As Android has become increasingly popular, so has malware targeting it, thus pushing the research community to propose different detection techniques. However, the constant evolution of the Android ecosystem, and of malware itself, makes it hard to design robust tools that can operate for long periods of time without the need for modifications or costly re-training. Aiming to address this issue, we set to detect malware from a behavioral point of view, modeled as the sequence of abstracted API calls. We introduce MaMaDroid, a static-analysis based system that abstracts the API calls performed by an app to their class, package, or family, and builds a model from their sequences obtained from the call graph of an app as Markov chains. This ensures that the model is more resilient to API changes and the features set is of manageable size. We evaluate MaMaDroid using a dataset of 8.5K benign and 35.5K malicious apps collected over a period of six years, showing that it effectively detects malware (with up to 0.99 F-measure) and keeps its detection capabilities for long periods of time (up to 0.87 F-measure two years after training). We also show that MaMaDroid remarkably outperforms DroidAPIMiner, a state-of-the-art detection system that relies on the frequency of (raw) API calls. Aiming to assess whether MaMaDroid's effectiveness mainly stems from the API abstraction or from the sequencing modeling, we also evaluate a variant of it that uses frequency (instead of sequences), of abstracted API calls. We find that it is not as accurate, failing to capture maliciousness when trained on malware samples that include API calls that are equally or more frequently used by benign apps.

Catalan nanotechnology engineer Sergi Santos holds the head of Samantha, a sex doll packed with artificial intelligence providing her the capability to respond to different scenarios and verbal stimulus, in his house in Rubi, north of Barcelona, Spain, March 31, 2017. Picture taken March 31, 2017.

A man who spent £3,500 creating a hyper-realistic sex robot that joins him and his wife in bed has said she is part of the family - so much so that'Samantha' even joins the couple and their children on the sofa. Arran Squire, 36, from North Wales, brought his robot along for it's debut on ITV's This Morning on Tuesday, and her presence both amused and horrified presenters Phillip Schofield and Holly Willoughby. Phillip warned viewers to switch off if there were young children watching, before playing a recording of some of the ardent responses the robot is designed to make on cue. Joking it would be like'making love to a car GPS', Phil went on to say he had touched the doll and it was so cold'it felt like a corpse'. Holly was shocked to learn that Arran allowed his children to see the doll, having assumed he would keep Samantha hidden.

Alexa will put up with just about anything. She has a remarkable tolerance for annoying behavior, and she certainly doesn't care if you forget your please and thank yous. But while artificial intelligence technology can blow past such indignities, parents are still irked by their kids' poor manners when interacting with Alexa, the assistant that lives inside the Amazon Echo. "I've found my kids pushing the virtual assistant further than they would push a human," says Avi Greengart, a tech analyst and father of five who lives in Teaneck, New Jersey. "[Alexa] never says'That was rude' or'I'm tired of you asking me the same question over and over again.'"