Project Watershed 250 deploys AI security and cybersecurity tools to protect Texas water systems from cyberattacks in a pilot program the Trump administration plans to scale nationwide.

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Here's why AI agents lie and cheat to reach their goals When two OpenAI models hacked into Hugging Face last month, they weren't trying to make money or commit sabotage--they were just looking for answers to a test question. According to OpenAI, the models decided to solve a cybersecurity exercise by hacking out of the environment in which OpenAI had attempted to contain them and into Hugging Face's databases, where--they reasoned--the correct answer to the problem might be stored. The incident has attracted intense attention over the past couple of weeks. It's a dramatic illustration of just how good AI models have gotten at hacking. But it's perhaps even more striking as an example of how and why AI systems lie and cheat. Read our story explaining why AI engages in this sort of behavior--known as "reward hacking."

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They're the government body behind the dreaded hosepipe bans. But the Environment Agency have come up with another way to save water – by deleting old emails. Historic messages and photos are stored in vast data centres which consume so much energy they require large amounts of water to keep cool. Now, the public is being urged to'play their part' to help reduce pressure on our water systems by having an email clear–out. The advice was issued as Britain endures its fourth heatwave of the summer. Five areas of England are currently officially in drought, with six more in'prolonged dry weather'.

Uber Eats uses four-wheeled robots to handle the final stretch of food delivery. Fixing underground water pipes usually means digging up roads and sidewalks -- a process that's disruptive and expensive. However, researchers at the University of Sheffield in the U.K. are working on a different approach. They've developed small robots called "Pipebots" that can travel inside water pipes to find and potentially repair leaks, all without any excavation. Sign up for my FREE CyberGuy Report Get my best tech tips, urgent security alerts, and exclusive deals delivered straight to your inbox.

--Digital twins (DTs) help improve real-time monitoring and decision-making in water distribution systems. However, their connectivity makes them easy targets for cyberattacks such as scanning, denial-of-service (DoS), and unauthorized access. Small and medium-sized enterprises (SMEs) that manage these systems often do not have enough budget or staff to build strong cybersecurity teams. T o solve this problem, we present a Virtual Cybersecurity Department (VCD), an affordable and automated framework designed for SMEs. The VCD uses open-source tools like Zabbix for real-time monitoring, Suricata for network intrusion detection, Fail2Ban to block repeated login attempts, and simple firewall settings. T o improve threat detection, we also add a machine-learning-based IDS trained on the OD-IDS2022 dataset using an improved ensemble model. Our solution gives SMEs a practical and efficient way to secure water systems using low-cost and easy-to-manage tools.

Enhancing Network Security Management in Water Systems using FM-based Attack Attribution Aleksandar Avdalovi c, Joseph Khoury, Ahmad Taha, Elias Bou-Harb Division of Computer Science and Engineering, Louisiana State University, USA Civil and Environmental Engineering, V anderbilt University, USA Abstract --Water systems are vital components of modern infrastructure, yet they are increasingly susceptible to sophisticated cyber attacks with potentially dire consequences on public health and safety. While state-of-the-art machine learning techniques effectively detect anomalies, contemporary model-agnostic attack attribution methods using LIME, SHAP, and LEMNA are deemed impractical for large-scale, interdependent water systems. This is due to the intricate interconnectivity and dynamic interactions that define these complex environments. Such methods primarily emphasize individual feature importance while falling short of addressing the crucial sensor-actuator interactions in water systems, which limits their effectiveness in identifying root cause attacks. T o this end, we propose a novel model-agnostic Factorization Machines (FM)-based approach that capitalizes on water system sensor-actuator interactions to provide granular explanations and attributions for cyber attacks. For instance, an anomaly in an actuator pump activity can be attributed to a top root cause attack candidates, a list of water pressure sensors, which is derived from the underlying linear and quadratic effects captured by our approach. In multi-feature cyber attack scenarios involving intricate sensor-actuator interactions, our FM-based attack attribution method effectively ranks attack root causes, achieving approximately 20% average improvement over SHAP and LEMNA. Additionally, our approach maintains strong performance in single-feature attack scenarios, demonstrating versatility across different types of cyber attacks. Notably, our approach maintains a low computational overhead equating to an O(n) time complexity, making it suitable for real-time applications in critical water system infrastructure. Our work underscores the importance of modeling feature interactions in water systems, offering a robust tool for operators to diagnose and mitigate root cause attacks more effectively. I NTRODUCTION W ATER systems at the physical layer comprise critical components such as flow and pressure sensors, and actuators, which are monitored and controlled by cyber layer systems to ensure a safe and reliable water supply for both communities and industries.

A Japanese government panel agreed Thursday to promote digital transformation to tackle the aging of public infrastructure, including water supply and sewage systems. This followed a high-profile road collapse incident in Yashio, Saitama Prefecture, last month, which is believed to have been caused by a broken sewage pipe. At a meeting of the digital administrative and fiscal reform panel, Prime Minister Shigeru Ishiba, who heads the group, instructed related officials to urgently work on the use of digital technologies for water and sewage systems to ensure that their operations by local governments are sustainable. He called for introducing such technologies within about three years, against the previous deadline of five years. For water and sewage systems, satellites and artificial intelligence systems will be used to collect and analyze data on temperature, geology and other factors to identify areas where water leaks may occur.