Trends in Security Information
The HSD Trendmonitor is designed to provide access to relevant content on various subjects in the safety and security domain, to identify relevant developments and to connect knowledge and organisations. The safety and security domain encompasses a vast number of subjects. Four relevant taxonomies (type of threat or opportunity, victim, source of threat and domain of application) have been constructed in order to visualize all of these subjects. The taxonomies and related category descriptions have been carefully composed according to other taxonomies, European and international standards and our own expertise.
In order to identify safety and security related trends, relevant reports and HSD news articles are continuously scanned, analysed and classified by hand according to the four taxonomies. This results in a wide array of observations, which we call ‘Trend Snippets’. Multiple Trend Snippets combined can provide insights into safety and security trends. The size of the circles shows the relative weight of the topic, the filters can be used to further select the most relevant content for you. If you have an addition, question or remark, drop us a line at info@securitydelta.nl.
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AI-enabled stock market manipulation
AI-Enabled Stock Market Manipulation
AI-enabled, algorithmic stock trading systems have replaced many human traders in the past years,
particularly in the area of high-frequency trading (HFT). However, the increased reliance on such systems
has provided opportunities for AI-aided stock market manipulation as well. Indeed, there are already
cases where private investors have managed to crack the algorithms of a large electronic marketplace
and manipulate share prices in their favor.88 Experiments with adversarial bots also demonstrate that by
using automation, the stock market can be manipulated.89
HFT algorithms exaggerate and accelerate market activity. Similarly, stock market “flash crashes” and the
consumption of asset value through a series of small returns on larger trading fees can create a sudden
unpredicted change in the market with consequent change in investor confidence. This can lead to further
systemic risk to the investors if exploited by criminals.
Variations on these security “criminal ML detection” approaches could be used to detect SIM-jacking
(through the detection of statistically anomalous behavior), mass wiretap (by giving alerts on unexpected
telecommunication metadata such as erratic latency), and other optimized telecommunication abuses.
Traditional fraud types like credit card fraud can also be found in nontraditional methods such as SIM card
auto-pay and other money-laundering methods.