Communication between devices should be based on predefined rules. These rules are called communication protocols. In this master thesis I am concerned with communication protocols, specially security protocols. Their design demand specialized tools, that will provide interactive simulations and security testing. I have described each of these tools in detail and mentioned about their properties, their pros and cons. In available tools I have implemented security protocols. The result is set of demonstration tasks that are usable in network courses at FIT VUT

Generating a video signal for ATtiny85 , authoring software worldwide for video game console ATARI2600 on the theme of UAV attacks and their media image - a reinterpretation of using "low res" generated video.

<div>Cellular networks are an indispensable part of a nation's critical infrastructure. They not only support functionality that are critical for our society as a whole (e.g., business, public-safety message dissemination) but also positively impact us at a more personal level by enabling applications that often improve our quality of life (e.g., navigation). Due to deployment constraints and backward compatibility issues, the various cellular protocol versions were not designed and deployed with a strong security and privacy focus. Because of their ubiquitous presence for connecting billions of users and use for critical applications, cellular networks are, however, lucrative attack targets of motivated and resourceful adversaries. </div><div><br></div><div></div><div>In this dissertation, we investigate the security and privacy of 4G LTE and 5G protocol designs and deployments. More precisely, we systematically identify design weaknesses and implementation oversights affecting the critical operations of the networks, and also design countermeasures to mitigate the identified vulnerabilities and attacks. Towards this goal, we developed a systematic model-based testing framework called LTEInspector. LTEInspector can be used to not only identify protocol design weaknesses but also deployment oversights. LTEInspector leverages the combined reasoning capabilities of a symbolic model checker and a cryptographic protocol verifier by combining them in a lazy fashion. We instantiated \system with three critical procedures (i.e., attach, detach, and paging) of 4G LTE. Our analysis uncovered 10 new exploitable vulnerabilities along with 9 prior attacks of 4G LTE all of which have been verified in a real testbed. Since identifying all classes of attacks with a unique framework like \system is nearly impossible, we show that it is possible to identify sophisticated security and privacy attacks by devising techniques specifically tailored for a particular protocol and by leveraging the findings of LTEInspector. As a case study, we analyzed the paging protocol of 4G LTE and the current version of 5G, and observed that by leveraging the findings from LTEInspector and other side-channel information and by using a probabilistic reasoning technique it is possible to mount sophisticated privacy attacks that can expose a victim device's coarse-grained location information and sensitive identifiers when the adversary is equipped only with the victim's phone number or other soft-identity (e.g., social networking profile). An analysis of LTEInspector's findings shows that the absence of broadcast authentication enables an adversary to mount a wide plethora of security and privacy attacks. We thus develop an attack-agnostic generic countermeasure that provides broadcast authentication without violating any common-sense deployment constraints. Finally, we design a practical countermeasure for mitigating the side-channel attacks in the paging procedure without breaking the backward compatibility.</div>

This diploma thesis deals with the influence of terrorist attacks on Instagram content that is shared in the immediate surroundings of locations where the attacks took place. Its primary focus is the transformation of the image of urban space near the Bataclan music club in Paris as a result of terrorist attacks in November, 2015. Using the visual content analysis of user photographs and the theoretical background of the theory of photography, visual studies and memory studies, the author investigates what image of the given place is created by shared photographs in the time before, during and after the attacks. The main conclusion is that terrorist attacks have a significant impact on the Instagram content, but it is rather short-term and their ratio of content gradually decreases over the course of six months. The thesis also presents a comparative analysis of the content shared at the time of the attacks in Paris in 2015 and in Brussels in 2016. It aims to reveal similarities as well as differences in the image of these attacks on Instagram. Above all, this analysis confirms a strong similarity of user content in all locations, but at a more detailed level it also points to their local specifics such as different forms of communication by sharing various mottos and symbols.

