In how far can algorithms take care of your creative work? Generative design is currently changing our conventional understanding of design in its basic principles. For decades, design was a handmade issue and postproduction a job for highly specialized professionals. Generative Design nowadays has become a popular instrument for creating artwork, models and animations with programmed algorithms. By using simple languages such as JavaScript’s p5.js and Processing based on Java, artists and makers can create everything from interactive typography and textiles to 3D-printed products to complex infographics. Computers are not only able to provide images, but also generate variations and templates in a professional quality. Pictures are being pre-optimized, processed and issued by algorithms. The profession of a designers will become more and more that of a director or conductor at the human-computer-interface. What effects does generative design have on the future creative field of designers? To find an answer to this complex field we analyze several examples of projects from a range of international designers and fine arts as well as commercial projects. In an exercise I will guide you step-by-step through a tutorial for creating your own visual experiments that explore possibilities in color, form and images.

The core part of the operating system is the kernel, and it plays an important role in managing critical data structure resources for correct operations. The kernel-level rootkits are the most elusive type of malware that can modify the running OS kernel in order to hide its presence and perform many malicious activities such as process hiding, module hiding, network communication hiding, and many more. In the past years, many approaches have been proposed to detect kernel-level rootkit. Still, it is challenging to detect new attacks and properly categorize the kernel-level rootkits. Memory forensic approaches showed efficient results with the limitation against transient attacks. Cross-view-based and integrity monitoring-based approaches have their own weaknesses. A learning-based detection approach is an excellent way to solve these problems. In this paper, we give an insight into the kernel-level rootkit characteristic features and how the features can be represented to train learning-based models in order to detect known and unknown attacks. Our feature set combined the memory forensic, cross-view, and integrity features to train learning-based detection models. We also suggest useful tools that can be used to collect the characteristics features of the kernel-level rootkit.

With the evolving artificial intelligence technology, the chatbots are becoming smarter and faster lately. Chatbots are typically available round the clock providing continuous support and services. A chatbot or a conversational agent is a program or software that can communicate using natural language with humans. The challenge of developing an intelligent chatbot still exists ever since the onset of artificial intelligence. The functionality of chatbots can range from business oriented short conversations to healthcare intervention based longer conversations. However, the primary role that the chatbots have to play is in understanding human utterances in order to respond appropriately. To that end, there is an increased emergence of Natural Language Understanding (NLU) engines by popular cloud service providers. The NLU services identify entities and intents from the user utterances provided as input. Thus, in order to integrate such understanding to a chatbot, this paper presents a study on existing major NLU platforms. Then, we present a case study chatbot integrated with Google DialogFlow and IBM Watson NLU services and discuss their intent recognition performance.

Monitoring Systems and the Internet of Things have become increasingly important, among others, in Renewable Energy applications. A combination of measuring sensors and actuators controlled and processed by an intelligent central system is necessary to reduce energy consumption automatically. This paper develops a modern concept for a Smart Energy House. The functionality and the hardware implementation are explained in detail based on a concrete simulation of the self-refilling water tank. The system comprises various separate located IoT modules integrated with a central host using TCP/IP network infrastructure, as well as communication technologies and protocols, such as WiFi and MQTT. Those sensors, also called clients, are wireless devices designed to measure different environmental conditions, such as temperature and humidity, in real-time. Changes in the current water level and battery charging progress are also being monitored. The host consists of three parts: storage service, web-based monitoring platform, and program logic for decision-making methods. Most of the processes, such as electrical control, data collection, information query, and analyzing functions, were implemented using Python libraries and self-written algorithms. An essential part of an intelligent home monitoring and automation system is secured remote accessibility and maintenance in any emergency. Therefore, the system supports both local and remote access. Data visualization and alarming routines are implemented within the web-based free software “Grafana” combined with the time-series database “InfluxDB”. Finally, the results demonstrated in this article show that the system has excellent application prospects due to its stability, low cost, high performance, user-friendly and customary configuration. The concept has been improved and prepared for the Smart Energy House test object located in Berlin.

