Hundreds of millions of email addresses and passwords have been posted online for anyone to download. Nearly 800 million logins are in the huge dump which contains information from thousands of data breaches. The stolen details are likely to be in use for years as hackers attempt to take over affected users accounts. Cybersecurity expert Troy Hunt said a list of more than 2.6 billion records containing around 773 million unique email addresses and more than 21 million unique passwords was being shared on a "popular hacking forum". Mr Hunt said his initial analysis of the data, which has been dubbed Collection £1, found it had been compiled from more than 2,000 different data breaches and hacked databases or websites, confirming some of his own personal information had also appeared in the lists.
Today, there are few forms of financial fraud that are more prevalent – or more costly – than credit card fraud. It's difficult to establish an exact accounting of the losses incurred each year due to credit card fraud, but one report put the cost at $21.84 billion in 2015. Troublingly, it's a problem that seems to be getting worse, not better, at least in the United States. According to the Federal Trade Commission, reports of credit card fraud went up by 23% last year alone, with no signs of slowing down. It's increasing despite a steady advancement towards more secure cards and transaction methods, leading many of the world's largest merchants and credit card issuers to search for new solutions to the problem.
Unlike technology, sometimes science fiction improves with age. Double Take is Popular Mechanics' look back at sci-fi classics that have something prescient to say about today. Four years ago, when Alex Garland's instant sci-fi classic Ex Machina debuted, it dropped into a different era--the time before Cambridge Analytica, before Russian election trolling, before the catastrophic Equifax leak and too many others like it. We'd spent decades knowing our personal data could be hacked, leaked, and abused by nefarious parties, of course. But back then, people tended to worry along individual lines, about a stolen identity or a maxed-out account--not the data-driven mass manipulation that has been repeatedly uncovered over the past few years.
Amazon, Microsoft and Google are the forerunners among tech giants to leverage artificial intelligence to tackle cybersecurity threats and keep hackers at bay, who often pose as a real user to gain crucial data. Speaking to an international news agency, the chief security officers from each of the company unanimously agreed that AI and ML plays a crucial role in protecting their company'' multi-million dollar infrastructure by crunching large pool of data on a daily basis. While acknowledging that it is impossible to stop every intruder, Stephen Schmidt, Amazon CISO, maintained that the new tech remains largely beneficial for companies like that of Amazon which has to ensure online safety of millions of people across the world. Speaking about the ability of AI and ML in identifying hacker he said, "We will see an improved ability to identify threats earlier in the attack cycle and thereby reduce the total amount of damage and more quickly restore systems to a desirable state." Speaking on the large set of data that needs to be processed for monitoring unauthorised activities, Mark Risher, product management director at Google said,"The amount of data we need to look at to make sure whether this is you or an impostor keeps growing at a rate that is too large for humans to write rules one by one."
Researchers at King Saud University, in Saudi Arabia, have developed a new approach to detect cyberbullying on Twitter using deep learning called OCDD. In contrast with other deep-learning approaches, which extract features from tweets and feed them to a classifier, their method represents a tweet as a set of word vectors. In recent years, cyberbullying on social media has become a huge and widely discussed issue. Cyberbullying entails the use of online communication channels to bully other users by sending intimidating, threatening or abusive messages. This can have psychological and sometimes life-threatening consequences for the victims.
Are you curious about the ways in which Artificial Intelligence, machine learning, and the range of cognitive technologies are helping improve Cybersecurity and respond better to emerging threats? Check out this infographic from Cognilytica that outlines some key stats as well as key ways in which AI is improving cybersecurity.
In early 2018, one of Malaysia's key security forces made a startling announcement. The Auxiliary Force, a branch of the Royal Malaysia Police Cooperative, had entered into a partnership with the Chinese company Yitu Technology to equip the Force's officers with facial-recognition capabilities. Security officials will be able to rapidly compare images caught by live body cameras with images from a central database. The head of the Auxiliary Force explained that this use of artificial intelligence (AI) was a "significant step forward" in efforts to improve public security. He also noted that his agency planned eventually to enhance the body-camera system so as to enable "real-time facial recognition and instant alerts to the presence of persons of interest from criminal watch lists."1
Recent advances in the field of artificial intelligence are gaining widespread attention from the world because of the impact that they can have on our lives. From speech recognition, virtual home assistants to learning platforms, things have gotten very interesting in the tech industry. Tech-giants have been racing against each other to incorporate AI aspects into their newest creations so as to make the human experience much more comfortable. By adding characteristics that understand children, empathy and work routines, artificial intelligence technology is set to become a revolution. Here are some of the recent advances in the field of artificial intelligence, in terms of research and technology.
The overall deep learning market is estimated to be valued at USD 3.18 Billion in 2018 and is expected to be worth USD 18.16 Billion by 2023 – MarketsandMarkets There is a lot of buzz around the deep learning technology and the remarkable market growth it has made. A deep learning solution, unlike AI and ML, needs a huge amount of embedded data and computational power to make machines learn human behavior, store knowledge, and make predictions using a trained neural network. To many people, machines behaving like humans and sharing an enormous amount of private data to it sounds creepy because it can harm their privacy. Apart from that, deep learning also has some deep problems like deepfakes and the black box models, which makes business owners reluctant to adopt the technology. But then, whether you know it or not, this technology has a lot of potential to deal with business-specific challenges and the benefits of deep learning outnumber its drawbacks.
The Consumer Electronic Show (CES) was full of artificial intelligence (AI) agents of change this past week. Amazon noted that 28,000 products are now partnered with Alexa, up from 4,000 this time last year. Distributing more content is a key focus of AI home devices, and Amazon, Google, Microsoft, and Samsung were all showcasing the AI-enabled life-enhancing features of their digital assistants. For this trend to continue, we need to embrace the policy challenges that AI brings to data collection and privacy. The explosion in AI products has been made possible by today's network speeds.