In recent years, the advent of Long Term Evolution (LTE) technology as a prominent component of 4G networks and future 5G networks, has paved the way for fast and new mobile web access and application services. With these advantages come some security concerns in terms of attacks that can be launched on such networks. This thesis focuses on the impact of the mobile botnet on LTE networks by implementing a mobile botnet architecture that initiates a Distributed Denial of Service (DDoS) attack. First, in the quest of understanding the mobile botnet behavior, a correlation between the mobile botnet impact and different mobile device mobility models, is established, leading to the study of the impact of the random patterns versus the uniform patterns of movements on the mobile botnet’s behavior under a DDoS attack. Second, the impact of two base transceiver station selection mechanisms on a mobile botnet behavior launching a DDoS attack on a LTE network is studied, the goal being to derive the effect of the attack severity of the mobile botnet. Third, an epidemic SMS-based cellular botnet that uses an epidemic command and control mechanism to initiate a short message services (SMS) phishing attack, is proposed and its threat impact is studied and simulated using three random graphs models. The simulation results obtained reveal that (1) in terms of users’ mobility patterns, the impact of the mobile botnet behavior under a DDoS attack on a victim web server is more pronounced when an asymmetric mobility model is considered compared to a symmetric mobility model; (2) in terms of base transceiver station selection mechanisms, the Distance-Based Model mechanism yields a higher threat impact on the victim server compared to the Signal Power Based Model mechanism; and (3) under the Erdos-and-Reyni Topology, the proposed epidemic SMS-based cellular botnet is shown to be resistant and resilient to random and selective cellular device failures. / Graduate

This literature and interview-informed dissertation research sought to explore the educational experiences of a small sample of those who identify as part of the generation of Muslim youth in the United States who have come of age in “the age of terror,” precipitated by the September 11th terrorist attacks on the U.S. The research involved analyses and interpretations of selected literatures pertaining to seminal theories, histories, and discourses pertaining to U.S situated Muslim students in high schools. In addition, responses from seven Muslim high school students who describe how they see themselves, their schooling environments around them, and their place within that constructed world also contributed to this dissertation work. The researcher interrogated study participants’ descriptions garnered mostly via facilitations of interviews, and some student written narrative and poetry. Simultaneously, the researcher, who identifies as a queer Arab Muslim-American educator, reflexively interrogated her own assumptions, biases and expectations propelling and affecting her analyses and interpretations of study data. Themes of visibility and “coming out” as Muslim as well as of political structures, forms of oppression, namely Islamophobia, and school environments are all navigated as well as questioned through the perspectives of both students and the Arab-American Muslim educator-researcher. The research both creates and leaves spaces for further delvings into teacher education dominant notions of pedagogy, classroom images, and school communities. Additionally, this dissertation research offers possibilities for change in relation to conceptions of larger intersecting power structures that influence not only how the public perceives Muslim cultures but also on how these youth see themselves.

Panikattacken sind mit einer Lebenszeitprävalenz von ungefähr 15% ein relativ häufiges Phänomen im Gegensatz zu einer vollen Panikstörung, die eine Prävalenz von 2,3–3% aufweist. In der vorliegenden epidemiologischen Untersuchung (n = 481) einer bundesweiten repräsentativen Stichprobe wurde geprüft, ob früh (vor dem 25. Lebensjahr) und spat auftretende Panikattacken sich hinsichtlich Symptomatik, Verlaufs- und Komorbiditätsmustern unterscheiden. Neben einer erhöhten Angstsymptomatik, insbesondere bezüglich respiratorischer Beschwerden und der Angst zu sterben, zeigte sich bei Panikattacken mit spätem Beginn ein erhöhtes Risiko für Multimorbidität. Auch entwickelten sich bei dieser Gruppe komorbide Bedingungen schneller. Dagegen waren Panikattacken mit frühem Beginn und einem erhöhten Risiko für Agoraphobie sowie phobische Störungen verbunden. Die Ergebnisse werden im Hinblick auf pathogenetische Mechanismen und Implikationen für die Planung therapeutischer Interventionen diskutiert.

A literature search, in addition to expert survey, was performed to estimate the size and burden of panic disorder in the European Union (EU). Epidemiologic data from EU countries were critically reviewed to determine the consistency of prevalence estimates across studies and to identify the most pressing questions for future research. A comprehensive literature search focusing on epidemiological studies in community and clinical settings in European countries since 1980 was conducted (Medline, Web of Science, Psychinfo). Only studies using established diagnostic instruments on the basis of DSM-III-R or DSM-IV, or ICD-10 were considered. Thirteen studies from a total of 14 countries were identified. Epidemiological findings are relatively consistent across the EU. The 12-month prevalence of panic disorder and agoraphobia without history of panic were estimated to be 1.8% (0.7–2.2) and 1.3% (0.7–2.0) respectively across studies. Rates are twice as high in females and age of first onset for both disorders is in adolescence or early adulthood. In addition to comorbidity with agoraphobia, panic disorder is strongly associated with other anxiety disorders, and a wide range of somatoform, affective and substance use disorders. Even subclinical forms of panic disorder (i.e., panic attacks) are associated with substantial distress, psychiatric comorbidity and functional impairment. In general health primary care settings, there appears to be substantial underdiagnosis and undertreatment of panic disorder. Moreover, panic disorder and agoraphobia are poorly recognized and rarely treated in mental health settings, despite high health care utilization rates and substantial long-term disability.

