On the Complexity of Asynchronous Gossip

In this paper, we study the complexity of gossip in an asynchronous, message-passing fault-prone distributed system. In short, we show that an adaptive adversary can significantly hamper the spreading of a rumor, while an oblivious adversary cannot. In the latter case, we present three randomized algorithms for achieving gossip, each offering a different trade-off between time and message complexity. We then show how to use these gossip algorithms to develop message-efficient asynchronous (randomized) consensus protocols

Who started this rumor? Quantifying the natural differential privacy guarantees of gossip protocols

International audienceGossip protocols are widely used to disseminate information in massive peer-to-peer networks. These protocols are often claimed to guarantee privacy because of the uncertainty they introduce on the node that started the dissemination. But is that claim really true? Can the source of a gossip safely hide in the crowd? This paper examines, for the first time, gossip protocols through a rigorous mathematical framework based on differential privacy to determine the extent to which the source of a gossip can be traceable. Considering the case of a complete graph in which a subset of the nodes are curious, we study a family of gossip protocols parameterized by a ``muting'' parameter s: nodes stop emitting after each communication with a fixed probability 1-s. We first prove that the standard push protocol, corresponding to the case s=1, does not satisfy differential privacy for large graphs. In contrast, the protocol with s=0 achieves optimal privacy guarantees but at the cost of a drastic increase in the spreading time compared to standard push, revealing an interesting tension between privacy and spreading time. Yet, surprisingly, we show that some choices of the muting parameter s lead to protocols that achieve an optimal order of magnitude in both privacy and speed. We also confirm empirically that, with appropriate choices of s, we indeed obtain protocols that are very robust against concrete source location attacks while spreading the information almost as fast as the standard (and non-private) push protocol

The logic of the violence in the civil war: the armed conflict in Colombia

This paper proposes a reading of the armed conflict from an evolutionary design that takes into account the Logic of Violence in the Civil War. Their aim is to assess the dynamics of conflict and changes from its author's scientific output. A context of conflicts that includes new expressions of violence and the relative failure of the paramilitary reintegration involves using new analytical models (argumentation, game theory and inconsistent information). The recent evolution of emerging gangs and their expansion into areas that were paramilitary camps requires monitoring not only of the government and the authorities, but those investigating the conflict in the present tense. The author provides heuristic research support from Schelling’s theory of strategy, Nozick’s agencies and the protection, and Gambetta’s recent contributions to the relationship between organized crime and drug cartels.Civil_war, Colombia, armed conflict, strategic_theory, Gambetta, Nozick, Schelling

A STUDY ON EFFECTIVE COUNTERMEASURES AGAINST CYBER ATTACKS IN SOUTH KOREA

Based on U.S. cybersecurity policy, this thesis proposes effective countermeasures for the Republic of Korea (ROK) to prepare for, deter, and recover from cyber threats posed by North Korea. This study identifies the most dangerous North Korean cyber strikes facing South Korea by reviewing several cases of North Korean cyberattacks, the ROK’s countermeasures, and the severity of the damage caused by the attacks. The study builds on the writings of academics and subject matter experts as well as publicly available government policy documents, although specifics on policy are limited due to national security concerns. In addition, the study acknowledges how the cybersecurity paradigm has shifted as a result of U.S. planning, reaction to, and establishment of follow-up measures for an attack of a similar type by a cyber superpower. The strategy of deterring an opponent's operations based on the past has evolved into a strategy of preparing for enemy attacks through information sharing and preemptive defense measures, and counterattack by rapid recovery and identification of the enemy through resilience and with tracking technologies. Although the ROK is a country with well-developed information technology, its cybersecurity knowledge, systems, and technology remain weak in comparison to North Korea's abilities. Consequently, it is conceivable that the ROK can respond effectively to North Korea’s cyber threats by applying the lessons learned from the United States.Major, Republic of Korea Air ForceApproved for public release. Distribution is unlimited

