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How Will Mobile Operators Make Money in the Future?

The mobile market continues to evolve at a blindingly fast pace. It seems as though new faster, sleeker, and more powerful mobile devices are launched every day. And new categories of mobile devices are created almost overnight. The number of applications available to run on these revolutionary new mobile devices is staggering, numbering in the millions. The insatiable demand for mobile devices and new bandwidth-hungry applications is generating enormous amounts of mobile data. The Cisco Visual Networking Index™ (Cisco VNI™) predicts that these trends will cause global mobile data traffic to increase 11-fold from 2013 to 2018, surpassing 15 exabytes per month by 2018.

In spite of this phenomenal growth and insatiable consumer demand, many MNOs are struggling to profit from this mobile gold rush. Mobile operators are watching as their average revenue per customer (ARPU) flattens or declines. Despite increasing customer appetite for mobile data, minutes of use in their cash-cow voice business are falling off sharply, and usage of text messaging is peaking. In fact, Ovum predicts that 2018 will mark the first year of revenue contraction in the history of the global mobile market. Following four years of less than 1 percent growth between 2012 and 2017, revenues will decline by 1 percent in 2018, ending the year $7.8 billion lower than in 2017.

This mobile paradox – huge growth and customer demand, yet Read More »

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Attack Analysis with a Fast Graph

TRAC-tank-vertical_logo-300x243This post is co-authored by Martin Lee, Armin Pelkmann, and Preetham Raghunanda.

Cyber security analysts tend to redundantly perform the same attack queries with different input data. Unfortunately, the search for useful meta-data correlation across proprietary and open source data sets may be laborious and time consuming with relational databases as multiple tables are joined, queried, and the results inevitably take too long to return. Enter the graph database, a fundamentally improved database technology for specific threat analysis functions. Representing information as a graph allows the discovery of associations and connection that are otherwise not immediately apparent.

Within basic security analysis, we represent domains, IP addresses, and DNS information as nodes, and represent the relationships between them as edges connecting the nodes. In the following example, domains A and B are connected through a shared name server and MX record despite being hosted on different servers. Domain C is linked to domain B through a shared host, but has no direct association with domain A.

graph_image_1 This ability to quickly identify domain-host associations brings attention to further network assets that may have been compromised, or assets that will be used in future attacks.

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TU Darmstadt Rolls Out Cisco Unified Access to Prepare for 802.11ac

Technische Universität Darmstadt, usually known as TU Darmstadt is a research university based in Germany. It was founded in 1877 and over the last 137 years has grown to be among the largest and most prestigious public universities in Germany serving over 25,000 students per year. It is the alma-mater to many world-wide leaders from Nobel prize winners, a CEO of a fortune 500 company, a president of a country and multiple World Robocup champions.

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No wonder, they have a reference from Albert Einstein!

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In 2009 TU Darmstadt embraced BYOD with the 5508 Series Controller managing the 1140 802.11n Access Points. Recently we talked to Thomas Vogel, the Head of Network Group and Andreas Liebe, the Network Services Manager who have over 15 years of experience managing WLAN environments. In this blog, we will describe some of the details of WLAN deployments using the 3850 Series Switch and the 5760 Series Wireless LAN Controller to address the new requirements in the school environment. Read More »

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Angling for Silverlight Exploits

VRT / TRACThis post is co-authored by Andrew Tsonchev, Jaeson Schultz, Alex Chiu, Seth Hanford, Craig Williams, Steven Poulson, and Joel Esler. Special thanks to co-author Brandon Stultz for the exploit reverse engineering. 

Silverlight exploits are the drive-by flavor of the month. Exploit Kit (EK) owners are adding Silverlight to their update releases, and since April 23rd we have observed substantial traffic (often from Malvertising) being driven to Angler instances partially using Silverlight exploits. In fact in this particular Angler campaign, the attack is more specifically targeted at Flash and Silverlight vulnerabilities and though Java is available and an included reference in the original attack landing pages, it’s never triggered.

Rise in Angler Attacks

HTTP requests for a specific Angler Exploit Kit campaign

Exploit Content Type

Angler exploit content types delivered to victims, application/x-gzip (Java) is notably absent

 

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Understanding the Changing Mobile User

Mobile communications today is virtually indistinguishable from the first mobile call that was made four decades ago.  We have gone from monster handsets to pocket-sized portable computers.  Mobile communications has become an essential part of our daily lives.  For mobile operators and other companies operating in this space it is essential to know the facts about the mobile market and how the mobile user is changing.

The recent video by Cisco “Understanding the Changing Mobile User” provides key insights for SPs into how mobile users are using LTE, Wi-Fi and their changing mobile behavior.  The video identifies options for operators to be successful in the changing mobile world.

The Read More »

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