Internet worm attacks pose a significant threat to network security and
management. In this work, we coin the term Internet worm tomography as
inferring the characteristics of Internet worms from the observations of
Darknet or network telescopes that monitor a routable but unused IP address
space.
Advances in embedded devices and wireless sensor networks have resulted in
new and inexpensive health care solutions. This paper describes the
implementation and the evaluation of a wireless body sensor system that
monitors human physiological data at home. Specifically, a waist-mounted
triaxial accelerometer unit is used to record human movements.
Internet worm infection continues to be one of top security threats.
Moreover, worm infection has been widely used by botnets to recruit new bots
and construct P2P-based botnets. In this work, we attempt to characterize the
network structure of Internet worm infection and shed light on the micro-level
information of "who infects whom." Our work quantifies the infection ability of
individual hosts and reveals the key characteristics of the underlying
topologies formed by worm infection, i.e., the number of children and the
generation of the Internet worm infection family tree.