If technology becomes standard in five years’ time, we need to be prepared.In terms of digital innovation, we are now in the midst of rapid growth. All draw attention to ever-expanding networking and automation – using technologies such as the Internet of Things (IoT), Big Data, Blockchain, Machine Learning, and Blank January 2019 Calendar Artificial Intelligence. People, businesses, and organizations are revolutionizing their processes, their entire production, and their work environments.
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These trends and developments provide tremendous benefits in terms of efficiency and connectivity, but they also present users with ever-increasing challenges, such as cybersecurity. Because data volumes and data complexity are sky-rocketing. Some security engineers and analysts are increasingly overwhelmed by an exponential increase in the number of cyber threats.
Potential attackers are finding it increasingly easy to make malicious attacks on their chosen targets – they can resort to a variety of publicly available hacking tools and, with appropriate expertise, use countless third-party computers as so-called “bots” to conceal their practices or gain unauthorized access. Digitization and the Connected Industry 4.0 provide the foundation for complex applications and new business processes – while providing attack surfaces for IT-based attacks of all kinds.
New machine learning skills help improve early detection and prevent catastrophic consequences of cyber-damage. THE AI FIGHT AGAINST CYBER ATTACKS AND ANOMALIENFRAUNHOFER AISEC21New Security through AI To meet the dangers of the networked world, it is becoming increasingly important to develop innovative security technologies. These must help to analyze and, in addition, understand potential threats and malicious behavior in cyberspace more efficiently – only in this way can safer systems and adequate protection mechanisms be provided in good time.
To this end, the Fraunhofer Institute for Applied and Integrated Security AISEC uses intelligent technologies of cognitive security: Security researchers use complex artificial intelligence algorithms to continuously improve their current IT systems in both software and hardware security. By leveraging machine learning and neural network techniques, emerging cybersecurity systems can continually learn from data to dynamically adapt to changes in operational scenarios, reliably uncovering anomalies, for example.
Cyber Attack Detection, Analysis, and Assessment Security engineers can use artificial intelligence to accomplish their daily tasks in this manner both on a large scale and in high complexity work. To this end, Fraunhofer AISEC designs and develops scalable security solutions for the detection, analysis and rapid assessment of attack activities on the Internet and offers direct solutions, new protection mechanisms and best-practice applications in the area of machine learning.
Close cooperation and constant exchange with other renowned security expert concerns for the necessary development of AI-based security technologies lead to tailor-made solutions for the individual Blank January 2019 Calendar requirements of all customers. Machine learning has become a necessity since our demands on IT systems have increased immensely Think about self-driving cars that need to properly assess traffic situations, speech recognition, or “recognizing” the content of an image.