April 30, 2024
Kannan Subbiah
FCA | CISA | CGEIT | CCISO | GRC Consulting | Independent Director | Enterprise & Solution Architecture | Former Sr. VP & CTO of MF Utilities | BU Soft Tech | itTrident
The chief data officer is tasked not only with unlocking the value of data but explaining the importance of data as the lifeblood of the company across all levels. They must be effective storytellers who can interpret data in such a way that business stakeholders take notice. An effective CDO pairs storytelling with the supporting data and makes it easy to share insights with stakeholders and get their buy-in. For instance, how effective a CDO is in getting departmental buy-in might boil down to the ongoing department "showback reports" they can produce. "Credibility and integrity are two other important traits in addition to effective communication skills, as it is crucial for the CDO to gain the trust of their peers," Subramanian says. ... To garner support for data initiatives and drive organizational buy-in, chief data officers must be able to communicate complex data concepts in a clear and compelling manner to diverse stakeholders, including executives, business leaders, and technical teams. "CDOs have to serve as a bridge between the tech and operational aspects of the organization as they work to drive business value and increase data literacy and awareness," says Schwenk.
The task of cracking much current online security boils down to the mathematical problem of finding two numbers that, when multiplied together, produce a third number. You can think of this third number as a key that unlocks the secret information. As this number gets bigger, the amount of time it takes an ordinary computer to solve the problem becomes longer than our lifetimes. Future quantum computers, however, should be able to crack these codes much more quickly. So the race is on to find new encryption algorithms that can stand up to a quantum attack. ... Most lattice-based cryptography is based on a seemingly simple question: if you hide a secret point in such a lattice, how long will it take someone else to find the secret location starting from some other point? This game of hide and seek can underpin many ways to make data more secure. A variant of the lattice problem called “learning with errors” is considered to be too hard to break even on a quantum computer. As the size of the lattice grows, the amount of time it takes to solve is believed to increase exponentially, even for a quantum computer.
The connected-device law kicks in following repeat attacks against devices with known or easily guessable passwords, which have led to repeat distributed denial-of-service attacks that have affected major institutions, including the BBC as well as major U.K. banks such as Lloyds and the Royal Bank of Scotland. Officials said the law is designed not just for consumer protection but also to improve national cybersecurity resilience, including against malware that targets IoT devices, such as Mirai and its spinoffs, all of which can exploit default passwords in devices. Western officials have also warned that Chinese and Russian nation-state hacking groups exploit known vulnerabilities in consumer-grade network devices. U.S. authorities earlier this year disrupted a Chinese botnet used by a group tracked as Volt Typhoon, warning that Beijing threat actors used infected small office and home office routers to cloak their hacking activities. "It's encouraging to see growing emphasis on implementing best practices in securing IoT devices before they leave the factory," said Kevin Curran, a professor of cybersecurity at Ulster University in Northern Ireland.
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“The risks of AI are real, but they are manageable when thoughtful governance practices are in place as enablers, not obstacles, to responsible innovation,” Dev Stahlkopf, Cisco’s executive VP and chief legal officer, said in the report. One of the big potential ways to benefit from privacy-preserving technology is enabling multiple parties to share their most valuable and sensitive data, but do so in a privacy-preserving manner. “My data alone is good,” Hughes said. “My data plus your data is better, because you have indicators that I might not see, and vice versa. Now our models are smarter as a result.” Carmakers could benefit by using privacy-preserving technology to combine sensor data collected from engines. “I’m Mercedes. You’re Rolls-Royce. Wouldn’t it be great if we combined our engine data to be able to build a model on top of that could identify and predict maintenance schedules better and therefore recommend a better maintenance schedule?” Hughes said. Privacy-preserving tech could also improve public health through the creation of precision medicine techniques or new medications.?
The basis for graph computing is the property graph, which is superior in describing dynamically changing data. Graph databases have been widely used for decades, and only recently, the form has generated new interest in being a pivotal component in Large Language Model-based Generative AI apps. A graph model can visualize complex, interconnected systems. The downside of LLMs is that they are black boxes of a sort, Rathle explained. “There’s no way to understand the reasoning behind the language model. It is just following a neural network and doing it’s doing its thing,” he said. A knowledge graph can serve as external memory, a way to visualize how the LLM constructed its worldview. “So I can trace through the graph and see why it arrived with that answer,” Rathle said. Graph databases are also widely used in the health care companies for drug discovery and by aircraft and other manufacturers as a way to visualize complex system design, Rathle said. “You have all these cascading dependencies and that calculation works really well in the graph,” Rathle said.?
One of the major promises is a reduction in the fraud that often occurs around clinical trials. Bad actors have a vested interest in whether the drug will pass FDA inspections – literally. In other words, falsified results and insider trading is a big risk. Applying AI-powered security to their operational technology in the manufacturing plant or lab can monitor the equipment and not only detect signs of failure, but alert the company to potential tampering. At the same time, they’re also looking at ways to improve drug and polymer research. “They build better products and shorten the cycle of go-to-market for drugs. That’s worth billions of dollars,” he said. “They have a patent that only lasts 10 years. If they can get to market faster, they can hold on to that market share more before it goes to the public.” But that transformation of the SOC is potentially the most impactful of use cases, especially as cybercriminals adopt generative AI and go to work without the guardrails that encumber organizations. “We’ve seen a dramatic adoption of what I would call open-source AI from attackers to be able to use and build models,” Bissell said.?