Evading Watermark based Detection of AI-Generated Content

A generative AI model can generate extremely realistic-looking content, posing growing challenges to the authenticity of information. To address the challenges, watermark has been leveraged to detect AI-generated content. Specifically, a watermark is embedded into an AI-generated content before it is released. A content is detected as AI-generated if a similar watermark can be decoded from it. In this work, we perform a systematic study on the robustness of such watermark-based AI-generated content detection. We focus on AI-generated images. Our work shows that an attacker can post-process a watermarked image via adding a small, human-imperceptible perturbation to it, such that the post-processed image evades detection while maintaining its visual quality. We show the effectiveness of our attack both theoretically and empirically. Moreover, to evade detection, our adversarial post-processing method adds much smaller perturbations to AI-generated images and thus better maintain their visual quality than existing popular post-processing methods such as JPEG compression, Gaussian blur, and Brightness/Contrast. Our work shows the insufficiency of existing watermark-based detection of AI-generated content, highlighting the urgent needs of new methods. Our code is publicly available: https://github.com/zhengyuan-jiang/WEvade.Comment: To appear in ACM Conference on Computer and Communications Security (CCS), 202

Staggered-Grid Finite Difference Method with Variable-Order Accuracy for Porous Media

The numerical modeling of wave field in porous media generally requires more computation time than that of acoustic or elastic media. Usually used finite difference methods adopt finite difference operators with fixed-order accuracy to calculate space derivatives for a heterogeneous medium. A finite difference scheme with variable-order accuracy for acoustic wave equation has been proposed to reduce the computation time. In this paper, we develop this scheme for wave equations in porous media based on dispersion relation with high-order staggered-grid finite difference (SFD) method. High-order finite difference operators are adopted for low-velocity regions, and low-order finite difference operators are adopted for high-velocity regions. Dispersion analysis and modeling results demonstrate that the proposed SFD method can decrease computational costs without reducing accuracy

Where have you been? A Study of Privacy Risk for Point-of-Interest Recommendation

As location-based services (LBS) have grown in popularity, the collection of human mobility data has become increasingly extensive to build machine learning (ML) models offering enhanced convenience to LBS users. However, the convenience comes with the risk of privacy leakage since this type of data might contain sensitive information related to user identities, such as home/work locations. Prior work focuses on protecting mobility data privacy during transmission or prior to release, lacking the privacy risk evaluation of mobility data-based ML models. To better understand and quantify the privacy leakage in mobility data-based ML models, we design a privacy attack suite containing data extraction and membership inference attacks tailored for point-of-interest (POI) recommendation models, one of the most widely used mobility data-based ML models. These attacks in our attack suite assume different adversary knowledge and aim to extract different types of sensitive information from mobility data, providing a holistic privacy risk assessment for POI recommendation models. Our experimental evaluation using two real-world mobility datasets demonstrates that current POI recommendation models are vulnerable to our attacks. We also present unique findings to understand what types of mobility data are more susceptible to privacy attacks. Finally, we evaluate defenses against these attacks and highlight future directions and challenges.Comment: 26 page

A new species of Petta (Annelida, Pectinariidae), with comments on Petta assimilis McIntosh, 1885

The genus Petta Malmgren, 1866 is a small and poorly known genus of the annelid family Pectinariidae Quatrefages, 1866. A previous revision of the genus found that the type material of the species P. assimilis McIntosh, 1885 had been lost. While searching for material from the type locality, we were able to examine material from a similar area but collected in much shallower water from off South Africa which represents another undescribed species of Petta. The new species, Petta brevis sp. nov., is described and compared to P. assimilis McIntosh, 1885, and a revised key to all species in the genus is provided

Time Domain Waveform Inversion for the Q Model Based on the First-Order Viscoacoustic Wave Equations

Propagating seismic waves are dispersed and attenuated in the subsurface due to the conversion of elastic energy into heat. The absorptive property of a medium can be described by the quality factor Q. In this study, the first-order pressure-velocity viscoacoustic wave equations based on the standard linear solid model are used to incorporate the effect of Q. For the Q model inversion, an iterative procedure is then proposed by minimizing an objective function that measures the misfit energy between the observed data and the modeled data. The adjoint method is applied to derive the gradients of the objective function with respect to the model parameters, that is, bulk modulus, density, and Q-related parameter τ. Numerical tests on the crosswell recording geometry indicate the feasibility of the proposed approach for the Q anomaly estimation

Finding an Appropriate Means of Internal Marketing under Differing Cultural Circumstances : a Case Study of Swedbank (Sweden) & Minsheng Bank (China)

Research Objects: we choose two banks as research objects. One is a Swedish bank, Swedbank, which was founded in 1820, the other is a Chinese bank, Minsheng Bank (CMBC), which is a new bank when compared with Swedbank. Purpose & Aim: The 2008 financial crisis hurt banks badly, and consequently how they can become stronger to resist future crises and gain competitive advantages is a key topic for them. There is no doubt that there are many factors that makes a bank successful, but employees are one of the most important factors in a service industry. Therefore, this research study is focused on internal marketing in banks. In addition, this study will attempt to assess whether two banks can learn from each other through the comparison of their internal marketing efforts. Research Methodology: this study will rely on the data collected from the interviews with a manager and an employee from two banks. Books and articles are also been used for secondary data collection. Findings & Conclusion: The research revealed that Swedbank tend to do a better job in satisfying employees' needs, sharing value, having an appropriate organisational culture and being more conscious to treat the employees as customers, in comparison with CMBC. While CMBC need to make more effort in this regard, it does not mean that they must copy what Swedbank do, but rather to establish an appropriate organisational culture for their own internal market. Contribution & Suggestion: In the end, the suggestions have been listed for both banks to improve their internal marketing programme