Abstract-As mobile phones increasingly become the target of propagating malware, their use of direct pair-wise communication mechanisms, such as Bluetooth and WiFi, pose considerable challenges to malware detection and mitigation. Unlike malware that propagates using the network, where the provider can employ centralized defenses, proximity malware can propagate in an entirely distributed fashion. In this paper we consider the dynamics of mobile phone malware that propagates by proximity contact, and we evaluate potential defenses against it. Defending against proximity malware is particularly challenging since it is difficult to piece together global dynamics from just pair-wise device interactions. Whereas traditional network defenses depend upon observing aggregated network activity to detect correlated or anomalous behavior, proximity malware detection must begin at the device. As a result, we explore three strategies for detecting and mitigating proximity malware that span the spectrum from simple local detection to a globally coordinated defense. Using insight from a combination of real-world traces, analytic epidemic models, and synthetic mobility models, we simulate proximity malware propagation and defense at the scale of a university campus. We find that local proximity-based dissemination of signatures can limit malware propagation. Globally coordinated strategies with broadcast dissemination are substantially more effective, but rely upon more demanding infrastructure within the provider.

We determine analytic expressions for the performance of some low-complexity combined source-channel coding systems. The main tool used is the Hadamard transform. In particular, we obtain formulas for the average distortion of binary lattice vector quantization with affine index assignments, linear block channel coding, and a binary-symmetric channel. The distortion formulas are specialized to nonredundant channel codes for a binary-symmetric channel, and then extended to affine index assignments on a binary-asymmetric channel. Various structured index assignments are compared. Our analytic formulas provide a computationally efficient method for determining the performance of various coding schemes. One interesting result shown is that for a uniform source and uniform quantizer, the Natural Binary Code is never optimal for a nonsymmetric channel, even though it is known to be optimal for a symmetric channel.

We derive bounds for optimal rate allocation between source and channel coding for linear channel codes that meet the Gilbert-Varshamov or Tsfasman-Vlȃduţ-Zink bounds. Formulas giving the high resolution vector quantizer distortion of these systems are also derived. In addition, we give bounds on how far below channel capacity the transmission rate should be for a given delay constraint. The bounds obtained depend on the relationship between channel code rate and relative minimum distance guaranteed by the Gilbert-Varshamov bound, and do not require sophisticated decoding beyond the error correction limit. We demonstrate that the end-to-end mean-squared error decays exponentially fast as a function of the overall transmission rate, which need not be the case for certain well-known structured codes such as Hamming codes.

In this paper we evaluate the effects of malware propagating using communication services in mobile phone networks. Although self-propagating malware is well understood in the Internet, mobile phone networks have very different characteristics in terms of topologies, services, provisioning and capacity, devices, and communication patterns. To investigate malware in this new environment, we have developed an event-driver simulator that captures the characteristics and constraints of mobile phone networks. In particular, the simulator models realistic topologies and provisioned capacities of the network infrastructure, as well as the contact graphs determined by cell phone address books. We evaluate the speed and severity of random contact worms in mobile phone networks, characterize the denial-of-service effects such worms could have on the network, investigate approaches to accelerate malware propagation, and discuss the implications of defending networks against such attacks.

It is known that among all redundancy-free codes (or index assignments), the natural binary code minimizes the mean-squared error (MSE) of the uniform source and uniform quantizer on a binary symmetric channel. We derive a code which maximizes the MSE and demonstrate that the code is linear and its distortion is asymptotically equivalent, as the blocklength grows, to the expected distortion of an index assignment chosen uniformly at random.