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eHealth cyber security vulnerabilities previously flagged by Sask. auditor  | Globalnews.ca

eHealth cyber security vulnerabilities previously flagged by Sask. auditor | Globalnews.ca

The province’s health data management agency, eHealth Saskatchewan, is still recovering from a ransomware attack. While the agency’s cybersecurity is considered effective by the province’s auditor, her office found vulnerabilities. The auditor’s office probed cybersecurity for eHealth’s Saskatchewan Lab Results Repository (SLRR) in 2015. Five recommendations were made following this audit. In December 2017, the auditor published a follow-up. It found eHealth did not ensure accounts with access to privileged information had passwords that expire. The auditor noted this increases the risk for a system to be breached. Alec Couros, an information and communications technology professor at the University of Regina, said it’s important to modify passwords frequently, as they are commonly bought and sold on the dark web. “Because people don’t often change their passwords very often from service to service or site to site, they can often be reused on other sites. For instance, if someone has a URegina account or an eHealth account, they might use that same password or user authentication on a different site. Once it’s exploited on one site, it can easily be used by hackers on a different site,” Couros explained. Story continues below advertisement “It’s hard for us to remember everything, and unless you’re using a password manager of some sort, it’s very typical that these passwords are reused on a number of different sites. It’s just the way it is.” The auditor also reported that not all security updates were applied on a timely basis for SLRR systems. Some updates were available since 2012 and there was no documented reason why they hadn’t been updated. 0:24 Alec Couros on cyber...
How AI is Revolutionizing Cyber Security – GBHackers

How AI is Revolutionizing Cyber Security – GBHackers

AI in Cyber attacks — once relegated to flashy movie scenes and TV dramas — are now becoming a part of our everyday lives. Nearly every week, news breaks out about another data breach at a major corporation, and every now and then, we receive emails from service providers about updating our information in light of a new information leak. Even households aren’t safe from these attacks, as Tech Radar reports that our own personal devices are becoming more vulnerable than ever One thing’s for sure: no one is exempt from cyber attacks. Fortunately, new technology is emerging in response to this particular security crisis — one of them being Artificial Intelligence (AI). With hackers now using increasingly sophisticated tactics, the innovative nature of AI could be the next best step to ensure cybersecurity. AI amasses from a large pool of data AI learns through amassing data, which means that the prevalence of cybersecurity attacks can actually be used as an advantage. special Counsel explains that AI is able to automatically assemble content in such a way that all related data is clustered together and represented visually, as well as removing duplicate content so that only the most relevant data is displayed. In a survey featured on CSO Online, it was reported that 54% of companies have all experienced some sort of cyberattack, whether through IoT or industrial controls. This means that there’s a lot of data that AI can go through to predict trends, thus loosening the burden of security professionals to investigate each and every attack. The natural language processing of AI also helps illuminate the logic...
Google’s AutoML lets you train custom machine learning models without having to code

Google’s AutoML lets you train custom machine learning models without having to code

Google today announced the alpha launch of AutoML Vision, a new service that helps developers — including those with no machine learning (ML) expertise — build custom image recognition models. While Google plans to expand this custom ML model builder under the AutoML brand to other areas, the service for now only supports computer vision models, but you can expect the company to launch similar versions of AutoML for all the standard ML building blocks in its repertoire (think speech, translation, video, natural language recognition, etc.). The basic idea here, Google says, is to allow virtually anybody to bring their images, upload them (and import their tags or create them in the app) and then have Google’s systems automatically create a customer machine learning model for them. The company says that Disney, for example, has used this system to make the search feature in its online store more robust because it can now find all the products that feature a likeness of Lightning McQueen and not just those where your favorite talking race car was tagged in the text description. The whole process, from importing data to tagging it and training the model, is done through a drag and drop interface. We’re not talking about something akin to Microsoft’s Azure ML studio here, though, where you can use a Yahoo Pipes-like interface to build, train and evaluate models. Instead, Google is opting for a system where it handles all of the hard work and trains and tunes your model for you. It’s no secret that it’s virtually impossible for businesses to hire machine learning experts and data scientists these...
What is The Role of Penetration Testing in Data Privacy

