Deep packet inspection | Breaking Cybersecurity News | The Hacker News

Today, most Network Detection and Response (NDR) solutions rely on traffic mirroring and Deep Packet Inspection (DPI). Traffic mirroring is typically deployed on a single-core switch to provide a copy of the network traffic to a sensor that uses DPI to thoroughly analyze the payload. While this approach provides detailed analysis, it requires large amounts of processing power and is blind when it comes to encrypted network traffic. Metadata Analysis has been specifically developed to overcome these limitations. By utilizing metadata for analysis, network communications can be observed at any collection point and be enriched by the information providing insights about encrypted communication. Network Detection and Response (NDR) solutions have become crucial to reliably monitor and protect network operations. However, as network traffic becomes encrypted and data volumes continue to increase, most traditional NDR solutions are reaching their limits. This begs the question: What detect

Governments in Turkey and Syria have been caught hijacking local internet users' connections to secretly inject surveillance malware, while the same mass interception technology has been found secretly injecting browser-based cryptocurrency mining scripts into users' web traffic in Egypt. Governments, or agencies linked to it, and ISPs in the three countries are using Deep Packet Inspection technology from Sandvine (which merged with Procera Networks last year), to intercept and alter Internet users' web traffic. Deep packet inspection technology allows ISPs to prioritize, degrade, block, inject, and log various types of Internet traffic, in other words, they can analyze each packet in order to see what you are doing online. According to a new report by Citizen Lab, Turkey's Telecom network was using Sandvine PacketLogic devices to redirect hundreds of targeted users (journalists, lawyers, and human rights defenders) to malicious versions of legitimate progra

Imagine a world where the software that powers your favorite apps, secures your online transactions, and keeps your digital life could be outsmarted and taken over by a cleverly disguised piece of code. This isn't a plot from the latest cyber-thriller; it's actually been a reality for years now. How this will change – in a positive or negative direction – as artificial intelligence (AI) takes on a larger role in software development is one of the big uncertainties related to this brave new world. In an era where AI promises to revolutionize how we live and work, the conversation about its security implications cannot be sidelined. As we increasingly rely on AI for tasks ranging from mundane to mission-critical, the question is no longer just, "Can AI  boost cybersecurity ?" (sure!), but also "Can AI  be hacked? " (yes!), "Can one use AI  to hack? " (of course!), and "Will AI  produce secure software ?" (well…). This thought leadership article is about the latter. Cydrill  (a