As organizations begin planning their security strategies for 2024, now is the time to look back on the year before and extrapolate what the future may hold.
The impact of the many new uses for GenAI rippled the cybersecurity world and was a top topic and cybersecurity concern, with a data breach of ChatGPT highlighting the risk.
On the good news front, the U.S. government issued the NIST Cybersecurity Framework 2.0 and the White House Cybersecurity plan took steps to protect critical infrastructure from cyberattacks.
Until now, cyber criminals have been very limited in how they can monetize from their data spoils collected from the billions of data compromised over the years.
All that's about to change thanks to GenAI. GenAI is going to help filter through, correlate and categorize those huge data sets in minutes and put them together in a programmatic way for cyber criminals to create profiles for potential targets.
Security and password hygiene have never been more important.
While we anticipate a bigger pivot to high-pressure data extortion attacks, ransomware isn't going anywhere, as we expect it to shift focus to a consumer or small business target base where threat actors' leverage remains strong.
Generative AI adoption will force CISOs to focus on critical data.
With enterprises beginning to embed GenAI into their infrastructure, they're dealing with new risks introduced by centralizing various types of data into AI models, various stakeholders accessing those models and data they're ingesting, as well as the actual inference and live use of the model.
This risk will drive CISOs to redefine what data can introduce an existential threat to the organization if compromised and reassess the security and access controls surrounding it.
Data security, protection and privacy measures are the linchpin to the success of an AI-driven business model.
With data becoming more dynamic and active across the environment, the discovery, classification and prioritization of critical data will be a top action for security leaders in 2024.
Companies have been using AI and machine learning to improve the efficacy of security technologies for years, and the introduction of generative AI will be aimed squarely at maximizing the human element of security.
In this coming year, GenAI will begin to take on certain tedious, administrative tasks on behalf of security teams - but beyond this, it will also enable less experienced team members to take on more challenging, higher-level tasks.
We'll see GenAI being used to translate technical content, such as machine-generated log data or analysis output, into simplified language that is more understandable and actionable for novice users.
As AI crosses a new threshold, security predictions at scale are becoming more tangible.
Although early security use cases of generative AI focus on the front end, improving security analysts' productivity, I don't think we're far from seeing generative AI deliver a transformative impact on the back end to completely reimagine threat detection and response into threat prediction and protection.
The goal is to create a less complex environment where consistent security authentication flows and visibility can be enforced.
Quantum system performance continues to scale closer to the point of being cryptographically relevant, with studies conducted by World Economic Forum, National Security memorandums and timelines published by CNSA suggesting quantum computers could have the ability to break the most widely used security protocols in the world by as early as the 2030s.
In anticipation of this, organizations should start the process today of identifying cryptography used in their environments to prepare for the transition to quantum-safe cryptography to ensure their data and systems remain protected from threats posed by quantum decryption.
This Cyber News was published on securityintelligence.com. Publication date: Tue, 09 Jan 2024 14:43:04 +0000