Manual para o cidadão. O que fazer em caso de incêndio, terramoto, cheia, tempestade ou ataque terrorista?

Recommendations for citizens in case of disaster and terrorist attacks, including prevention measures. Recomendaçoes para se comportar em caso de catástrofe, incluindo medidas de prevençao.

The police officer's terrorist dilemma: Trust resilience following fatal errors

Suicide attacks have raised the stakes for officers deciding whether or not to shoot a suspect ('Police Officer's Terrorist Dilemma'). Despite high-profile errors we know little about how trust in the police is affected by their response to the terrorist threat. Building on a conceptualisation of lay observers as intuitive signal detection theorists, a general population sample (N= 1153) were presented with scenarios manipulated in terms of suspect status (Armed/Unarmed), officer decision (Shoot/Not Shoot) and outcome severity (e.g. suspect armed with Bomb/Knife; police shoot suspect/ suspect plus child bystander). Supporting predictions, people showed higher trust in officers who made correct decisions. reflecting good discrimination ability and who decided to shoot, reflecting an 'appropriate' response bias given the relative costs and benefits. This latter effect was moderated by (a) outcome severity, suggesting it did not simply reflect a preference for a particular type of action, and (b) preferences for a tough stance towards terrorism indexed by Right-Wing Authoritarianism (RWA). Despite loss of civilian life, failure to prevent minor terror attacks resulted in no loss of trust amongst people low in RWA. whereas among people high in RWA trust was positive when police erroneously shot all unarmed suspect. Relations to alternative definitions of trust and procedural justice research are discussed. Copyright (C),. 2007 John Wiley & Sons, Ltd.

Attacks on German public figures, 1968-2004: warning behaviors, potentially lethal and non-lethal acts, psychiatric status, and motivations

Fourteen non-terrorist attackers of public figures in Germany between 1968 and 2004 were intensively studied, with a particular focus on warning behaviors, attack behaviors, and the relationship between psychiatric diagnosis, symptoms, and motivations for the assault. A large proportion of the attackers were severely mentally ill, and most likely to be in the potentially lethal rather than the non-lethal group. A new typology of seven warning behaviors was applied to the data, and all were present, most frequently fixation and pathway warning behavior, and least frequently a direct threat. Psychiatric diagnosis could be closely linked to motivation when analyzed at the level of symptom and content of thought, often delusional. Most of the attacks were directed at political figures, and the majority occurred after 1995.

Suicide Bombers in Israel: Their Motivations, Characteristics, and Prior Activity in Terrorist Organizations

This paper examines the characteristics of suicide bombers as reflected in the Israeli press during the Second Intifada in Israel. The analysis aims to determine whether there were significant differences in the characteristics of suicide bombers with religious motives versus those with nationalist motives. The findings reveal that gender, education level, and organizational affiliation correlated significantly with motives for carrying out suicide attacks. Most of the suicide bombers with religious motives were men with elementary education. In addition, the results show that most of the suicide bombers who were affiliated with the Hamas organization acted out of religious motives. No significant differences were found between suicide bombers with religious and those with nationalist motives with regard to age, marital status, and prior activity in terrorist organizations.

GIS-integrated mathematical modeling of social phenomena at macro- and micro- levels—a multivariate geographically-weighted regression model for identifying locations vulnerable to hosting terrorist safe-houses: France as case study

Adaptability and invisibility are hallmarks of modern terrorism, and keeping pace with its dynamic nature presents a serious challenge for societies throughout the world. Innovations in computer science have incorporated applied mathematics to develop a wide array of predictive models to support the variety of approaches to counterterrorism. Predictive models are usually designed to forecast the location of attacks. Although this may protect individual structures or locations, it does not reduce the threat—it merely changes the target. While predictive models dedicated to events or social relationships receive much attention where the mathematical and social science communities intersect, models dedicated to terrorist locations such as safe-houses (rather than their targets or training sites) are rare and possibly nonexistent. At the time of this research, there were no publically available models designed to predict locations where violent extremists are likely to reside. This research uses France as a case study to present a complex systems model that incorporates multiple quantitative, qualitative and geospatial variables that differ in terms of scale, weight, and type. Though many of these variables are recognized by specialists in security studies, there remains controversy with respect to their relative importance, degree of interaction, and interdependence. Additionally, some of the variables proposed in this research are not generally recognized as drivers, yet they warrant examination based on their potential role within a complex system. This research tested multiple regression models and determined that geographically-weighted regression analysis produced the most accurate result to accommodate non-stationary coefficient behavior, demonstrating that geographic variables are critical to understanding and predicting the phenomenon of terrorism. This dissertation presents a flexible prototypical model that can be refined and applied to other regions to inform stakeholders such as policy-makers and law enforcement in their efforts to improve national security and enhance quality-of-life.

Modelling Denial of Service Attacks on JFK with Meadow's Cost-Based Framework

We present the first detailed application of Meadows’s cost-based modelling framework to the analysis of JFK, an Internet key agreement protocol. The analysis identifies two denial of service attacks against the protocol that are possible when an attacker is willing to reveal the source IP address. The first attack was identified through direct application of a cost-based modelling framework, while the second was only identified after considering coordinated attackers. Finally, we demonstrate how the inclusion of client puzzles in the protocol can improve denial of service resistance against both identified attacks.

Experiences in Passively Detecting Session Hijacking Attacks in IEEE 802.11 Networks

Current IEEE 802.11 wireless networks are vulnerable to session hijacking attacks as the existing standards fail to address the lack of authentication of management frames and network card addresses, and rely on loosely coupled state machines. Even the new WLAN security standard - IEEE 802.11i does not address these issues. In our previous work, we proposed two new techniques for improving detection of session hijacking attacks that are passive, computationally inexpensive, reliable, and have minimal impact on network performance. These techniques utilise unspoofable characteristics from the MAC protocol and the physical layer to enhance confidence in the intrusion detection process. This paper extends our earlier work and explores usability, robustness and accuracy of these intrusion detection techniques by applying them to eight distinct test scenarios. A correlation engine has also been introduced to maintain the false positives and false negatives at a manageable level. We also explore the process of selecting optimum thresholds for both detection techniques. For the purposes of our experiments, Snort-Wireless open source wireless intrusion detection system was extended to implement these new techniques and the correlation engine. Absence of any false negatives and low number of false positives in all eight test scenarios successfully demonstrated the effectiveness of the correlation engine and the accuracy of the detection techniques.

Modeling key compromise impersonation attacks on group key exchange protocols

A key exchange protocol allows a set of parties to agree upon a secret session key over a public network. Two-party key exchange (2PKE) protocols have been rigorously analyzed under various models considering different adversarial actions. However, the analysis of group key exchange (GKE) protocols has not been as extensive as that of 2PKE protocols. Particularly, the security attribute of key compromise impersonation (KCI) resilience has so far been ignored for the case of GKE protocols. We first model the security of GKE protocols addressing KCI attacks by both outsider and insider adversaries. We then show that a few existing protocols are not secure even against outsider KCI attacks. The attacks on these protocols demonstrate the necessity of considering KCI resilience for GKE protocols. Finally, we give a new proof of security for an existing GKE protocol under the revised model assuming random oracles.