Suchergebnisse

Cyber Warfare conducted by organizations such as Anonymous and LulzSec and by nation states such as China, China, India, Iran, North Korea and the United States (Stuxnet) has become a global problem threatening governments, corporations and individuals. According to a recent analysis the global market for Cyber Warfare consulting, product development and protective services will reach a value of $15.9 billion in 2012. This in-depth text on cyber warfare written by experts on the front lines, explores the cutting edge world of cyber-warfare through the use of recent case studies such as cyber-attack conducted by large, powerful, non-state hacking organizations such as Anonymous and LulzSec and cyber-espionage and exploitation attempts that are sponsored by nations, such as China, Iran and North Korea and the recent Stuxnet attack. These topics and other s are discussed not only from a computer security perspective but also from multi-disciplinary approach including policy, military, sociological, and scientific aspects. . Provides a multi-disciplinary approach to Cyber Warfare analyzing the information technology, military, policy, social, and scientific issues that are in play. . Presents detailed case studies of cyber-attack including inter-state cyber-conflict (Russia-Estonia), cyber-attack as an element of an information operations strategy (Israel-Hezbollah,) and cyber-attack as a tool against dissidents within a state (Russia, Iran) . Explores cyber-attack conducted by large, powerful, non-state hacking organizations such as Anonymous and LulzSec . Covers cyber-attacks directed against infrastructure such including but not limited to water treatment plants, power-grid and a detailed account on Stuxent

Recently, there has been strong interest in measuring influence in online social networks. Different measures have been proposed to predict when individuals will adopt a new behavior, given the influence produced by their friends. In this article, we show that one can achieve significant improvement over these measures, extending them to consider a pair of time constraints that provide a better proxy for social influence. By conducting an engineering study that investigates retweet networks from Twitter and Sina Weibo datasets, we tune those two parameters while we examine the correlation between influence and the probability of adoption, as well as the ability to predict adoption, estimating the real susceptibility and influence to which microblog users are dynamically subjected. Although there are limitations about using retweets to analyze social influence, our results show that for the simple count of active neighbors, its correlation with the probability of adoption is boosted up to 518.75%, whereas similar gains are observed for the other influence measures analyzed. We also obtain up to 18.89% improvement in
F
1 score when compared to recent machine learning techniques that aim to predict adoption, enabling practical use of the corresponding concepts for social influence applications.