The cyber attack incidents are frequently transmitted, and the techniques are numerous, so that the security defense technology must constantly keep pace with the times. In view of this, network security players are investing heavily in artificial intelligence (AI), machine learning (Machine Learning) and other technologies, and hope to enhance their ability to respond to cybersecurity threats. This trend will make global data (Big Data) and labor. The investment in smart and data analytics technology continues to climb, and by 2021, it will see $96 billion.
Dimitrios Pavlakis, industry analyst at ABI Research, said that we are at the heart of the artificial intelligence security revolution, which will drive machine learning solutions to quickly become the new standard after security information, event management (SIEM), and will eventually be in the next five years. Replaces a large part of traditional anti-virus software and signature-based security systems.
ABI Research found that the government, defense, banking, and technology market sectors are the main drivers and users of machine learning technology. User and EnTIty Behavioral AnalyTIcs (UEBA) and deep learning algorithm design are gradually becoming the two most prominent technologies in network security products. Many startups are focusing on related fields. Existing anti-virus software vendors, such as Symantec, will gradually change the security solution from a highly trained surveillance model to an unsupervised or semi-supervised model to respond to changing threats.
Enterprise-centric companies like IBM have drastically changed the enterprise system and introduced machine learning technology to every market segment, from healthcare to corporate analysis and network security. Companies such as Gurucul, Niara, Splunk, StatusToday, Trudera and Vectra Networks are also trying to take the lead in innovative applications for user and entity behavior analysis. Other market participants such as Deep InsTInct and Spark CogniTIon are adopting more feature-agnostic modes, deep learning and natural language processing.
Overall, Pavlakis said that this fundamental shift is already underway, and the proliferation of machine learning has also prompted new startups in the security sector to spring up, such as JASK, a new company focused on SIEM's complementary network usage analysis. . Machine learning technology has even opened up a new security field for application protection and contributed to the birth of the startup Sqreen.
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