On the Privacy of Peer-Assisted Distribution of Security Patches

When a host discovers that it has a software vulnerability that is susceptible to an attack, the host needs to obtain and install a patch. Because centralized distribution of patches may not scale well, peer-to-peer (P2P) approaches have recently been suggested. There is, however, a serious privacy problem with peer-assisted patch distribution: when a peer A requests a patch from another peer B, it announces to B its vulnerability, which B can exploit instead of providing the patch. Through analytical modeling and simulation, we show that a large majority of vulnerable hosts will typically become compromised with a basic design for peer-assisted patch distribution. We then study the effectiveness of two different approaches in countering this privacy problem. The first approach utilizes special-purpose peer nodes, referred to as honeypots, that discover and blacklist malicious peers listening for patch requests from susceptible hosts. In the second approach, the patches are requested through an anonymizing network, hiding the identities of susceptible hosts from malicious peers. Using analytical models and simulation, we show that, honeypots do not completely solve the privacy problem; in contrast, an anonymizing network turns out to be more suitable for security patch distribution. ?2010 IEEE.EI

Security in network games

Attacks on the Internet are characterized by several alarming trends: 1) increases in frequency; 2) increases in speed; and 3) increases in severity. Modern computer worms simply propagate too quickly for human detection. Since attacks are now occurring at a speed which prevents direct human intervention, there is a need to develop automated defenses. Since the financial, social and political stakes are so high, we need defenses which are provably good against worst case attacks and are not too costly to deploy. In this dissertation we present two approaches to tackle these problems. For the first part of the dissertation we consider a game between an alert and a worm over a large network. We show, for this game, that it is possible to design an algorithm for the alerts that can prevent any worm from infecting more than a vanishingly small fraction of the nodes with high probability. Critical to our result is designing a communication network for spreading the alerts that has high expansion. The expansion of the network is related to the gap between the 1st and 2nd eigenvalues of the adjacency matrix. Intuitively high expansion ensures redundant connectivity. We also present results simulating our algorithm on networks of size up to $2^{25}$. In the second part of this dissertation we consider the virus inoculation game which models the selfish behavior of the nodes involved. We present a technique for this game which makes it possible to achieve the \u27windfall of malice\u27 even without the actual presence of malicious players. We also show the limitations of this technique for congestion games that are known to have a windfall of malice

Peer to Peer Networks for Defense Against Internet Worms ∗

Internet worms, which spread in computer networks without human mediation, pose a severe threat to computer systems today. The rate of propagation of worms has been measured to be extremely high and they can infect a large fraction of their potential hosts in a short time. We study two different methods of patch dissemination to combat the spread of worms. We first show that using a fixed number of patch servers performs woefully inadequately against Internet worms. We then show that by exploiting the exponential data dissemination capability of P2P systems, the spread of worms can be halted very effectively. We compare the two methods by using fluid models to compute two quantities of interest: the time taken to effectively combat the progress of the worm and the maximum number of infected hosts. We validate our models using simulations. 1

Peer to Peer Networks for Defense Against Internet Worms

Internet worms, which spread in computer networks without human mediation, pose a severe threat to computer systems today. The rate of propagation of worms has been measured to be extremely high and they can infect a large fraction of their potential hosts in a short time. We study two different methods of patch dissemination to combat the spread of worms. We first show that using a fixed number of patch servers performs inadequately against Internet worms. We then show that by exploiting the exponential data dissemination capability of P2P systems, the spread of worms can be halted effectively. We compare the two methods by using fluid models to compute two quantities of interest: the time taken to effectively combat the progress of the worm, and the maximum number of infected hosts. We validate our models using simulations