First contagious WiFi computer virus goes airborne, spreads like the common cold
First contagious WiFi computer virus goes airborne,
spreads like the common cold
4:47 PM 02/25/2014
Computer science researchers have demonstrated for the
first time how a digital virus can go airborne and spread via WiFi networks in
populated areas at the same pace as a human diseases.
The “Chameleon” virus, designed by a University of
Liverpool team, showed a remarkable amount of intelligence by avoiding
detection and breaking into personal and business WiFi networks at their
weakest points — spreading at an alarming rate.
Network Security Professor Alan Marshall said the virus
doesn’t try to damage or disrupt established networks — instead, the virus
slips in unnoticed to collect the data and log-in information of all users
connected to the network via WiFi, and seeks other WiFi networks through them —
a much more subtle, sinister and dangerous objective.
“WiFi connections are increasingly a target for computer
hackers because of well-documented security vulnerabilities, which make it
difficult to detect and defend against a virus,” Marshall said in a ScienceBlog
report. “It was assumed, however, that it wasn’t possible to develop a virus
that could attack WiFi networks — but we demonstrated that this is possible and
that it can spread quickly.”
The secret to Chameleon is the method by which it avoids
detection. Traditional computer antivirus programs look for viruses present on
computers and the Internet itself. Chameleon sticks strictly to WiFi networks,
bypassing secured, more heavily encrypted networks to enter and spread through
weaker ones — especially free public access points like those found in cafes,
on trains and in airports.
A lab experiment by the University’s School of Computer
Science and Electrical Engineering and Electronics simulated what researchers
likened to an airborne contagion attack against Belfast and London, entering
WiFi access points that connect public
and private networks to the Internet.
The virus traveled fastest across access points within a
160 feet or less of each other, following similar rates of human infection by
viruses among more densely populated areas.
“We are now able to use the data generated from this
study to develop a new technique to identify when an attack is likely,”
Marshall said.
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