When the iPad first came out and was only available in the US I asked around on how to get one to The Netherlands. I wanted one and didn’t want to wait an extra 2 months. The company that arranged one for me was US Unlocked. Their CEO, Linda Hemerik, took great care to make sure I was one of the first people in The Netherlands to get my iPad. She alsotook orders from hundreds of peoplefrom all over the world who also wanted their iPads....

If you frequently send voice messages in WhatsApp, chances are you’ve sent an unintended voice clip at least once or twice. Maybe there was something embarrassing going on in the background, or perhaps you’ve recorded a message, only to realize the other person can’t actually hear you due to ambient noise. It’s a mistake that, ideally, should be avoidable. Fret no more: WhatsApp now allows you to preview messages before sending them....

How to protect AI systems against image-scaling attacks Adversarial image-scaling When trained on many examples, machine learning models create mathematical representations of the similarities between different classes. For instance, if you train a machine-learning algorithm to tell the difference between cats and dogs, it will try to create a statistical model that can tell whether the pixels in a new image are more like those found in the dog or cat images....

How to protect your AI systems against adversarial machine learning Applying ATT&CK to machine learning The Adversarial ML Threat Matrix is presented in the style of ATT&CK, a tried-and-tested framework developed by MITRE to deal with cyber-threats in enterprise networks. ATT&CK provides a table that summarizes different adversarial tactics and the types of techniques that threat actors perform in each area. Since its inception, ATT&CK has become a popular guide for cybersecurity experts and threat analysts to find weaknesses and speculate on possible attacks....

Machine learning has become an important component of many applications we use today. And adding machine learning capabilities to applications is becoming increasingly easy. Many ML libraries and online services don’t even require a thorough knowledge of machine learning. However, even easy-to-use machine learning systems come with their own challenges. Among them is the threat ofadversarial attacks, which has become one of the important concerns of ML applications. Adversarial attacks aredifferent from other types of security threatsthat programmers are used to dealing with....