Like many
industries undergoing transformation, the Infrastructure/Security/Compliance function within large telecom
companies is becoming more data driven. Flutura Decision Sciences has been at
the forefront of some cutting edge use cases for Telecom Infrastructure/Security
Intelligence. Here are 3 powerful use cases which vividly bring out new
possibilities in Telecom big data
In most organisations the contact centre channel data is
analyzed typically from a SLA(Service Level Agreement perspective). For example
TAT (Turnaround time), Average wait time etc. But the actual transcript of the
conversation can yield powerful insights regarding telecom infrastructure
usage. Surge in Contact centre keyword frequency as a lead indicator to
infrastructure bottlenecks.
Telecom
providers are competing with each other to get greater ARPU (Average revenue
per user) from data services as opposed to voice services. In this competitive
environment a telecom provider launched a new but extremely viral gaming application
on Mobile devices. A few days after its launch it started observing a burst of
calls to the call centres and on text mining the transcript Data Scientists found
a sharp spike in the keywords alluding to performance. The specific intelligence
regarding keyword burst and specific time of day at which this was encountered was
shared with the infrastructure planning group which then put a plan in place to
throttle the bandwidth dynamically based on usage.
This is a
security use case where if an investigation team wants to find out if there
were multiple phones with the same person. When a call is made typically the following data points are captured - subscriber , date, time, and
duration. Depending on the type of call, additional data can be gathered,
including switch data, cell tower IDs, device identification (serial) numbers,
as well as International Mobile Subscriber Identity (IMSI) and International
Mobile Equipment Identity (IMEI) codes. The unique ID of the cell tower a
handset was connected to when a connection was made is one of the most important
components for collocation analysis
By examining
terabytes of CDR/Tower records from the
switch one can triangulate on a few collocation events. A co-location event can be defined as the same cellphone tower being
used to route calls during a specific point in time. This is almost like looking
for a needle in a haystack and traditional solutions would have trouble
handling the massive volume of tower and switch data. But with a combination of
massive Hadoop clusters and columnar database architecture, these queries can
be executed at lightning speed to surface a significant few events of interest
from the massive ocean of log data
across devices
Telecom
use case-3 : Multi
device event stream analysis co-relating Firewall & IDS & Switch
activity
Typically in most telecom
infrastructures IDS ( Intrusion detection systems ) sit at the periphery of the
network monitoring malicious activity and recording the same as log entries or
alarm events into a log file. Firewalls and application logs also store a plethora of important events which if triangulated
thru a central log repository to provide a comprehensive picture
of any patterns which are dormant in the attack
One key components to enabling a Central
Log File repository with events
streaming from multiple devices which are ingested and collated centrally. Once this central log file is set up to store
the torrent of event data, it can be channelized
into intelligence to optimize network infrastructure and aid security of the
telecom assets. Flutura Decision Sciences is convinced that setting up of a
Network Intelligence team consisting of Security experts and Data Scientists
who work in a collaborative fashion can yield dramatic game changing insights
to catapult an organisation to the next level
I am not very much cleared with the point number 2. Can you throw more light on it to get it better explained?
ReplyDeleteRegards
Shivlu Jain
Sir,
ReplyDeleteCan you share more details on the data sources for each use case( CDR, application log etc) so that we egt a more clear picture of how unstructured data was utilized to provide solution to these problem statements?
Hi Ishaan/Shivlu,
ReplyDeleteThe breadth of data sources used are
- CDR : Call detail records from the switch
- Firewall alarm event logs
- Location logs from towers
- Virtually any device in the telecom infrastructure instrumented to capture event logs. Trust that helps
I need some clarification like from where M2M usage information is captured? How devices & customers are linked?(The way we have Mobile Number/IMSI linked with customer in Wireless Telecom).
ReplyDeleteDoes M2M billing happens on data usage done through GGSN/SGSN? If yes, how to identify it?
Are there any separate billing plans those are offered for M2M service enablement?
The fifth necessity is to frequently check and screen systems and their exercises. Security ought to be frequently checked for redesigns. All endeavors to get to private data inside the system ought to likewise be checked.
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