The scale of Internet-connected systems has increased considerably, and these systems are being exposed to cyber attacks more than ever. The complexity and dynamics of cyber attacks require protecting mechanisms to be responsive, adaptive, and large-scale. Machine learning, or more specifically deep reinforcement learning (DRL), methods have been proposed widely to address these issues. By incorporating deep learning into traditional RL, DRL is highly capable of solving complex, dynamic, and especially high-dimensional cyber defense problems. This paper presents a survey of DRL approaches developed for cyber security. We touch on different vital aspects, including DRL-based security methods for cyber-physical systems, autonomous intrusion detection techniques, and multi-agent DRL-based game theory simulations for defense strategies against cyber attacks. Extensive discussions and future research directions on DRL-based cyber security are also given. We expect that this comprehensive review provides the foundations for and facilitates future studies on exploring the potential of emerging DRL to cope with increasingly complex cyber security problems.

Fuzzing has played an important role in improving software development and testing over the course of several decades. Recent research in fuzzing has focused on applications of machine learning (ML), offering useful tools to overcome challenges in the fuzzing process. This review surveys the current research in applying ML to fuzzing. Specifically, this review discusses successful applications of ML to fuzzing, briefly explores challenges encountered, and motivates future research to address fuzzing bottlenecks.

Even though he started working in government more than 30 years ago, former Defense Secretary Ash Carter said he wouldn't work for President Donald Trump. Carter previously swore off politics but he says his desire not to work for Trump runs deep. "It's not politics, it's personal conduct," Carter said on "CBS This Morning" on Monday. Carter explained that he used to tell officers and soldiers in the military that they "needed to behave themselves" and would have fired an officer for acting as the president has. But that doesn't mean he always agreed with the presidents under whom he did serve.

Cyberattacks have increased on an unprecedented scale. The main reason obviously is our increasing dependence on computing devices (computers, smartphones etc) and the internet for our day-to-day needs. The technology that we depend on today has interconnectedness as one of its salient features. This, plus our habit of using unsecured networks and devices (like, for example, public Wi-Fi) for convenience's sake, too has proven to be the cause for an unprecedented increase in cyberattacks. Of the various technologies that we use today to prevent cyberattacks and to ensure cybersecurity, machine learning deserves special mention.

We know that the money launderers are winning. We know that law enforcement is losing. By now, you've probably heard the UN's statistics on this, that we catch less than 1% of these crimes, which add up to an estimated $1.6 trillion a year. At the heart of this problem is asymmetrical technology. The bad guys have sophisticated, networked, rapidly improving technologies, and the good guys are stuck in the past.

According to media reports, China and the US are leading the way in adopting AI, with the former's percentage of AI patents granted growing by 190 per cent in a five-year period and the latter investing close to $10 billion in venture capital. Not to be left behind by the other two superpowers though, Russia's president has announced his intentions to make 30 per cent of its military equipment robotic by 2025. The compound annual growth rate of AI has hit 60 per cent and is still growing. The UK is itself funding over £603 million investment in AI and one industry here that stands to benefit from AI is field and customer service. Field service organisations increasingly feel the pressure to maximise the productivity and efficiency of their workforce so they get every job right on the first try, keeping customers happy and reducing costs through increased productivity and SLA compliance.

Every time you connect to the internet from a computer, tablet or smartphone, there is a growing risk of cyberattack. If the threat is aimed at your workplace, then the entire organization around you could be vulnerable as well and, too often, the result is a major data breach. A well-run company, regardless of its size or global reach, must eventually acknowledge that cybersecurity requires a significant investment. But what tools and processes return the most bang for your buck? A growing number of experts believe that new technology based on machine learning and artificial intelligence are where the smart money lies when it comes to computer, network and data security.

How will emerging autonomous and intelligent systems affect the international landscape of power and coercion two decades from now? Will the world see a new set of artificial intelligence (AI) hegemons just as it saw a handful of nuclear powers for most of the twentieth century? Will autonomous weapon systems make conflict more likely or will states find ways to control proliferation and build deterrence, as they have done (fitfully) with nuclear weapons? And importantly, will multilateral forums find ways to engage the technology holders, states as well as industry, in norm setting and other forms of controlling the competition? The answers to these questions lie not only in the scope and spread of military applications of AI technologies but also in how pervasive their civilian applications will be.

What was perhaps most fascinating, however, was how complex the problem at hand seems to be, and how varied the proposed solutions were. Commenting on why the current automation trend appears to be so strong, Daron Acemoglu (MIT Professor of Economics and coauthor of the New York Times 2012 best-selling book Why Nations Fail) spoke about how many of the most highly compensated professionals in the workplace today are turning their creative talents to "automate, automate, automate" all available technologies, which tends to adversely affect lower-wage workers. And when asked what they would do if given a "magic wand" to protect the current workforce against automation, speakers proposed making the U.S. tax code more favorable to workers by taxing capital gains at a higher rate; dramatically expanding educational opportunities, particularly alternatives to traditional four-year college degrees; and in the developing world, making social security benefits portable. Secretary Acosta, who delivered the keynote address, declared that in a rapidly automating world, "it is critical that we adapt the culture of lifelong learning," at both the personal and policy levels. Having worked in the technology sector for the six years between my undergraduate career and joining Erb, I have personally experienced the incredible rate of current technological change, and I absolutely agree with Acosta's sentiment.

SURGERY performed with the help of a robot has been billed as the next revolution in healthcare: such procedures can be carried out through an incision the width of a finger, causing less scarring and often allowing people to return to their homes more quickly. The UK's National Health Service recently announced plans to spend £50 million on more robotic surgical equipment for operating theatres, and yet the benefits of this high-tech approach are debated.