What do they all have in common? If you've been paying attention to cybersecurity news this past year, then you already know. All of them have experienced truly staggering data breaches in 2020. Hackers have learned to deploy every technology and trick up their sleeves to steal data, cause disruption, and exploit the billions of people out there just trying to use the internet. Fortunately, the last few years have seen the rise of new technologies that finally give us an effective way of fighting back against hackers.

On 4 June 2020, the Flemish Knowledge Centre Data & Society (KCDS) organised a consultation to gather feedback on the European Commission's white paper on artificial intelligence. In this article, you can read the key elements of the feedback. The KCDS was founded in 2019 and focuses on the interplay between data, AI and society. It enables socially responsible, ethical, and legally appropriate implementations of AI in Flanders (Belgium). It aims to enable Flemish companies, policymakers, regulators, and citizens to achieve the greatest social and/or economic benefits of AI.

As cyberattacks grow in volume and complexity in recent years, Artificial Intelligence (AI) helps under-resourced security operations analysts stay ahead of threats. From millions of research papers, blogs, and news stories to pressurize intelligence, AI provides instant results to help you fight through the noise of thousands of daily alerts, drastically reducing response time. There are very basic requirements for cybersecurity. By relying on ever-larger quantities of data, we have created the need for a parallel problem that keeps all of this safe. Unfortunately, it is much easier to generate than to protect data.

By now, it is obvious to everyone that widespread remote working is accelerating the trend of digitization in society that has been happening for decades. What takes longer for most people to identify are the derivative trends. One such trend is that increased reliance on online applications means that cybercrime is becoming even more lucrative. For many years now, online theft has vastly outstripped physical bank robberies. Willie Sutton said he robbed banks "because that's where the money is." If he applied that maxim even 10 years ago, he would definitely have become a cybercriminal, targeting the websites of banks, federal agencies, airlines, and retailers.

Here's What You Need To Remember: While much has been discussed regarding the stealthy exterior of China's fifth-generation aircraft with respect to it appearing as a transparent or deliberate F-35 rip-off, less has been known about the internal technical specifics of advanced Chinese fighters. The true margin of difference, when it comes to what may or may not make a fifth or sixth generation aircraft superior to another, may likely reside in the area of AI and its impact upon computing, sensing, targeting, maneuvering and various kinds of attack tactics. China claims to be rapidly advancing artificial intelligence capabilities for a next-generation stealth fighter slated to emerge by 2035, according to a Chinese government-backed newspaper citing the chief designer of the J-20. The description of technical plans and systems applications offered by the Global Times appears to mirror that which is often described about the F-35, meaning that it has an autonomous computerized ability to gather, organize and present an array of otherwise disparate pools of information for pilots. Quoting J-20 designer Yang Wei, the paper states, "a future fighter jet will generally require a longer combat range, longer endurance, stronger stealth capability, a larger load of air-to-air and air-to-surface weapons, and the functionality to provide its pilot with easy-to-understand battlefield situation images and predictions."

The 1st National workshop on Smart Farming and Data Analytics took place at Maynooth University in Ireland on June 12, 2019. The workshop included two invited keynote presentations, invited talks and breakout group discussions. The workshop attracted in the order of 50 participants, consisting of a mixture of computer scientists, general scientists, farmers, farm advisors, and agricultural business representatives. This allowed for lively discussion and cross-fertilization of ideas. And showed the significant interest in the smart farming domain, the many research challenges faced in the space and the potential for data analytics and information retrieval here.

A dataset of COVID-19-related scientific literature is compiled, combining the articles from several online libraries and selecting those with open access and full text available. Then, hierarchical nonnegative matrix factorization is used to organize literature related to the novel coronavirus into a tree structure that allows researchers to search for relevant literature based on detected topics. We discover eight major latent topics and 52 granular subtopics in the body of literature, related to vaccines, genetic structure and modeling of the disease and patient studies, as well as related diseases and virology. In order that our tool may help current researchers, an interactive website is created that organizes available literature using this hierarchical structure.

Recent studies have shown that graph neural networks are vulnerable against perturbations due to lack of robustness and can therefore be easily fooled. Most works on attacking the graph neural networks are currently mainly using the gradient information to guide the attack and achieve outstanding performance. Nevertheless, the high complexity of time and space makes them unmanageable for large scale graphs. We argue that the main reason is that they have to use the entire graph for attacks, resulting in the increasing time and space complexity as the data scale grows. In this work, we propose an efficient Simplified Gradient-based Attack (SGA) framework to bridge this gap. SGA can cause the graph neural networks to misclassify specific target nodes through a multi-stage optimized attack framework, which needs only a much smaller subgraph. In addition, we present a practical metric named Degree Assortativity Change (DAC) for measuring the impacts of adversarial attacks on graph data. We evaluate our attack method on four real-world datasets by attacking several commonly used graph neural networks. The experimental results show that SGA is able to achieve significant time and memory efficiency improvements while maintaining considerable performance in the attack compared to other state-of-the-art methods of attack.

The British Government has today announced it is investing £32million into cutting-edge healthcare technology. They will be formally announced by Science Minister, Amanda Solloway, MP for Derby North, later today at the launch of London Tech Week. It includes funding for six pieces of healthcare technology at the very forefront of medicine and could offer new avenues into treatment and diagnostics for millions. The investments range in size from £3.2 million to £6.1 million and will go to the universities leading the projects. The funding will come via the Engineering and Physical Sciences Research Council (EPSRC).

A new patent granted to Microsoft by the United States Patent and Trademark Office (USPTO) reveals that the company is working on conversational agents that mirror users' conversational style and/or facial expressions. The patent - Linguistic Style Matching Agent – was granted to Microsoft on September 3, 2020, and credits Daniel J McDuff, Kael R. Rowan, Mary P Czerwinski, Deepali Aneja, and Rens Hoegen as inventors. With advances in speech recognition and generative dialogue models, conversational interfaces like chatbots and virtual agents are becoming increasingly popular. While such natural language interactions have led to an evolution in human-computer interactions, the communication is mostly monotonic and constrained. These conversations, therefore, end up being only transactional and are not very natural.