Compositional competitiveness for distributed algorithms

We define a measure of competitive performance for distributed algorithms based on throughput, the number of tasks that an algorithm can carry out in a fixed amount of work. This new measure complements the latency measure of Ajtai et al., which measures how quickly an algorithm can finish tasks that start at specified times. The novel feature of the throughput measure, which distinguishes it from the latency measure, is that it is compositional: it supports a notion of algorithms that are competitive relative to a class of subroutines, with the property that an algorithm that is k-competitive relative to a class of subroutines, combined with an l-competitive member of that class, gives a combined algorithm that is kl-competitive. In particular, we prove the throughput-competitiveness of a class of algorithms for collect operations, in which each of a group of n processes obtains all values stored in an array of n registers. Collects are a fundamental building block of a wide variety of shared-memory distributed algorithms, and we show that several such algorithms are competitive relative to collects. Inserting a competitive collect in these algorithms gives the first examples of competitive distributed algorithms obtained by composition using a general construction.Comment: 33 pages, 2 figures; full version of STOC 96 paper titled "Modular competitiveness for distributed algorithms.

Rumor propagation on random and small world networks

In this work; three specific dynamical systems models, the Basic, Maki-Thompson, and Daley-Kendall, are used to model rumor transmission on social networks. Rumor flow is a measure of the time it takes for the rumor to completely pass through a specified network. Comparisons between random social networks and a small world social networks yield the faster transmission of a rumor over a small world network. Using unique adjacency matrices that define our random networks, observations of some characteristics of the random networks will be made that are specific to this type of graph. Differences in the constructs of the two networks will be illustrated by comparing these properties to those of the small world networks (created by a certain rewiring scheme of a k-regular network). Interesting comparisons are to be made about the networks\u27 defining characteristics include average clustering coefficients, centrality measures, and average path lengths. The flow of a rumor through each type of network reveals the characteristics of the network. A rumor will clearly flow through a small world network faster than in a random network, mainly due to higher density, increased clustering and better defined centrality

Identifying infection processes with incomplete information

textInfections frequently occur on both networks of devices and networks of people, and can model not only viruses, but also information, rumors, and product use. However, in many circumstances, the infection process itself is hidden, and only the effects, e.g. sickness or knowledge, can be observed. In addition, this information is likely incomplete, missing many sick nodes, as well as inaccurate, with false positives. To use this data effectively, it is often essential to identify the infection process causing the sickness, or even whether the cause is an infection. For our purposes, we consider the susceptible-infected (SI) infection model. We seek to distinguish between infections and random sickness, as well as between different infection (or infection-like) processes in a limited information setting. We formulate this as a hypothesis testing problem, where (typically) in the null, the sickness affects nodes at random, and in the alternative, the infection is spread through the network. Similarly, we consider the case where the sickness may be caused by one of two infection (or infection-like) processes, and we wish to find which is the causative process. We do this is a setting with very limited information, given only a single snapshot of the infection. Only a small portion of the infected population reports the sickness. In addition, there are several other limitations we consider. There may be false positives, obfuscating the infection. Similarly, there may be a random sickness and epidemic process occurring simultaneously. Knowledge of the graph topology may be incomplete, with unknown edges over which the infection may spread. The graph may also be weighted, affecting the way the infection spreads over the graph. In all these cases, we develop algorithms to identify the causative process of the infection utilizing the fact that infected nodes will be clustered. We demonstrate that under reasonable conditions, these algorithms detect an infection with asymptotically zero error probability as the graph size increases.Electrical and Computer Engineerin

Cyberspace and Artificial Intelligence: The New Face of Cyber-Enhanced Hybrid Threats

While, until recently, cyber operations have constituted a specific subset of defense and security concerns, the synergization of cyberspace and artificial intelligence (AI), which are driving the Fourth Industrial Revolution, has raised the threat level of cyber operations, making them a centerpiece of what are called hybrid threats. The concept of hybrid threat is presently a key concern for the defense and security community; cyber-enabled and cyber-enhanced hybrid operations have been amplified in scope, frequency, speed, and threat level due to the synergies that come from the use of cyberspace and machine learning (ML)-based solutions. In the present work, we address the relevance of cyberspace-based operations and artificial intelligence for the implementation of hybrid operations and reflect on what this cyber dimension of hybrid operations implies for the concept of what constitutes a cyberweapon, the concept of hybrid human intelligence (hybrid HUMINT) and possible responses to the hybrid threat patterns