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Behavioral analytics, long associated with threat detection (i.e. UEBA or UBA), is experiencing a renaissance. Once primarily used to identify suspicious activity, it's now being reimagined as a powerful post-detection technology that enhances incident response processes. By leveraging behavioral insights during alert triage and investigation, SOCs can transform their workflows to become more accurate, efficient, and impactful. Fortunately, many new cybersecurity products like AI SOC analysts are able to incorporate these techniques into their investigation capabilities, thus allowing SOCs to utilize them into their response processes. This post will provide a brief overview of behavior analytics then discuss 5 ways it's being reinvented to shake up SOC investigation and incident response work. Behavior Analysis is Back, But Why? Behavioral analytics was a hot topic back in 2015, promising to revolutionize static SIEM and SOC detections with dynamic anomaly detection to uncover t...

Recently the Office of the Director of National Intelligence (ODNI) unveiled a new strategy for open-source intelligence (OSINT) and referred to OSINT as the "INT of first resort". Public and private sector organizations are realizing the value that the discipline can provide but are also finding that the exponential growth of digital data in recent years has overwhelmed many traditional OSINT methods. Thankfully, Artificial Intelligence (AI) and Machine Learning (ML) are starting to provide a transformative impact on the future of information gathering and analysis.  What is Open-Source Intelligence (OSINT)? Open-Source Intelligence refers to the collection and analysis of information from publicly available sources. These sources can include traditional media, social media platforms, academic publications, government reports, and any other data that is openly accessible. The key characteristic of OSINT is that it does not involve covert or clandestine methods of information ga...

Every week seems to bring news of another data breach, and it's no surprise why: securing sensitive data has become harder than ever. And it's not just because companies are dealing with orders of magnitude more data. Data flows and user roles are constantly shifting, and data is stored across multiple technologies and cloud environments. Not to mention, compliance requirements are only getting stricter and more elaborate.  The problem is that while the data landscape has evolved rapidly, the usual strategies for securing that data are stuck in the past. Gone are the days when data lived in predictable places, with access controlled by a chosen few. Today, practically every department in the business needs to use customer data, and AI adoption means huge datasets, and a constant flux of permissions, use cases, and tools. Security teams are struggling to implement effective strategies for securing sensitive data, and a new crop of tools, called data security platforms, have appear...

As we enter 2024, Gcore has released its latest Gcore Radar report, a twice-annual publication in which the company releases internal analytics to track DDoS attacks. Gcore's broad, internationally distributed network of scrubbing centers allows them to follow attack trends over time. Read on to learn about DDoS attack trends for Q3–Q4 of 2023, and what they mean for developing a robust protection strategy in 2024. Gcore's Key Findings DDoS attack trends for the second half of 2023 reveal alarming developments in the scale and sophistication of cyberthreats. Unprecedented Attack Power The past three years have brought about a >100% annual increase in DDoS peak (registered maximum) attack volume: In 2021, the peak capacity of DDoS attacks was  300 Gbps In 2022, it increased to  650 Gbps In Q1–Q2 of 2023, it increased again to  800 Gbps In Q3–Q4 of 2023, it surged to  1600 Gbps  (1.6 Tbps) Notably, the jump in H2 of 2023 means the cybersecurity indu...

Top Story— Facebook has just lost over $60 billion in market value over the past two days—that's more than Tesla's entire market capitalisation and almost three times that of Snapchat. Facebook shares plunge over revelations that personal data of 50 million users was obtained and misused by British data analytics firm ' Cambridge Analytica ,' who reportedly helped Donald Trump win the US presidency in 2016. The privacy scandal that rocked the social media giant was revealed earlier this week when Chris Wylie , the 28-year-old data scientist who worked with a Cambridge University academic, turned into a whistleblower and leaked to the newspapers how poorly Facebook handles people's private information. Wylie claims Cambridge Analytica created " Steve Bannon's psychological warfare mindf**k tool " that profiles citizens to predict their voting patterns based on the personal information gathered from a variety of sources and then helps political ...