The Data Blog
According to VentureBeat, AI is facing several critical challenges. Not only does it need huge amounts of data to deliver accurate results, but it also needs to be able to ensure that data isn’t biased, and it needs to comply with increasingly restrictive data privacy regulations.
We have seen several solutions proposed over the last couple of years to address these challenges, including various tools designed to identify and reduce bias, tools that anonymize user data, and programs to ensure that data is only collected with user consent. But each of these solutions is facing challenges of its own.
Now we’re seeing a new industry emerge that promises to be a saving grace: synthetic data. Synthetic data is artificial computer-generated data that can stand-in for data obtained from the real world. A synthetic dataset must have the same mathematical and statistical properties as the real-world dataset it is replacing but does not explicitly represent real individuals. Think of this as a digital mirror of real-world data that is statistically reflective of that world. This enables training AI systems in a completely virtual realm. And it can be readily customized for a variety of use cases ranging from healthcare to retail, finance, transportation, and agriculture.
Over the last few years, there has been increasing concern about how inherent biases in datasets can unwittingly lead to AI algorithms that perpetuate systemic discrimination. In fact, Gartner predicts that through 2022, 85% of AI projects will deliver erroneous outcomes due to bias in data, algorithms, or the teams responsible for managing them.
One alternative often used to offset privacy concerns is anonymization. Personal data, for example, can be anonymized by masking or eliminating identifying characteristics such as removing names and credit card numbers from ecommerce transactions or removing identifying content from healthcare records. But there is growing evidence that even if data has been anonymized from one source, it can be correlated with consumer datasets exposed from security breaches. In fact, by combining data from multiple sources, it is possible to form a surprisingly clear picture of our identities even if there has been a degree of anonymization. In some instances, this can even be done by correlating data from public sources, without a nefarious security hack.
Synthetic data promises to deliver the advantages of AI without the downsides. Not only does it take our real personal data out of the equation, but a general goal for synthetic data is to perform better than real-world data by correcting bias that is often ingrained in the real world.
Synthetic data is consistently able to fill the gaps where real-world data can't quite manage to hit the mark. Whether it's for the advancement of artificial intelligence or enhancement of robust simulations, synthetic data has one thing that real-world data never will have; controlled variation.
Synthetic data being created artificially gives a major advantage which allows us to control test conditions and variations within the data. Instead of needing to rely on real-world data to satisfy every single test condition you can think of, synthetic data fills each of those gaps with ease, and allows for not only progression, but automation as well. Soon, artificial intelligence will be able to improve itself by synthesizing its own simulated data and automate its own evolution.
Think of it; if artificial intelligence is able to automate its own testing and training and improve itself until completion, there won't be a need for real-world data anymore. AI would just need to create its own data to adjust itself to, which let's face it, would cover more ground a lot more quickly than any non-synthetic data counterparts.
For example, self-driving cars being able to calculate the quickest route to any given destination on the fly and adjusting accordingly based on upcoming traffic, accidents that may have occurred, or any other predicted trouble on the road would innovate the automobile industry to no end.
This also begs the question, if everyone is using synthetic data for automation, who will do it best? Will AI compete with each other to automate itself best? Only time will tell.
Jefferson Health recently reported their cloud-based database was hacked and data belonging to 1,769 patients treated at the Sidney Kimmel Cancer Center was compromised as a result. This attack occurred back in April of 2021, but was reported both publicly and to the federal government for the first time Thursday, July 22nd at the end of the 60-day legal window for reporting cyber attacks.
Cyber attacks in general have been on the rise ever since the beginning of the COVID-19 pandemic, however ransomware attacks and hackings against health facilities in the United States have soared to 153% from the year prior, and these are just those which have been reported.
Additionally, Jefferson Health was not the only healthcare facility breached by the data attack; reports suggest Yale New Haven Health System and many other affiliated Elekta healthcare organizations were breached, with intent seemingly related to stealing data related to Cancer patients.
With cyber attacks on the rise across all industries, especially healthcare, it's easy to tell that nobody is safe from malicious ransomware attacks. Companies worldwide are in constant demand for cybersecurity maintenance but it seems like the supply isn't getting any larger.
