数据隐私

The new malware SparkKitty is threatening the security of crypto assets on mobile devices.

After months of observation of different mobile operating systems, the well-known security company Kaspersky has discovered new malware SparkKitty is quietly spreading through tampered applications.

This malware is actually an upgraded version of the SparkCat malware from early February this year, and its harmfulness has significantly increased. Attackers first implant malicious code into seemingly normal applications, including cryptocurrency price trackers, instant messaging software, etc. One messaging application named SOEX had surpassed 10,000 downloads before being removed from the app store.

It is worth noting that these infected applications, after obtaining access to user photo album permissions, continuously scan the device's image data, specifically searching for images that may contain cryptocurrency wallet seed phrases. Reports indicate that this malware specifically targets crypto users, particularly in China and Southeast Asia.

The distribution channels for this malware are not limited to crypto-related applications; it also disguises itself as casino programs, adult websites, and even impersonates TikTok applications to spread. Compared to earlier versions, the attack range of SparkKitty has expanded from simple theft of crypto assets to various types of sensitive data, but its core target remains stealing mnemonic phrases for digital wallets.

Security experts particularly warn that this malware has a strong concealment capability; even if users grant photo album permissions, the application will still appear to operate normally on the surface while actually conducting data scans in the background.

In response to this new threat, Kaspersky advises users to never store seed phrases in digital form, including the common but dangerous practice of taking photos of mnemonic phrases. Additionally, users should carefully manage application permissions, especially photo album and file access permissions.

In summary, for users holding digital assets, using hardware wallets or storing mnemonic phrases in paper form offline is the safest storage method. As malware technology evolves, the means of stealing digital assets from mobile devices have become increasingly concealed and complex. Therefore, users must remain highly vigilant and regularly check device permission settings to guard against potential security risks.

#恶意软件 #加密资产安全 #数据隐私

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Why is data security important for#AItraining?
AI requires data provenance for training, and while some data is public and can be used publicly, much of it is the intellectual property of the data provider or individual. The use of this data may require specific licensing or involve compensation. Additionally, workloads may be computationally intensive, which blockchain technology alone cannot provide. ROSE is in a unique position to address these needs through its confidentiality capabilities and framework.
The ROSE team is developing a new product that builds on the consensus layer and the previous success of Sapphire ParaTime, combining them with verifiable off-chain computation, which uses the same underlying cryptography as the ROSE network today. Verifiable off-chain capabilities will address the needs of AI compute-intensive workloads, as well as the data confidentiality and runtime integrity required when using proprietary data in AI training. We believe this is the cornerstone of decentralized AI. #AI幣 #AI模型 #数据隐私 $ROSE

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Oasis Labs announced a collaboration with MetaAI to use its cutting-edge privacy technology to evaluate the fairness of Meta AI models while protecting people's privacy. As a technology partner of Meta, Oasis Labs has built a platform that uses secure multi-party computation (SMPC) to protect information. It is used to explore new uses of emerging Web3 technologies based on blockchain networks. The goal is to provide further global accessibility, audibility, and transparency around the conduct and collection of survey data and its use in measurement.

This is an unprecedented use of these technologies to measure the fairness of AI models at scale in the real world. In this collaboration with Meta, Oasis Labs is committed to building a fairer and more inclusive society, safer artificial intelligence, and responsible data use.
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