A quote by Richard Clarke, the United States’ former cybersecurity czar, serves as a stark warning: “If you’re spending more on coffee than on IT security, you will be hacked. What’s more, you deserve to be hacked.”
This statement highlights the critical importance of data security, which is often overlooked by individuals and organizations alike. Data security is paramount for both businesses and users, as it ensures the reliability and privacy of financial information, health data, and job prospects. However, in the age of data dominance, there is a significant risk of sensitive information being leaked, potentially affecting hundreds of millions or even billions of people.
The digital revolution has led to an exponential increase in the amount of information circulating worldwide. Consequently, the number of data breaches has also increased, as malicious actors exploit personal and confidential information. Several high-profile cases illustrate the severity of the problem. In June 2021, LinkedIn suffered a data breach that exposed the details of 700 million users, including phone numbers, email addresses, geolocation records, and gender. Marriott International acknowledged that hackers had accessed the personal data of half a million guests in September 2018 . The incident involved unauthorized access to the Starwood guest reservation database dating back to 2014. In November 2018, hackers copied and encrypted data, including email addresses, passport numbers, booking dates, and phone numbers. However, Marriott managed to decrypt the data and resolve the global issue.
These incidents emphasize the importance of investing in the development and implementation of innovative AI-based tools to ensure data and crypto asset protection in the future. Governments, private companies, and research institutions must collaborate to stimulate innovation in this space. The digital society is creating AI-based solutions that will provide transparency and protection for users, companies, and organizations. Some of these solutions include:
Biometric authentication: this process involves analyzing user behavior patterns to create cyber fingerprints, keystroke dynamics, and personal typing patterns. Several startups are actively using biometric authentication, such as [Behaviosec](These incidents emphasize the importance of investing in the development and implementation of innovative AI-based tools to ensure data and crypto asset protection in the future. Governments, private companies, and research institutions must collaborate to stimulate innovation in this space. The digital society is creating AI-based solutions that will provide transparency and protection for users, companies, and organizations. Some of these solutions include:
Biometric authentication: this process involves analyzing user behavior patterns to create cyber fingerprints, keystroke dynamics, and personal typing patterns. Several startups are actively using biometric authentication, such as Behaviosec, which analyzes users’ typing rhythm, and Bionym’s Nymi bracelet, which authenticates users based on their heartbeat. Mastercard even implemented this technology to allow customers to make payments.
Blockchain-based encryption: this method uses a special structural model that contains raw data obtained from the supplier and a hash code stored in the blockchain. The raw data is fed to the AI, compared to the hash code, and if there are any discrepancies, it allows the supplier to be tracked and identified as malicious or not. CertiK actively uses this encryption method. Core Scientific integrates personalized blockchain and AI infrastructure with current business networks, updating the physical structure of businesses, servers, and software.), which analyzes users’ typing rhythm, and Bionym’s Nymi bracelet, which authenticates users based on their heartbeat. Mastercard even implemented this technology to allow customers to make payments.
Anomaly detection: specific algorithms can be used to identify problems. For example, LOF (Local Outlier Factor) investigates the local density of data points. SVM (Support Vector Machines) aims to divide data points into classes using hyperplanes in a multidimensional space. As a result, the machine model learns to recognize “data point norms” and assess whether these points are “familiar” with the integrity policy. The LeewayHertz generative platform is based on algorithms that detect anomalies.
Autoencoders: these use artificial neural networks to encode data, compressing its size. The data is then decoded and presented to the company with a complete analysis to identify potential threats, as viso.ai demonstrates.
AI for crypto assets: in the digital age, cybersecurity is becoming increasingly important for investors. Outdated, centralized systems used by traditional asset management companies are vulnerable to cyberattacks. ATPBot offers an innovative solution that takes data security to the next level through alternative encryption methods and cryptographic protocols. Web3 authorization and Web3 deposits are highly relevant, aimed at increasing trust among clients, primarily cryptocurrency exchanges such as WhiteBIT, Kraken, Bybit, and many others.
Conclusion
It is clear that our present must be focused on securing our data and its integrity. Losing even partial access to this chain can result in the loss of not only reputation but also personal funds. By investing in AI-powered cybersecurity solutions, we can build a more secure and resilient digital future for everyone. Data security is crucial in today’s digital world, where breaches can expose sensitive information to millions. AI-powered solutions offer promising ways to combat this growing threat.
Governments, businesses, and researchers need to collaborate on developing AI tools for data protection. These solutions include biometric authentication, blockchain encryption, anomaly detection algorithms, and autoencoders for threat identification.
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