Synthetic data generation, however, offers an alternative solution, ensuring the safety of data belonging to clients while keeping the benefits of using real-world data. Now more than ever, synthetic data is imperative and serves as a great defense against hackers and cyberterrorists out to steal customer data.
Learn more at www.exactdata.net/
According to Erica Davis, Guy Carpenter, Managing Director and Cyber Center of Excellence Leader for North America, there will be $6T in 2021 global cybercrimes costs with only $6B in 2021 cyber insurance gross written premiums. The Ponemon Institute indicates 60% of cybercrime costs are due to 3rd party breaches. Fully synthetic data generation technologies eliminate the cost and risks of 3rd party breaches. The potential global financial impact is enormous with a potential reduction in cybercrime cost of $3.6T annually. The insurance industry would also be closing a huge risk exposure gap of trillions of dollars through broad adoption of synthetic data generation technologies.
Just recently, McDonalds has suffered from a data breach where the personal data of customers in Taiwon and South Korea was exposed. This comes right after JBS admitted to paying $11 million in ransom to Hackers who broke into their computer system last month.
With more and more companies are being targeted, it's hard to say who will be safe from looming threats.
Cybersecurity is one of the largest growing industries for all types of employment, including scam artists and hackers looking to make a few easy bucks. Due to the pandemic and its financial repercussions, it's more important than ever to make sure you keep yourself safe and avoid anything suspicious online.
CNBC warns that scammers are looking to target younger audiences with empty promises to forgive student loans and file taxes so that malicious software and patiently waiting hackers may steal PII (personally identifiable information), important documents, financial assets, credit card information, and more from right under their noses. This is of immediate concern especially during tax season and because stimulus checks are rolling out from the IRS, so it's important to keep your internet connection private and anti-malware software up to date.
This is not the first nor the last time scammers have tried taking advantage of a bad situation to make a quick profit which is why it's even more crucial we find new ways to combat malicious attacks coming from the cyber world.
Throughout the last few years, cybersecurity and cybersecurity strategies have drastically altered to combat data breaches and hackers trying to access private information, but did you know that one way it evolved was simply due to the overwhelming amount of information posted online by regular internet users?
Enter misinformation and disinformation; two tactics that are now employed very easily thanks to the plethora of "fake news" and faulty tabloid headlines that are written as clickbait to attract the attention of social media users and website browsers. With an abundance of all of this information on the internet and there not being any signs of incorrect information slowing down, we've entered a new age of fighting cyberattacks; by overloading wrong information.
Misinformation and disinformation, while similar, do have one key difference; misinformation is the accidental or unknowing spread of incorrect information no matter how 'almost factual' or beyond the truth the content is. The important part here is that misinformation is spread without proper intent to do so; users who share content with incorrect data or information are finding themselves misinforming the general public, or those who read their social media posts at least, which leads to the misinformation cause.
Disinformation however, is the spread of incorrect information and data with intent to do just that; lie or upload false statements for any means necessary. Whether it's for political intent, cybersecurity strategy, or because someone just wanted to lie over the internet, the act is classified as disinformation, something that has become very popular over the last few centuries through different means such as espionage and propaganda.
Disinformation campaigns have been around just as long as misinformation campaigns have been, the only difference being intent, but nevertheless both are methods that are being picked up as a cybersecurity strategy and defense mechanism to mitigate people from finding out the truth. Whether the campaign seeks to inflate profits, deflate statistics, or just simply cover up a piece of information, it's easy to say that these strategies have become modernized in the world of technology.
Everyone always tells you to be careful what you post online and that once posted to the internet something will be there forever. Social media websites are the biggest examples of pages you should monitor your activity on and the information you give out on them. Whether it's someone being able to see private information you uploaded about yourself publicly, through your messages with friends, or clicking on a link from the website that turns out to be malware, it's safe to say there are numerous ways one can become less secure simply by just having an account on a social media website.
