Abstract:
Signalling System No. 7 (SS7) is used in GSM/ UMTS telecommunication technologies
for signalling and management of communication. It was designed on the concept
of private boundary walled technology having mutual trust between few national/ multinational
operators with no inherent security controls in 1970s. Deregulation, expansion
and merger of telecommunication technology with data networks have beaten the concept
of boundary walls hence increasing service providers, entry points and interfaces
to SS7 network making it vulnerable to serious attacks. SS7 exploits can be used by
attackers to intercept messages, track a subscriber’s location, tape/ redirect calls, adversely
affect disaster relief operations, drain funds of individuals from banks in combination
with other methods and send billions of spam messages. This thesis provides a
comprehensive review of SS7 attacks with detailed methods to execute attacks, methods
to enter SS7 core network and recommends safeguards against SS7 attacks. It provides
implementation of machine learning concepts Vs rule based filtering to detect anomalies
in SS7 network, a template for rule based filtering of specific SS7 messages and a
conceptual defence model for the defence of the network.
