedings/2024/bibtex/175","volume":{"slug":"2024","title":"Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2024","url":"https://ijcai.org/proceedings/2024/","year":2024,"location":"Jeju, Korea","dates":"3-9 August 2024","editors":"Kate Larson","isbn":"978-1-956792-04-1","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2024"},"section":"Computer Vision","track":"Main Track","number":175,"pages":{"first":1579,"last":1587},"keywords":["Computer Vision: CV: Structural and model-based approaches, knowledge representation and reasoning","Computer Vision: CV: Machine learning for vision","Computer Vision: CV: Applications"],"videos":[],"references":[{"position":1,"raw":"[AlKhamese et al., 2019] Aya Y AlKhamese, Wafaa R Sha- bana, and Ibrahim M Hanafy. 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