Skolattacker är en av de värsta händelser som ett samhälle kan utsättas för och polisen kan anses ha en viktig roll för att arbeta mot att detta brott inte ska behöva inträffa. Den föreliggande studiens syfte var att få djupare kunskap för hur den svenska polismyndigheten arbetar förebyggande mot att en skolattack ska ske, samt hur polisens eget krisstödsarbete ser ut inom myndigheten. Studien genomförde fyra kvalitativa semistrukturerade intervjuer med representanter från polismyndigheten i region Bergslagen. Resultatet visade att polisen kategoriserar skolattacker som “pågående dödligt våld”, och har utformat riktlinjer enbart utifrån den brottskategorin. Resultatet visade även att vissa insatser som polisen använder inte anses effektiva baserat på evidensen. Fortsättningsvis påvisade resultatet på ett behov av utveckling inom det krisstöd som polisen kan använda efter en skolattack. Den föreliggande studiens slutsatser visar att polisens förebyggande- och krisstödsarbete generellt sett är tillfredsställande, men att vissa aspekter inom arbetet bör förbättras. / A school attack is perceived as one of the worst incidents that a society can be exposed to, and the police is considered to have an essential role in preventing that such a crime will occur. The present study’s aim was to deepen the knowledge regarding how the swedish police authority works to prevent school attacks, and how the crisis support within the authority, after such an event, works. The study was conducted through four qualitative semi-structured interviews with representatives from the region Bergslagen. The results revealed that the police categorize school attacks as “ongoing deadly violence”, and that the guidelines are based solely on that category of crime. The results also showed that some methods the police use are not considered effective based on previous research. Furthermore, the results indicated a need for development within the crisis support that the police can use after a schoolattack. The present study’s conclusions showed that the preventive work and crisis support generally is seen as satisfactory but that some aspects can be improved upon.

<div>In this thesis, we focus on the problem of estimating an unknown quantity of interest, when the information required to do so is dispersed over a network of agents. In particular, each agent in the network receives sequential observations generated by the unknown quantity, and the collective goal of the network is to eventually learn this quantity by means of appropriately crafted information diffusion rules. The abstraction described above can be used to model a variety of problems ranging from environmental monitoring of a dynamical process using autonomous robot teams, to statistical inference using a network of processors, to social learning in groups of individuals. The limited information content of each agent, coupled with dynamically changing networks, the possibility of adversarial attacks, and constraints imposed by the communication channels, introduce various unique challenges in addressing such problems. We contribute towards systematically resolving some of these challenges.</div><div><br></div><div>In the first part of this thesis, we focus on tracking the state of a dynamical process, and develop a distributed observer for the most general class of LTI systems, linear measurement models, and time-invariant graphs. To do so, we introduce the notion of a multi-sensor observable decomposition - a generalization of the Kalman observable canonical decomposition for a single sensor. We then consider a scenario where certain agents in the network are compromised based on the classical Byzantine adversary model. For this worst-case adversarial setting, we identify certain fundamental necessary conditions that are a blend of system- and network-theoretic requirements. We then develop an attack-resilient, provably-correct, fully distributed state estimation algorithm. Finally, by drawing connections to the concept of age-of-information for characterizing information freshness, we show how our framework can be extended to handle a broad class of time-varying graphs. Notably, in each of the cases above, our proposed algorithms guarantee exponential convergence at any desired convergence rate.</div><div><br></div><div>In the second part of the thesis, we turn our attention to the problem of distributed hypothesis testing/inference, where each agent receives a stream of stochastic signals generated by an unknown static state that belongs to a finite set of hypotheses. To enable each agent to uniquely identify the true state, we develop a novel distributed learning rule that employs a min-protocol for data-aggregation, as opposed to the large body of existing techniques that rely on "belief-averaging". We establish consistency of our rule under minimal requirements on the observation model and the network structure, and prove that it guarantees exponentially fast convergence to the truth with probability 1. Most importantly, we establish that the learning rate of our algorithm is network-independent, and a strict improvement over all existing approaches. We also develop a simple variant of our learning algorithm that can account for misbehaving agents. As the final contribution of this work, we develop communication-efficient rules for distributed hypothesis testing. Specifically, we draw on ideas from event-triggered control to reduce the number of communication rounds, and employ an adaptive quantization scheme that guarantees exponentially fast learning almost surely, even when just 1 bit is used to encode each hypothesis. </div>