Rocco Alfonzetti

The recent wildfires in California have had a devastating impact, both in terms of human life and property damage. While we are all aware of how damaging these natural disasters can be, the fraud implications of these disasters are often overlooked. Wildfires, hurricanes and other natural disasters present opportunities for bad actors to infiltrate and exploit the relaxation of security and the human condition to help. Malicious actors are employing sophisticated phishing tactics to take advantage of the situation. Cybersecurity researchers at Veriti have identified numerous newly registered domains closely linked to the fires. These domains, such as “malibu-firecom” and “fire-reliefcom,” mimic legitimate services, luring unsuspecting victims with promises of fire evacuation assistance, recovery permits, and even fire coverage. Scammers are also attempting to collect money in promise of helping wildfire victims while keeping the funds for themselves, as highlighted in this news article here. FEMA also issued a warning […]

PETs (Privacy Enhancing Technologies) are increasingly vital in today’s digital landscape. PETs are essential for protecting individual rights, fostering trust, ensuring compliance, and supporting ethical practices in an increasingly interconnected world. Laws like GDPR, DORA and CCPA require companies to handle personal data responsibly. And PETs can help organizations comply with these regulations and avoid hefty fines. Besides being required by compliance, PETs also strengthen data protection and, in turn, bolster user trust. Paperclip SAFE aligns with the key tenets of PET, allowing for data to be encrypted during ingestion and keeping it encrypted during use and throughout the entirety of the data lifecycle. There are a number of different PET techniques that are effective.   1. Data Anonymization and Pseudonymization These techniques modify data to remove personally identifiable information (PII) while still allowing for analysis. Anonymization removes all identifiers, while pseudonymization replaces them with fictitious values. Both Privacy solutions […]

The advent of Large Language Models (LLMs) as a foundation of Generative Artificial Intelligence (GenAI) has revolutionized computing as we know it and has become the hottest trend of 2023, rolling into 2024. It offers remarkable capabilities for data analysis, mining, utilization, and other data related computational tasks. However, this technology also harbors significant concern related to the potential for unintentional exposure of sensitive, controlled, and private data such as Personal Identifiable Information (PII) and Protected Health Information (PHI). As a result, the importance of genAI security is expected to rise. LLMs, by their very nature, are trained on massive datasets of text and code, often sourced from databases (unstructured/structured), the internet, or open-access repositories. While these datasets provide a rich source of information for learning, they may also inadvertently contain sensitive PII and PHI, such as names, addresses, Social Security numbers, financial information, and medical records. The viewer may […]