What is The Role of Penetration Testing in Data Privacy

Lack of penetration testing, A recent study found that 33% of businesses have lost customers because of a breach. Not only will this kind of security incident further add to the costs of the potential damages, but it can also negatively impact the reputation of your business — which can be harder to recover from.  If you lose the personal information and other financial data of your customers, all your hard work could go down the drain from just one cyber attack.  This is why running penetration tests regularly plays a crucial role in securing critical data.  Although it isn’t a perfect solution that will keep out every single cyber threat, pen testing can help you uncover vulnerabilities in your networks, systems, and web apps before hackers do. It is by far one of the best methods you can use to strengthen your cybersecurity. In this post, we’ll take a look at the role of pen testing in the protection and privacy of your customer and business data.     Why use penetration testing?  On average, a hacking attack happens every 39 seconds — which means there could be hackers right now with plenty of time in their hands and have the right tools who are attempting to break into your systems.  If you’re not aware where the weak spots in your systems are (or that you even have security vulnerabilities), then your highly-sensitive data could be easily exploited and exposed by hackers.   Penetration testing helps provide a solution by helping you assess whether or not the security measures, configurations, and tools you have in place are strong enough to withstand...

“100 % Cyber Security Is Myth,” Says World-Renowned Ethical Hacker Anand Prakash

There is speculation that World War III will take place over computers. Well, it is true that the Internet has simplified our life, but we tend to skip the threat of data breach hanging like a sword all over our heads. A data breach can happen through bugs or by hackers. In 2018, the world’s largest social media company, Facebook, was hacked, exposing the personal information of 50 million users. The attackers exploited a feature in Facebook’s code to gain access to user accounts and potentially take control of them. It is at this time “ethical hackers” with their creative minds help companies to retrieve the stolen data and ensure that no such hacks happen. “It is difficult to understand the mindset of hackers,” says Anand Prakash, a renowned ethical hacker from India. Anand has been scouring security loopholes on various websites. From Phishing To Finding Bugs His hunt for the bugs started in 2013 when he spotted a security flaw on Facebook. He was awarded US$ 150 for spotting the bug. “That was the first time I was rewarded for my work. Before this I used to do my work for free or for a certificate,” adds Anand. As of now, Anand has been rewarded more than Rs 3 crore for informing major MNCs about the bugs. “It all started in 2009-2010 when Orkut was dominating the social media platforms. I was challenged by my friend to hack into his account, which I did after following steps on how to hack an account,” Anand shares going down the memory lane. “It was not even hacking, it was basically...
The whisper of schizophrenia: Machine learning finds ‘sound’ words predict psychosis – Neuroscience News

The whisper of schizophrenia: Machine learning finds ‘sound’ words predict psychosis – Neuroscience News

Summary: A new deep learning algorithm can predict those at risk of psychosis with 93% accuracy by examining the latent semantic content of an individual’s speech. Source: Emory Health Sciences A machine-learning method discovered a hidden clue in people’s language predictive of the later emergence of psychosis — the frequent use of words associated with sound. A paper published by the journal npj Schizophrenia published the findings by scientists at Emory University and Harvard University. The researchers also developed a new machine-learning method to more precisely quantify the semantic richness of people’s conversational language, a known indicator for psychosis. Their results show that automated analysis of the two language variables — more frequent use of words associated with sound and speaking with low semantic density, or vagueness — can predict whether an at-risk person will later develop psychosis with 93 percent accuracy. Even trained clinicians had not noticed how people at risk for psychosis use more words associated with sound than the average, although abnormal auditory perception is a pre-clinical symptom. “Trying to hear these subtleties in conversations with people is like trying to see microscopic germs with your eyes,” says Neguine Rezaii, first author of the paper. “The automated technique we’ve developed is a really sensitive tool to detect these hidden patterns. It’s like a microscope for warning signs of psychosis.” Rezaii began work on the paper while she was a resident at Emory School of Medicine’s Department of Psychiatry and Behavioral Sciences. She is now a fellow at Harvard Medical School’s Department of Neurology. “It was previously known that subtle features of future psychosis are present in...
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