Singapore's Health Sciences Authority has approved the use of an artificial intelligence-powered (AI) software for the automated analysis and reporting of vascular ultrasound scans. Developed by See-Mode Technologies, the application taps deep learning, text recognition, and signal processing technologies with the aim of helping clinicians interpret such images -- a task that typically is performed manually, time-consuming, and error-prone. Such scans, used for patients with cardiovascular or heart diseases, are commonly analysed by a sonographer or radiologist who has to manually review between 50 and 150 images for each patient, according to See-Mode. No system is infallible and cybersecurity breaches are inevitable, but Singapore needs to do better in mitigating the risks and following through on its pledge to safeguard citizen data. "The end result is a hand-written, paper-based template filled with drawings, numbers, and measurements, which can take as long as 20 minutes per patient for severe cases," it said in a statement Tuesday.
A few years ago, I was invited to Minnesota Public Radio to speak about various legal issues related to cybersecurity. To my left was Bruce Schneier, a famous and respected cybersecurity researcher and prolific author. There wasn't much disagreement between us during the interview, though I recall emphasizing a bit more the FTC's cybersecurity efforts, noting that I thought they were doing a pretty good job in the current regulatory vacuum, building a de-facto common law as they went along. In his latest book, "Click Here to Kill Everybody," Schneier argues, among other things, that there is a systemic lack of security in all things computer (something he calls "Internet ", essentially an extension of IoT) and that what is needed to fix this is government intervention. Schneier's call for intervention comes in the form of a new government agency, one that has the ability to "coordinate and advise with other agencies" on the Internet .
In an always advancing cyber threat landscape where antivirus programming and firewalls are viewed as tools of antiquity, companies are currently searching for all the more technologically advanced methods for protecting classified and sensitive data. Artificial intelligence (AI) is accepting the situation as a warrior against digital threats over the globe. It has gotten mainstream in military space, yet security organizations are likewise consolidating AI technologies for using deep learning to discover likenesses and differences within a data set. Organizations like Microsoft are putting 1 billion USD in AI-based organizations, for example, Open AI. As indicated by ESG research, 29% of security experts would like to utilize AI innovation to accelerate the virus detection process.
Rest assured, Elon--we don't need to fear AI killer robots, at least for the time being. At this juncture, some experts believe artificial intelligence (AI) is the panacea for all of society's woes. Meanwhile, we all know how fearful Tesla CEO Elon Musk is of AI. To paraphrase, Musk has pretty much said that artificial intelligence could possibly result in the end of humanity as we know it. And that would be pretty bad.
Organisations are becoming so overwhelmed with data relating to cybersecurity that they are having to turn to artificial intelligence (AI) in order to keep abreast of it all. More than half of them reported that they were using or looking to use AI because their organisations had too much data to deal with. The machine-learning systems can help by processing huge volumes of data in a way that would be impossible for human analysts. Some cyber-attacks can be identified and blocked automatically. The AI can also alert human analysts to areas of data that they should be paying particular attention to, allowing them to respond to threats more effectively.
Artificial intelligence is a double-edged sword that can be used as a security solution or as a weapon by hackers. AI entails developing programs and systems capable of exhibiting traits associated with human behaviors. The characteristics include the ability to adapt to a particular environment or to intelligently respond to a situation. AI technologies have extensively been applied in cybersecurity solutions, but hackers are also leveraging them to develop intelligent malware programs and execute stealth attacks. Security experts have conducted a lot of research to harness the capabilities of AI and incorporate it into security solutions.
AI and machine learning will continue to enable asset management improvements that also deliver exponential gains in IT security by providing greater endpoint resiliency in 2020. Nicko van Someren, Ph.D. and Chief Technology Officer at Absolute Software, observes that "Keeping machines up to date is an IT management job, but it's a security outcome. Knowing what devices should be on my network is an IT management problem, but it has a security outcome. And knowing what's going on and what processes are running and what's consuming network bandwidth is an IT management problem, but it's a security outcome. I don't see these as distinct activities so much as seeing them as multiple facets of the same problem space, accelerating in 2020 as more enterprises choose greater resiliency to secure endpoints."
Gartner predicts $137.4B will be spent on Information Security and Risk Management in 2019, increasing to $175.5B in 2023, reaching a CAGR of 9.1%. Cloud Security, Data Security, and Infrastructure Protection are the fastest-growing areas of security spending through 2023. Spending on AI-based cybersecurity systems and services reached $7.1B in 2018 and is predicted to reach $30.9B in 2025, attaining a CAGR of 23.4% in the forecast period according to Zion Market Research. Traditional approaches to securing endpoints based on the hardware characteristics of a given device aren't stopping breach attempts today. Bad actors are using AI and Machine Learning to launch sophisticated attacks to shorten the time it takes to compromise an endpoint and successfully breach systems.
Fortinet has unveiled predictions from the FortiGuard Labs team about the threat landscape for 2020 and beyond. These predictions reveal methods that Fortinet anticipates cybercriminals will employ in the near future, along with important strategies that will help organizations protect against these oncoming attacks. Changing the Trajectory of Cyberattacks Cyberattack methodologies have become more sophisticated in recent years magnifying their effectiveness and speed. This trend looks likely to continue unless more organizations make a shift as to how they think about their security strategies. With the volume, velocity, and sophistication of today's global threat landscape, organizations must be able to respond in real time at machine speed to effectively counter aggressive attacks.
Cybersecurity is one of the many uses of artificial intelligence. Going by a recent report by Norton, the global cost to recover from a typical data breach is USD 3.86 million. Studies also conclude that it takes a whole 196 days to recover from any data breach. As such, it makes sense for companies to use AI to avoid both financial losses and waste of time. That said, this article highlights how AI can help in cybersecurity.