Twitter and Facebook accounts get hacked all the time and even prominent figures accounts (which could be argued are actually less safe than the average person's account) are vulnerable to cyberterrorists, hackers, and anyone trying to get a good laugh or access information they maybe shouldn't be able to see as easily. So is social media bad for cybersecurity? Not necessarily; social media websites take these hackings as a challenge and create algorithms and programs to detect any funny business so that hackers can't access information as easily as they used to. Hackers in turn develop better hacking software and it becomes an endless cycle where one party tries to outdo the other to ensure they get the final say in what happens to your data.
Avoiding social media all together seems like a good strategy then, right? On one hand, If you don't have an account, you can't get hacked, so your data and personal software are safe. However, it just takes one devious person to notice you don't have any social media accounts before it comes crashing down on you. By catfishing and pretending to be you, hackers are able to get access to private information they may not otherwise be able to get. Furthermore, if you can't monitor social media, pictures or information about you that you wouldn't want up otherwise can go unseen by you and thus uploaded, downloaded, and on the internet forever.
The best practice for social media is to monitor your accounts and limit both what you post and what information you provide. Limit who can see that information and what they can do with it, and to be really secure, make sure you use different passwords for each of your social media accounts, so if one is hacked, you have the others to fall back on.
Social media is still an evolving technology much like cybersecurity, and due to this it has led to many data leaks and hackings. However, because of it and the focus on keeping your information safe on social media, the world of cybersecurity has advanced greatly.
Cyber Security Consulting companies are always interested in new value-added advice they can provide to their clients. One potentially lucrative area is recommending a synthetic data solution that would eliminate the risk of a data breach through your development, laboratory, and testing ecosystems where most breaches occur.
This is potentially a very lucrative market opportunity for these consulting companies. Software development globally is estimated to be around $500B annually, of which about 30% or $150B is for test data provisioning. This is all being done today through a process that modifies production data with the potential to convert to services revenue through a new disruptive synthetic data process. ROI’s are strong for the end customer eliminating repetitive labor tasks, compressing development times and removing a security risk area, which drives high margins for these new professional services.
Learn more at www.exactdata.net
When one thinks of cyber security, cyber attacks and hackers, one doesn't typically associate the manner with terrorism. However, cyberterrorism and foreign intelligence cyber attacks are becoming more of an issue as the internet evolves into a more mainstream medium around the world. Just this past July, hackers from Russia have been accused of electronically meddling in international affairs and general elections of the United Kingdom and of trying to steal information relating to a potential COVID-19 vaccine. Likewise, The United States has reportedly launched cyber operations against countries such as Iran, China, Russia, and North Korea via the CIA to 'cause disruption and leak information to the public.'
Cyber attacks can take many different forms; phishing emails, keystroke monitoring, malware downloads, and web activity monitoring, which makes tracing them hard to begin with. Additionally, attacks can be historically hard to trace due to the sophisticated nature the operations tend to take. Why, anyone can download a VPN to fool online tools and fool browsers and companies by placing their signal in another country; if just about any computer user can change their location on the internet, just imagine what the most advanced hackers are capable of.
Fortunately, there are several ways to combat cyberterrorism which range from flooding the internet with fake data to discredit the findings of any successful cyber operations to full fledged task forces and commands to fight it such as the United States Cyber Command or China's Blue Army. For more information about how the United States combats cyberterrorism, visit the United States Cyber Command website.
Every company or government agency has had some sort of data breach at some point in time. They might not even know that the breach has happened. An interesting new strategy gaining interest within the cyber security community is the use of offensive misinformation campaigns.
Misinformation campaigns involve generating synthetic databases that would be indistinguishable from the production databases and having them passed to adversaries either through a honeypot deception solution or directly placed on dark websites dealing with selling stolen data. The result is that the adversaries will uselessly expend resources trying to sort out what is real and not, place doubt on any real information they might already have, and run illicit fraud campaigns against people who do not exist.
For example, the Boeing aircraft manufacturing company would leak synthetic highly confidential wing design databases that would be indistinguishable from the real ones without extensive analysis or access to other information for verification. Other examples would be Equifax leaking bogus credit reports or VISA fake personnel financial information. The confusion and harmful effects on the adversarial community would be tremendous.
Learn more at www.exactdata.net