Detecting word substitutions in text

Searching for words on a watchlist is one way in which large-scale surveillance of communication can be done, for example in intelligence and counterterrorism settings. One obvious defense is to replace words that might attract attention to a message with other, more innocuous, words. For example, the sentence the attack will be tomorrow" might be altered to the complex will be tomorrow", since 'complex' is a word whose frequency is close to that of 'attack'. Such substitutions are readily detectable by humans since they do not make sense. We address the problem of detecting such substitutions automatically, by looking for discrepancies between words and their contexts, and using only syntactic information. We define a set of measures, each of which is quite weak, but which together produce per-sentence detection rates around 90% with false positive rates around 10%. Rules for combining persentence detection into per-message detection can reduce the false positive and false negative rates for messages to practical levels. We test the approach using sentences from the Enron email and Brown corpora, representing informal and formal text respectively

Lying takes time : a meta-analysis on reaction time measures of deception

Lie detection techniques are frequently used, but most of them have been criticized for the lack of empirical support for their predictive validity and presumed underlying mechanisms. This situation has led to increased efforts to unravel the cognitive mechanisms underlying deception and to develop a comprehensive theory of deception. A cognitive approach to deception has reinvigorated interest in reaction time (RT) measures to differentiate lies from truths and to investigate whether lying is more cognitively demanding than truth telling. Here, we provide the results of a meta-analysis of 114 studies (n = 3307) using computerized RT paradigms to assess the cognitive cost of lying. Results revealed a large standardized RT difference, even after correction for publication bias (d = 1.049; 95% CI [0.930; 1.169]), with a large heterogeneity amongst effect sizes. Moderator analyses revealed that the RT deception effect was smaller, yet still large, in studies in which participants received instructions to avoid detection. The autobiographical Implicit Association Test produced smaller effects than the Concealed Information Test, the Sheffield Lie Test, and the Differentiation of Deception paradigm. An additional meta-analysis (17 studies, n = 348) showed that, like other deception measures, RT deception measures are susceptible to countermeasures. Whereas our meta-analysis corroborates current cognitive approaches to deception, the observed heterogeneity calls for further research on the boundary conditions of the cognitive cost of deception. RT-based measures of deception may have potential in applied settings, but countermeasures remain an important challenge

Code wars: steganography, signals intelligence, and terrorism

This paper describes and discusses the process of secret communication known as steganography. The argument advanced here is that terrorists are unlikely to be employing digital steganography to facilitate secret intra-group communication as has been claimed. This is because terrorist use of digital steganography is both technically and operationally implausible. The position adopted in this paper is that terrorists are likely to employ low-tech steganography such as semagrams and null ciphers instead

Stealthy Plaintext

Correspondence through email has become a very significant way of communication at workplaces. Information of most kinds such as text, video and audio can be shared through email, the most common being text. With confidential data being easily sharable through this method most companies monitor the emails, thus invading the privacy of employees. To avoid secret information from being disclosed it can be encrypted. Encryption hides the data effectively but this makes the data look important and hence prone to attacks to decrypt the information. It also makes it obvious that there is secret information being transferred. The most effective way would be to make the information seem harmless by concealing the information in the email but not encrypting it. We would like the information to pass through the analyzer without being detected. This project aims to achieve this by “encrypting” plain text by replacing suspicious keywords with non-suspicious English words, trying to keep the grammatical syntax of the sentences intact

Political Speech on Twitter: A Sentiment Analysis of Tweets and News Coverage of Local Gun Policy

While the gun debate has been one of America’s most politically contentious issues, Twitter has become, in recent years a popular venue for politicians to carry out the debate. The present thesis is aimed at better understanding of political speech on Twitter, as well as the ways in which political frames and sentiment on Twitter differ from those of news media coverage regarding gun policy in the state of Arkansas. The study uses framing theory, which assumes that both news media and individuals use frames to construct perceptions and narratives about issues. Adopting an automated content analysis as a method, the study examined 354 gun-related tweets downloaded from the Twitter accounts of three Arkansas politicians (Charlie Collins, Denise Garner, and Greg Leding) and 40 news articles about gun policy involving these politicians from three local newspapers. The results indicated that state politicians’ discourse on Twitter constituted of a variety of extremely polarized words and frames pertaining and appealing to the core values of their local constituents, while local newspapers’ frames were very fact-based and unbiased. The results also showed that political sentiment on Twitter was extremely negative, fearful, and agitated, while news media expressed a very neutral sentiment in their coverage of gun policy, suggesting a new venue for further investigation of current assumptions about the negative nature of news tone