Discussions around AI cyber defence have traditionally focused on the ability of advanced machine learning to detect the earliest signs of an unfolding attack, including sophisticated, never-seen-before threats. This real-time threat detection overcomes the shortcomings of legacy tools and cuts through the noise in live, complex networks to accurately identify threatening anomalies, including'unknown unknowns'. But while the capability to identify the entire spectrum of threats in their nascent stages before a problem becomes a crisis is incredibly powerful in its own right, it also serves as a fundamental enabler for autonomous response measures, which truly deliver on the promise of artificial intelligence in cyber defense. Before the advent of AI cyber defense, the principal obstacle to achieving autonomous response was determining the exact action that is needed to stop an infection from spreading, while keeping the business operational. By their very nature and definition, traditional approaches to cyber security cannot make the jump from detection to response.
Khorasini's killing follows a slight thawing in relations between Islamabad and Washington, seemingly sparked by the Pakistan army last week freeing a U.S.-Canadian couple and their three children after five years in captivity. The family was held by the Haqqani network, an Afghan Taliban-allied militant group.
The U.S. has stepped up its military involvement in the Horn of Africa nation since President Donald Trump approved expanded military operations against the group early this year. The U.S. has carried out at least 19 drone strikes in Somalia since January, according to The Bureau of Investigative Journalism, which tracks U.S. drone strikes in a number of countries.
Recent studies by Google Brain have shown that any machine learning classifier can be tricked to give incorrect predictions, and with a little bit of skill, you can get them to give pretty much any result you want. This fact steadily becomes worrisome as more and more systems are powered by artificial intelligence -- and many of them are crucial for our safe and comfortable life. Lately, safety concerns about AI were revolving around ethics -- today we are going to talk about more pressuring and real issues. Machine learning algorithms accept the input in a form of numeric vectors. Designing an input in a specific way to get the wrong result from the model is called an adversarial attack.
RAQQA, Syria – Drone footage from the northern Syrian city of Raqqa shows the extent of devastation caused by weeks of fighting between Kurdish-led forces and the Islamic State group. Footage from Thursday shows the bombed-out shells of buildings and heaps of concrete slabs lay piled on streets littered with destroyed cars. Entire neighborhoods are seen turned to rubble, with little sign of civilian life. The U.S.-backed Kurdish-led Syrian Democratic Forces announced they have driven Islamic State group militants out of the city after weeks of fighting. The spokesman for the coalition, Col. Ryan Dillon, tweeted on Thursday that the SDF has cleared 98 percent of the city, adding that some militants remain holed up in a small pocket east of the city's athletic stadium.
The Australian government has announced awarding five organisations with Defence Innovation Hub grants worth AU$5.9 million. Western Australia-based L3 Oceania has secured a AU$2.9 million contract to explore the development of an underwater acoustic sensor, while the University of Newcastle will explore the development of virtual reality-based resilience training programs for Australian Defence Force (ADF) personnel under a AU$2.2 million contract. Agent Oriented Software from Victoria has been awarded a AU$378,000 grant to explore the concept of an "autonomous teamed intelligent software agent capability resilient to cyber-attacks"; Explosive Protective Equipment from Queensland received a AU$242,000 grant to explore the integration of a Cobham Amulet Ground Penetrating Radar into an existing unmanned ground vehicle for the detection of improvised explosive devices; and Griffith University received a AU$183,000 grant to explore the development of a portable device that enables real-time detection of airborne biological threats. "These investments will drive growth in defence industry and innovation whilst focusing on the capability needs required to ensure Australia's national security now and into the future," Minister for Defence Industry Christopher Pyne said in a statement on Friday. Launched in December last year, the Defence Innovation Hub has invested about AU$20 million to industry and research organisations, Pyne said.
The ambush in Niger earlier this month that left four U.S. troops dead has been the subject of immense speculation, not only concerning President Trump's public response to the tragedy but also about what actually happened on the ground that day. Asked by Fox News on Capitol Hill if the administration has been forthcoming about the attack, Armed Services Committee Chairman Sen. John McCain, R-Ariz., replied, "of course not" and added, "it may require a subpoena." Defense Secretary Jim Mattis said Thursday that the attack is under investigation. A dozen U.S. Army soldiers, mostly Green Berets, along with 30 Nigerians, traveled 125 miles north of Niger's capital, Niamey, in unarmored trucks on a routine mission and to meet with local village elders in Tonga Tonga, near the border with Mali, on Oct. 4. U.S. Army Sergeant La David Johnson was killed when his patrol was ambushed in Niger.
Since the 2013 Target breach, it's been clear that companies need to respond better to security alerts even as volumes have gone up. With this year's fast-spreading ransomware attacks and ever-tightening compliance requirements, response must be much faster. Adding staff is tough with the cybersecurity hiring crunch, so companies are turning to machine learning and artificial intelligence (AI) to automate tasks and better detect bad behavior. In a cybersecurity context, AI is software that perceives its environment well enough to identify events and take action against a predefined purpose. AI is particularly good at recognizing patterns and anomalies within them, which makes it an excellent tool to detect threats.
Artificial Intelligence (AI) presents a significant opportunity to solve problems previously either not easy to solve or worse, not possible to solve. The combination of AI along with today's Graphics Processing Unit (GPU) technology provides an added boost to those leveraging sophisticated algorithms in their deep learning solutions. These sophisticated systems are able to train deep learning models and ultimately lead to predictive insights. The objective is to move from reactive to proactive and finally to predictive insights. The breadth of opportunities that AI presents is wide, however, a significant opportunity is in the Cybersecurity space.