Recent mass commercialization of affordableUnmanned Aerial Vehicles (UAVs, or "drones") has significantly altered the media production landscape, allowing easy acquisition of impressive aerial footage. Relevant applications include production of movies, television shows or commercials, as well as filming outdoor events or news stories for TV. Increased drone autonomy in the near future is expected to reduce shooting costs and shift focus to the creative process, rather than the minutiae of UAV operation. This short overview introduces and surveys the emerging field of autonomous UAV filming, attempting to familiarize the reader with the area and, concurrently, highlight the inherent signal processing aspects and challenges.

The emerging field of autonomous UAV cinematography is examined through a tutorial for non-experts, which also presents the required underlying technologies and connections with different UAV application domains. Current industry practices are formalized by presenting a UAV shot-type taxonomy composed of framing shot types, single-UAV camera motion types, and multiple-UAV camera motion types. Visually pleasing combinations of framing shot types and camera motion types are identified, while the presented camera motion types are modeled geometrically and graded into distinct energy consumption classes and required technology complexity levels for autonomous capture. Two specific strategies are prescribed, namely focal length compensation and multidrone compensation , for partially overcoming a number of issues arising in UAV live outdoor event coverage, deemed as the most complex UAV cinematography scenario. Finally, the shot types compatible with each compensation strategy are explicitly identified. Overall, this tutorial both familiarizes readers coming from different backgrounds with the topic in a structured manner and lays necessary groundwork for future advancements.

1 Research into Data-Driven Storytelling using Open Data has led to considerable discussion into many possible futures for storytelling and journalism in a Data-Driven world, in particular, into the Open Data directives framed by various governments across the globe as a means of facilitating governments, transparency enabled citizens and journalists to get more insights into government actions and enable deeper and easier monitoring of governments' work. While progress in the development of Open Data platforms (usually funded by national and local governments) has been significant, it is only now that we are beginning to see the emergence of more practical and more applied use of Open Data platforms. Previous works have highlighted the potential for storytelling using Open Data as a source of information for journalistic stories. Nevertheless, there is a paucity of studies into Open Data platform affordances to support Data-Driven Storytelling. In this paper, we elaborate on existing Open Data platforms in terms of support for storytelling and analyse feedback from stakeholder focus groups, to discover what methods and tools can introduce or facilitate the storytelling capabilities of Open Data platforms.

ORI OR-MEIR, NIR NISSIM, YUVAL ELOVICI, and LIOR ROKACH, Ben-Gurion University of the Negev, Beer-Sheva, IsraelAlthough malicious software (malware) has been around since the early days of computers, the sophistication and innovation of malware has increased over the years. In particular, the latest crop of ransomware has drawn attention to the dangers of malicious software, which can cause harm to private users as well as corporations, public services (hospitals and transportation systems), governments, and security institutions. To protect these institutions and the public from malware attacks, malicious activity must be detected as early as possible, preferably before it conducts its harmful acts. However, it is not always easy to know what to look for-especially when dealing with new and unknown malware that has never been seen. Analyzing a suspicious file by static or dynamic analysis methods can provide relevant and valuable information regarding a file's impact on the hosting system and help determine whether the file is malicious or not, based on the method's predefined rules. While various techniques (e.g., code obfuscation, dynamic code loading, encryption, and packing) can be used by malware writers to evade static analysis (including signature-based antivirus tools), dynamic analysis is robust to these techniques and can provide greater understanding regarding the analyzed file and consequently can lead to better detection capabilities. Although dynamic analysis is more robust than static analysis, existing dynamic analysis tools and techniques are imperfect, and there is no single tool that can cover all aspects of malware behavior. The most recent comprehensive survey performed in this area was published in 2012. Since that time, the computing environment has changed dramatically with new types of malware (ransomware, cryptominers), new analysis methods (volatile memory forensics, side-channel analysis), new computing environments (cloud computing, IoT devices), new machine-learning algorithms, and more. The goal of this survey is to provide a comprehensive and up-to-date overview of existing methods used to dynamically analyze malware, which includes a description of each method, its strengths and weaknesses, and its resilience against malware evasion techniques. In addition, we include an overview of prominent studies presenting the usage of machine-learning methods to enhance dynamic malware analysis capabilities aimed at detection, classification, and categorization.

This paper presents an overview and the first results of the FP7 MULTISENSOR project, which deals with multidimensional content integration of multimedia content for intelligent sentiment enriched and context oriented interpretation. MULTISENSOR aims at providing unified access to multilingual, multimedia and multicultural economic, news story material across borders in order to support journalism and media monitoring tasks and provide decision support for internationalisation of companies.