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

On the power of mediators

We consider a problem at the intersection of distributed computing and game theory, namely: Is it; possible to achieve the "windfall of malice" even without the actual presence of malicious players'? Our answer to this question is "Yes and No". Our positive result is that for the virus inoculation game, it is possible to achieve the windfall of malice by use of a mediator. Our negative result is that for symmetric congestion games that are known to have a windfall of malice, it is not possible to design a mediator that achieves this windfall. In proving these two results, we develop novel techniques for mediator design that we believe will be helpful for creating non-trivial mediators to improve social welfare in a large class of games.Postprint (published version

Worm Versus Alert: Who Wins in a Battle for Control of a Large-Scale Network?

Abstract. Consider the following game between a worm and an alert 3 over a network of n nodes. Initially, no nodes are infected or alerted and each node in the network is a special detector node independently with small but constant probability. The game starts with a single node becoming infected. In every round thereafter, every infected node sends out a constant number of worms to other nodes in the population, and every alerted node sends out a constant number of alerts. Nodes in the network change state according to the following four rules: 1) If a worm is received by a node that is not a detector and is not alerted, that node becomes infected; 2) If a worm is received by a node that is a detector, that node becomes alerted; 3) If an alert is received by a node that is not infected, that node becomes alerted; 4) If a worm or an alert is received by a node that is already infected or already alerted, then there is no change in the state of that node. We make two assumptions about this game. First, that an infected nod

The forgiving tree: a self-healing distributed data structure

We consider the problem of self-healing in peer-to-peer networks that are under repeated attack by an omniscient adversary. We assume that the following process continues for up to n rounds where n is the total number of nodes initially in the network: the adversary deletes an arbitrary node from the network, then the network responds by quickly adding a small number of new edges. We present a distributed data structure that ensures two key properties. First, the diameter of the network is never more than $O(\log \Delta)$ times its original diameter, where $\Delta$ is the maximum degree of the network initially. We note that for many peer-to-peer systems, $\Delta$ is polylogarithmic, so the diameter increase would be a O(log log n) multiplicative factor. Second, the degree of any node never increases by more than 3 over its original degree. Our data structure is fully distributed, has O(1) latency per round and requires each node to send and receive O(1) messages per round. The data structure requires an initial setup phase that has latency equal to the diameter of the original network, and requires, with high probability, each node v to send O(log n) messages along every edge incident to v. Our approach is orthogonal and complementary to traditional topology-based approaches to defending against attack.Comment: Submitted to Principles of Distributed Computing (PODC) 200

Reduced meiotic recombination in rhesus macaques and the origin of the human recombination landscape.

Characterizing meiotic recombination rates across the genomes of nonhuman primates is important for understanding the genetics of primate populations, performing genetic analyses of phenotypic variation and reconstructing the evolution of human recombination. Rhesus macaques (Macaca mulatta) are the most widely used nonhuman primates in biomedical research. We constructed a high-resolution genetic map of the rhesus genome based on whole genome sequence data from Indian-origin rhesus macaques. The genetic markers used were approximately 18 million SNPs, with marker density 6.93 per kb across the autosomes. We report that the genome-wide recombination rate in rhesus macaques is significantly lower than rates observed in apes or humans, while the distribution of recombination across the macaque genome is more uniform. These observations provide new comparative information regarding the evolution of recombination in primates

Extremely low-coverage whole genome sequencing in South Asians captures population genomics information

Abstract Background The cost of Whole Genome Sequencing (WGS) has decreased tremendously in recent years due to advances in next-generation sequencing technologies. Nevertheless, the cost of carrying out large-scale cohort studies using WGS is still daunting. Past simulation studies with coverage at ~2x have shown promise for using low coverage WGS in studies focused on variant discovery, association study replications, and population genomics characterization. However, the performance of low coverage WGS in populations with a complex history and no reference panel remains to be determined. Results South Indian populations are known to have a complex population structure and are an example of a major population group that lacks adequate reference panels. To test the performance of extremely low-coverage WGS (EXL-WGS) in populations with a complex history and to provide a reference resource for South Indian populations, we performed EXL-WGS on 185 South Indian individuals from eight populations to ~1.6x coverage. Using two variant discovery pipelines, SNPTools and GATK, we generated a consensus call set that has ~90% sensitivity for identifying common variants (minor allele frequency ≥ 10%). Imputation further improves the sensitivity of our call set. In addition, we obtained high-coverage for the whole mitochondrial genome to infer the maternal lineage evolutionary history of the Indian samples. Conclusions Overall, we demonstrate that EXL-WGS with imputation can be a valuable study design for variant discovery with a dramatically lower cost than standard WGS, even in populations with a complex history and without available reference data. In addition, the South Indian EXL-WGS data generated in this study will provide a valuable resource for future Indian genomic studies

Additional file 1: of A hybrid computational strategy to address WGS variant analysis in >5000 samples

Figure S1. Venn Diagram of number of SNPs called by GATK-HC, GATK-UG, SNPTools and GotCloud and the FDR using HumanExome BeadChip array with 3533 shared samples as control. Figure S2. Rediscovery rate of SNP in the Exome region as function of alternate allele frequency using CHARGE WES variant call set as gold standard. The rediscovery rate exceeds 95% when alternate allele frequency f>=5x10-4 (AC>=5). Table S1. The choice of AWS instances used to deploy goSNAP for CHARGE WGS variant discovery in Stage A. All the jobs were scheduled via DNAnexus platform. Note that this list does not include the jobs for slicing and repacking in Stage A. Table S2. Instance specs in the “cost-effective” and “time-sensitive” mode of running goSNAP. Table S3. Profile of goSNAP runtime (in hour) with different region size, 100 Kbp and 1 Mbp, and different instance specifications. Table S4. Profile of GATK-UG runtime (in hour) with different region size, 100 Kbp and 1 Mbp, and different instance specifications. (DOCX 232 kb