The volume and complexity of malware attacks continues to increase. Old style anti-virus doesn’t suffice. Everyone – companies large and small, government agencies, and home users – need anti-malware solutions today more than ever. We’ll discuss the new forms of malware, including ransomware, file-less, and cryptojacking. We will describe the major approaches to malware detection and prevention.
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The evasiveness of modern malware is forcing the security industry to find new ways for threat identification while maintaining the balance between business and security needs. The decreasing costs of hardware, the availability of cloud infrastructure, and evolving large scale data processing frameworks, have made big data analytics and machine learning, an affordable technology to be used for cyber defense. The presentation will cover key definitions, main technologies and cyber related use cases of big data analytics. It will also detail the workflow of operation required for implementing it in the cyber domain, discuss the offender’s perspective, demonstrate identification of malware, and offer a vision for big data analytics evolving into “self-driving networks” in the future. The session incorporates a unique view of the subject, from collective academic & industry perspectives, based on my research at the Blavatnik Interdisciplinary Cyber Research Center at Tel Aviv University, and my work experience at Juniper Networks. |
Value to audience:
• Comprehend big data analytics definitions, technologies, and cyber related use cases
• Understand the principles of machine learning, and usage for both identifying malware and offensive activity
• Consider the future of big data analytics and artificial intelligence in the cybersecurity domain
