When Wales takes on Ireland in the Six Nations rugby championship Saturday, Big Brother will be watching. Fans filing into the stadium in Cardiff will be scanned with facial recognition software as part of a police trial of the technology. Should any of their faces match a database of potential suspects, officers will be standing by, ready to swoop. It's the kind of indiscriminate mass surveillance that would be expected, in ordinary times, to be the subject of fierce debate in the U.K., as journalists and politicians fought over the proper balance between privacy and security. Instead, trial runs like the one in South Wales are taking place largely unchallenged by parliament.

This paper describes a baseline for the second iteration of the Fact Extraction and VERification shared task (FEVER2.0) which explores the resilience of systems through adversarial evaluation. We present a collection of simple adversarial attacks against systems that participated in the first FEVER shared task. FEVER modeled the assessment of truthfulness of written claims as a joint information retrieval and natural language inference task using evidence from Wikipedia. A large number of participants made use of deep neural networks in their submissions to the shared task. The extent as to whether such models understand language has been the subject of a number of recent investigations and discussion in literature. In this paper, we present a simple method of generating entailment-preserving and entailment-altering perturbations of instances by common patterns within the training data. We find that a number of systems are greatly affected with absolute losses in classification accuracy of up to $29\%$ on the newly perturbed instances. Using these newly generated instances, we construct a sample submission for the FEVER2.0 shared task. Addressing these types of attacks will aid in building more robust fact-checking models, as well as suggest directions to expand the datasets.

The future Internet of Things (IoT) will have a deep economical, commercial and social impact on our lives. The participating nodes in IoT networks are usually resource-constrained, which makes them luring targets for cyber attacks. In this regard, extensive efforts have been made to address the security and privacy issues in IoT networks primarily through traditional cryptographic approaches. However, the unique characteristics of IoT nodes render the existing solutions insufficient to encompass the entire security spectrum of the IoT networks. This is, at least in part, because of the resource constraints, heterogeneity, massive real-time data generated by the IoT devices, and the extensively dynamic behavior of the networks. Therefore, Machine Learning (ML) and Deep Learning (DL) techniques, which are able to provide embedded intelligence in the IoT devices and networks, are leveraged to cope with different security problems. In this paper, we systematically review the security requirements, attack vectors, and the current security solutions for the IoT networks. We then shed light on the gaps in these security solutions that call for ML and DL approaches. We also discuss in detail the existing ML and DL solutions for addressing different security problems in IoT networks. At last, based on the detailed investigation of the existing solutions in the literature, we discuss the future research directions for ML- and DL-based IoT security.

WASHINGTON – The Defense Department has approved a new policy that will largely bar most transgender troops and military recruits from transitioning to another sex, and require most individuals to serve in their birth gender. The new policy comes after a lengthy and complicated legal battle, and it falls short of the all-out transgender ban that was initially ordered by President Donald Trump. But it will likely force the military to eventually discharge transgender individuals who need hormone treatments or surgery and can't or won't serve in their birth gender. The order says the military services must implement the new policy in 30 days, giving some individuals a short window of time to qualify for gender transition if needed. And it allows service secretaries to waive the policy on a case-by-case basis.

As a child, I questioned just about everything. Why was my country different than the ones I saw on television shows and in movies? Why was my gender an obstacle to me becoming a leader someday? Why was educating young girls seen as so threatening to the leaders of my country? My mother would attempt to answer my questions.

The Northern Virginia Technology Council's inaugural Impact AI 2019 summit on March 21 will gather technologists in government and tech executives from companies in the region making advancements in artificial intelligence. The all-day event kicks off 7 a.m. at the Inova Center for Personalized Health Conference Center in Fairfax, Virginia, and will open with keynote speaker Toni Townes-Whitley, president of U.S. regulated industries at Microsoft. Midmorning keynote speaker Rumman Chowdhury, global lead for responsible AI at Accenture Applied Intelligence, will discuss building ethical, responsible AI. Impact AI will also feature Tech Talks -- NVTC's version of TED Talks. The MITRE Corp.'s Jay Crossler, chief engineer of operations, will present a cyber Tech Talk, and Booz Allen Hamilton's Kirk Borne, principal data scientist and executive adviser, will talk about the real power of AI and how it can help us better understand our data.

Killer robots, once imaginary fears envisioned in sci-fi films, are now referred to as Lethal Autonomous Weapons Systems (LAWS) (sometimes referred to as Lethal Autonomous Weapons (LAW) and Lethal Autonomous Robots (LAR)). The US Department of Defence defines LAWS as "a weapon system that, once activated, can select and engage targets without further intervention by a human operator …". These robots are not only capable of taking lives, but are also "learning" to take lives without human control. The general capabilities and developments on LAWS are well known and have been the focus of many more detailed articles than can be discussed here (see for example articles by Toby Walsh and Stuart Russell's Resources on LAWS). LAWS' capabilities are advancing with the exponential growth of technological capacity.

If you're going to the play the "AI" drinking game at RSA Conference 2019, you may not make it out alive. Ahead of the industry's largest trade show in San Francisco, vendors are already touting AI-based solutions meant to address one of the industry's most pressing issues: a scarcity of workers qualified to defend against cyberattacks. Over the past week, both Palo Alto Networks Inc. PANW, -0.30% and Microsoft Corp. MSFT, 0.72% announced new AI-branded services to address an often-cited lack of cybersecurity workers qualified to keep on top of an exponentially growing number of cyberattacks. In a report released Thursday, however, Cisco Systems Inc. CSCO, 0.50% said that the industry may actually be cooling to AI-powered cybersecurity.

MIT has responded to Donald Trump's bizarre suggestion that its scientists are better at flying planes than trained pilots. In a strange tweet posted on Tuesday morning, the president had suggested that computer scientists from the Massachusetts Institute of Technology were required to to fly new planes, because they are so "complicated". "Pilots are no longer needed," he wrote. The post appeared to be a response to the Ethiopian Airlines disaster, in which 157 people were killed in a crash that had strange parallels to another accident involving the same model of plane just months before. Authorities across Europe have temporarily grounded all of the same planes in an attempt to stop further disasters.

Secretary of Transportation Elaine Chao has announced a council aimed at supporting transportation projects including hyperloops and self-driving cars. The Non-Traditional and Emerging Transportation Technology Council (NETT) hopes to make sure the Department of Transportation's complex structure of various administrations doesn't impede companies from deploying such tech. "New technologies increasingly straddle more than one mode of transportation, so I've signed an order creating a new internal Department council to better coordinate the review of innovation that have multi-modal applications," Chao said in a statement. The Department of Transportation has 11 administrations (including the Federal Aviation Administration and the Federal Transit Administration), each with their own processes and regulations. The council, chaired by Deputy Secretary Jeffrey Rosen, will give companies a central access point to talk about their ideas and proposals, and NETT could help streamline permit, approval and funding processes.