WEST 2020 Sponsorship and Branding Opportunities


AFCEA and the U.S. Naval Institute have developed an enhanced sponsorship program for WEST 2020 that will offer maximum visibility to those who participate! What better way to make sure you stand out and increase your exposure than at this foremost event in which industry leaders can learn about military requirements and connect with decision makers and operators, where senior military and government officials can gain feedback from sea service warfighters, and where industry thought leaders will discuss and demonstrate sea service solutions? Sponsorship opportunities are offered at a several investment levels, ensuring your ability to participate.

Browse available options below, or jump to specific categories: Patron Packages, Individual Sponsorships, Advertising Opportunities, Branding Opportunities.

Innovation Showcase: Mobile Threat Landscape

  • Room: Hall B, 1400 Aisle
Tuesday, March 03, 2020: 1:45 PM - 2:05 PM

Speaker(s)

Speaker (confirmed)
Victoria Mosby
Solutions Engineer
Lookout

Description

Mobile devices like iPads, iPhones and Android phones and tablets are increasing in popularity every month. Whether personal and using it for occasional work access (BYOD) or GFE devices, almost every organization is being impacted by this trend.

In this talk, we will describe the current threat landscape for mobile devices. This includes recent wellknown threats like Monokle, Project Zero, and the Checkra1n Jailbreak but also examples of some lesser-known threats. And how those threats can impact federal agencies and organizations. We will discuss BYOD trends and how simple it is for users of mobile devices to sideload applications on both Android and iOS devices (even without jailbreaking) that significantly increase the risk level. We will also describe some of the other threats to the mobile user such as phishing attacks, app exploits, and SDK abuse.

Finally, we will describe malware economics and how solutions can leverage automation techniques such as machine learning for mobile malware identification, and scalability. We will also discuss considerations to manage optimizing for false positive/negative alerting.


Tracks: