Deepfakes and data integrity: understanding the risks and the possible solution
Ever heard of deepfakes? They're like the chameleons of the digital world, blending reality and deception in a way that's seriously concerning.
These days, anyone with a computer and some tech-knowledge can create a deepfake — a video or audio clip that looks and sounds so real, it's hard to tell it's fake. And that's where the trouble starts.
Think about it: with deepfakes, you could make it seem like anyone is saying or doing anything. From spreading fake news to impersonating someone for malicious purposes, the possibilities are downright scary.
Recently, British multinational based in Hong Kong has fallen victim to an unprecedented cyber scam: an employee was deceived by a deepfake video of their chief financial officer, leading them to transfer 25 million dollars. It all began with a suspicious email containing a message from the manager requesting a confidential transaction. Initially wary, the individual suspected phishing, but upon entering a video call, they were reassured. On the screen appeared their colleagues and the same director, requesting 15 transfers to five bank accounts, totaling 25 million dollars.
Instances like these highlight AI's vulnerability to disseminating misinformation, compromising security, and causing mistakes. The increasing risk of AI unintentionally spreading false information and breaching security protocols has become a significant concern. However, decentralized cloud storage solutions offer a potential remedy.
Decentralized cloud storage networks securely store data across multiple centers globally. When coupled with blockchain technology, they provide accessibility, verifiability, traceability, and immutability. Blockchain, a type of Distributed Ledger Technology (DLT), ensures data integrity by enabling the entire network to collaborate effectively.
Proof of provenance helps to alleviate risks associated with AI.
Proof of provenance within the context of decentralized cloud storage and AI is crucial. This involves verifying and documenting the origin, history, and alterations of data throughout its lifecycle, also known as data lineage. By adopting this approach, commonly referred to as proof of provenance, a robust framework is established to uphold the reliability and authenticity of data utilized in AI systems. This not only bolsters accountability and trust in AI-driven processes but also addresses technological and ethical concerns within the AI landscape.
Leveraging blockchain technology for AI presents a promising strategy to safeguard data integrity and mitigate risks associated with centralization. Preserving data integrity in the age of AI is not solely a technological challenge but also an ethical imperative. By maintaining data integrity, we uphold the highest standards of integrity and accountability, ensuring that AI-driven advancements continue to propel progress in a trustworthy and reliable manner. This emphasis on safeguarding data integrity is crucial in averting potential drawbacks from compromised data, thus reinforcing trust in AI-driven advancements.
Data storage in the era of AI: Custody of Digital Goods
As reliance on AI continues to grow, conventional centralized storage methods face vulnerabilities, posing risks of data compromise and manipulation. Companies are grappling with unprecedented costs associated with data breaches, particularly those adhering to traditional models, underscoring the pressing need to update data protection approaches. Notably, a staggering 82% of data breaches analyzed occurred within cloud environments, with 39% affecting multiple. This highlights the necessity for organizations to assert control over data within hybrid cloud settings, prioritizing encryption, stringent data security protocols, and access policies.
In response to these challenges, forward-thinking companies are turning to regulated custodians like Colossus, who offer institutional-grade custody solutions within the blockchain space. By integrating digital custody services into their data management strategies, organizations can enhance security and compliance measures, mitigating the risks associated with centralized storage and bolstering confidence in their AI systems.
Moreover, the concept of asset-tokenization is revolutionizing the web3.0 infrastructure landscape. Through tokenization, built-in functions like the Proof of Provenance which are naturally hereditary on most of the blockchain systems, are automatically implemented into the token built upon the blockchain, and could represent an added value in trust and transparency for customers and investors.
The same goes for many other valuables data which, as we previously said, can be tokenized on blockchain networks. New protocols, foundations, emerging blockchain projects usually implement most of their vital functions embedded into the code of their valuable tokens, thus making professional custody a priority, enabling greater management, safety and accessibility. Colossus as institutional grade custodian, leveraging platforms like Fireblocks and Ledger Enterprise, offers the capability to hold these tokens on more than 15 chains, providing unparalleled flexibility and interoperability for clients.
source data breach - https://vulcan.io/blog/ibm-cost-of-data-breach-2023