NSO Spyware Targets Saudi Human Rights Activists and Researchers


Amnesty International, one of the most prominent non-profit human rights organizations in the world, claims one of its staff members has been targeted by a sophisticated surveillance tool made by Israel's NSO Group. The NSO Group is an Israeli firm that's mostly known for selling high-tech spyware and surveillance malware capable of remotely cracking into Apple's iPhones and Google's Android devices to intelligence apparatuses, militaries, and law enforcement around the world. The company's most powerful spyware called Pegasus for iPhone, Android, and other mobile devices has previously been used to target human rights activists and journalists, from Mexico to the United Arab Emirates. Pegasus has been designed to hack mobile phones remotely, allowing an attacker to access an incredible amount of data on a target victim, including text messages, emails, WhatsApp messages, user's location, microphone, and camera--all without the victim's knowledge. Spyware Targets Amnesty International and Saudi Dissident Now, the nasty spyware was used against one of the Amnesty International staffers in Saudi Arabia earlier this year, alongside another Saudi human rights defender based abroad, according to a new report published today.

Solar Impulse 2: Sun-powered plane takes off from Cairo on last leg of round-the-world voyage

The Independent - Tech

Nasa has announced that it has found evidence of flowing water on Mars. Scientists have long speculated that Recurring Slope Lineae -- or dark patches -- on Mars were made up of briny water but the new findings prove that those patches are caused by liquid water, which it has established by finding hydrated salts. Several hundred camped outside the London store in Covent Garden. The 6s will have new features like a vastly improved camera and a pressure-sensitive "3D Touch" display

Analyzing the Political Sentiment of Tweets in Farsi

AAAI Conferences

We examine the question of whether we can automatically classify the sentiment of individual tweets in Farsi, to determine their changing sentiments over time toward a number of trending political topics. Examining tweets in Farsi adds challenges such as the lack of a sentiment lexicon and part-of-speech taggers, frequent use of colloquial words, and unique orthography and morphology characteristics. We have collected over 1 million Tweets on political topics in the Farsi language, with an annotated data set of over 3,000 tweets. We find that an SVM classifier with Brown clustering for feature selection yields a median accuracy of 56% and accuracy as high as 70%. We use this classifier to track dynamic sentiment during a key period of Irans negotiations over its nuclear program.

Google's prototype Chinese search engine links users' activity to their phone numbers, report claims

Daily Mail - Science & tech

Google's secretive plans in China are attracting renewed scrutiny from privacy advocates. The tech giant is said to be building a prototype version of a censored Chinese search engine that links users' activity to their personal phone number, according to the Intercept. In doing so, it would be able to comply with the Chinese government's censorship requirements, increasing the chances that such a product would launch there in the future. A bipartisan group of 16 US lawmakers asked Google if it would comply with China's internet censorship and surveillance policies should it re-enter the search engine market there While China is home to the world's largest number of internet users, a 2015 report by US think tank Freedom House found that the country had the most restrictive online use policies of 65 nations it studied, ranking below Iran and Syria. But China has maintained that its various forms of web censorship are necessary for protecting its national security.

Gang way! Compsci geeks coming through! AI engine can finger fakes on social networks


A group of computer scientists have built a machine learning algorithm that can sniff out fake profiles lurking on social networks. It's likely that you and your Facebook friends have the same mutual friends. And on Twitter, it's also probable that your followers also follow the same people you do too due to common interests. These associations in social networks can be modeled on a graph as edges, where users are the vertices or nodes. The researchers from the Ben-Gurion University of the Negev, Israel, and the University of Washington, United States, hunted for fake social media accounts by developing an unsupervised learning algorithm that measures the probability of an edge existing between vertices.