Welcome to the 2022 ACM Workshop on Information Hiding and Multimedia Security - IH&MMSec '22. The meeting is held at the beautiful University of California, Santa Barbara Campus, with a return to an in-person meeting after 2 years of virtual meetings.
In these challenging times, security and forensics are topics of significant global interest. We would like to thank all the authors who contributed to making this event possible. The meeting was advertised as in-person when the call for papers went out, and we received a total of 38 submissions. After a careful review of the submissions, 18 papers were accepted for presentation, 10 as full length papers and 8 as short papers. The papers cover a broad spectrum of topics ranging from security of multimedia data and machine learning models, data hiding to image/video forensics.
Proceeding Downloads
Towards Generalization in Deepfake Detection
In recent years there have been astonishing advances in AI-based synthetic media generation. Thanks to deep learning-based approaches it is now possible to generate data with a high level of realism. While this opens up new opportunities for the ...
Looking for Signals: A Systems Security Perspective
Over the last 20 years, my students and I have built systems that look for signals of malice in large datasets. These datasets include network traffic, program code, web transactions, and social media posts. For many of our detection systems, we used ...
Intellectual Property (IP) Protection for Deep Learning and Federated Learning Models
This talk focuses on end-to-end protection of the present and emerging Deep Learning (DL) and Federated Learning (FL) models. On the one hand, DL and FL models are usually trained by allocating significant computational resources to process massive ...
FMFCC-V: An Asian Large-Scale Challenging Dataset for DeepFake Detection
The abuse of DeepFake technique has raised enormous public concerns in recent years. Currently, the existing DeepFake datasets suffer some weaknesses of obvious visual artifacts, minimal Asian proportion, backward synthesis methods and short video ...
Know Your Library: How the libjpeg Version Influences Compression and Decompression Results
Introduced in 1991, libjpeg has become a well-established library for processing JPEG images. Many libraries in high-level languages use libjpeg under the hood. So far, little attention has been paid to the fact that different versions of the library ...
Identity-Referenced Deepfake Detection with Contrastive Learning
With current advancements in deep learning technology, it is becoming easier to create high-quality face forgery videos, causing concerns about the misuse of deepfake technology. In recent years, research on deepfake detection has become a popular ...
Sparse Trigger Pattern Guided Deep Learning Model Watermarking
Watermarking neural networks (NNs) for ownership protection has received considerable attention recently. Resisting both model pruning and fine-tuning is commonly considered to evaluate the robustness of a watermarked NN. However, the rationale behind ...
BlindSpot: Watermarking Through Fairness
With the increasing development of machine learning models in daily businesses, a strong need for intellectual property protection arised. For this purpose, current works suggest to leverage backdoor techniques to embed a watermark into the model, by ...
Hiding Needles in a Haystack: Towards Constructing Neural Networks that Evade Verification
Machine learning models are vulnerable to adversarial attacks, where a small, invisible, malicious perturbation of the input changes the predicted label. A large area of research is concerned with verification techniques that attempt to decide whether a ...
Covert Communications through Imperfect Cancellation
We propose a method for covert communications using an IEEE 802.11 OFDM/QAM packet as a carrier. We show how to hide the covert message so that the transmitted signal does not violate the spectral mask specified by the standard, and we determine its ...
Covert Channels in Network Time Security
Network Time Security (NTS) specified in RFC8915 is a mechanism to provide cryptographic security for clock synchronization using the Network Time Protocol (NTP) as foundation. By using Transport Layer Security (TLS) and Authenticated Encryption with ...
Collusion-resistant Fingerprinting of Parallel Content Channels
The fingerprinting game is analysed when the coalition size k is known to the tracer, but the colluders can distribute themselves across L TV channels. The collusion channel is introduced and the extra degrees of freedom for the coalition are made ...
Domain Adaptational Text Steganalysis Based on Transductive Learning
Traditional text steganalysis methods rely on a large amount of labeled data. At the same time, the test data should be independent and identically distributed with the training data. However, in practice, a large number of text types make it difficult ...
Few-shot Text Steganalysis Based on Attentional Meta-learner
Text steganalysis is a technique to distinguish between steganographic text and normal text via statistical features. Current state-of-the-art text steganalysis models have two limitations. First, they need sufficient amounts of labeled data for ...
Hidden in Plain Sight - Persistent Alternative Mass Storage Data Streams as a Means for Data Hiding With the Help of UEFI NVRAM and Implications for IT Forensics
This article presents a first study on the possibility of hiding data using the UEFI NVRAM of today's computer systems as a storage channel. Embedding and extraction of executable data as well as media data are discussed and demonstrated as a proof of ...
Fighting the Reverse JPEG Compatibility Attack: Pick your Side
In this work we aim to design a steganographic scheme undetectable by the Reverse JPEG Compatibility Attack (RJCA). The RJCA, while only effective for JPEG images compressed with quality factors 99 and 100, was shown to work mainly due to change in ...
A Nearest Neighbor Under-sampling Strategy for Vertical Federated Learning in Financial Domain
Machine learning techniques have been widely applied in modern financial activities. Participants in the field are aware of the importance of data privacy. Vertical federated learning (VFL) was proposed as a solution to multi-party secure computation ...
Colmade: Collaborative Masking in Auditable Decryption for BFV-based Homomorphic Encryption
This paper proposes a novel collaborative decryption protocol for the Brakerski-Fan-Vercauteren (BFV) homomorphic encryption scheme in a multiparty distributed setting, and puts it to use in designing a leakage-resilient biometric identification ...
AMR Steganalysis based on Adversarial Bi-GRU and Data Distillation
Existing AMR (Adaptive Multi-Rate) steganalysis algorithms based on pitch delay have low detection accuracy on samples with short time or low embedding rate, and the model shows fragility under the attack of adversarial samples. To solve this problem, ...
Capacity Laws for Steganography in a Crowd
A steganographer is not only hiding a payload inside their cover, they are also hiding themselves amongst the non-steganographers. In this paper we study asymptotic rates of growth for steganographic data -- analogous to the classical Square-Root Law -- ...
Detector-Informed Batch Steganography and Pooled Steganalysis
We study the problem of batch steganography when the senders use feedback from a steganography detector. This brings an additional level of complexity to the table due to the highly non-linear and non-Gaussian response of modern steganalysis detectors ...
Index Terms
- Proceedings of the 2022 ACM Workshop on Information Hiding and Multimedia Security
Recommendations
Acceptance Rates
Year | Submitted | Accepted | Rate |
---|---|---|---|
IH&MMSec '18 | 40 | 18 | 45% |
IH&MMSec '17 | 34 | 18 | 53% |
IH&MMSec '16 | 61 | 21 | 34% |
IH&MMSec '15 | 45 | 20 | 44% |
IH&MMSec '14 | 64 | 24 | 38% |
IH&MMSec '13 | 74 | 27 | 36% |
Overall | 318 | 128 | 40% |