Given the pandemic infection risk in classrooms and given the potential to purify COVID-19 prone air, this research team has visualized the flow of air to find the optimal position in a room. Through Schlieren imaging the air flow was studied to establish the circulation in the tested room. With a variation of air purifier positions in a model classroom, the imaging sensors have taken profiles of airflow and therefore contributed to identifying the optimal placings in heated classrooms. Given a random position of a potentially infected and COVID-19 infectious person, the systematic research measured concentrations of artificially produced particles that emulated aerosol distributions. The research established contaminations stabilizing after a quarter of an hour. The concentrations are only a fraction of the emitted effluents. In this way, the risk of superspreading can be mitigated and so the results allow continued academic work during the Corona pandemic

Open-source technologies (OSINT) are becoming increasingly popular with investigative and government agencies, intelligence services, media companies, and corporations. These OSINT technologies use sophisticated techniques and special tools to analyze the continually growing sources of information efficiently. There is a great need for professional training and further education in this field worldwide. After having already presented the overall structure of a professional training concept in this field in a previous paper [25], this series of articles offers individual further training modules for the worldwide standard state-of-the-art OSINT tools. The modules presented here are suitable for a professional training program and an OSINT course in a bachelor’s or master’s computer science or cybersecurity study at a university. In this part 1 of a series of 4 articles, the OSINT tool RiskIQ PassivTotal [26] is introduced, and its application possibilities are explained using concrete examples. In part 2 the OSINT tool Censys is explained [27]. Part 3 deals with Maltego [28] and Part 4 compares the 3 different tools of Part 1-3 [29].

Open-source technologies (OSINT) are becoming increasingly popular with investigative and government agencies, intelligence services, media companies, and corporations. These OSINT technologies use sophisticated techniques and special tools to analyze the continually growing sources of information efficiently. There is a great need for professional training and further education in this field worldwide. After having already presented the overall structure of a professional training concept in this field in a previous paper [25], this series of articles offers individual further training modules for the worldwide standard state-of-the-art OSINT tools. The modules presented here are suitable for a professional training program and an OSINT course in a bachelor’s or master’s computer science or cybersecurity study at a university. In part 1 of a series of 4 articles, the OSINT tool RiskIQ PassivTotal [26] is introduced, and its application possibilities are explained using concrete examples. In this part 2 the OSINT tool Censys is explained [27]. Part 3 deals with Maltego [28] and Part 4 compares the 3 different tools of Part 1-3 [29].

Open-source technologies (OSINT) are becoming increasingly popular with investigative and government agencies, intelligence services, media companies, and corporations [22]. These OSINT technologies use sophisticated techniques and special tools to analyze the continually growing sources of information efficiently [17]. There is a great need for professional training and further education in this field worldwide. After having already presented the overall structure of a professional training concept in this field in a previous paper [25], this series of articles offers individual further training modules for the worldwide standard state-of-the-art OSINT tools. The modules presented here are suitable for a professional training program and an OSINT course in a bachelor’s or master’s computer science or cybersecurity study at a university. In part 1 of a series of 4 articles, the OSINT tool RiskIQ Passiv-Total [26] is introduced, and its application possibilities are explained using concrete examples. In part 2 the OSINT tool Censys is explained [27]. This part 3 deals with Maltego [28] and Part 4 compares the 3 different tools of Part 1-3 [29].

Industrial control systems are essential for producing goods, electricity generation, infrastructure maintenance, and the transport of energy, water, and gas. They form the core of the critical infrastructure of modern industrial nations and are therefore of particular interest. Through the increased inter-connectivity of formerly isolated ICS process environments and standard IT technologies such as Ethernet, processes can be optimized and synergies leveraged. However, ICS/SCADA also becomes the target of the same cyber-attacks as conventional IT systems. Therefore, it is necessary to combine IT security has accumulated knowledge and experience with the classic Safety-First-mentality of ICS/SCADA environments to avoid significant problems in the foreseeable future. The new course was created for precisely this purpose. The investigation of the security of systems and organizations in Red and Blue Teams has long proven it is worth and is used worldwide. The first part of the Red Team side exercise deals specifically with finding and exploiting security vulnerabilities. Red Teaming refers to an independent group that acts as a counterpart to an organization to improve its operational effectiveness and enhance its security. It is the declared goal of the Red Team to detect security vulnerabilities. This work is intended to convey this interfacing knowledge; in the practical exercises for Red Teaming, these hybrid infrastructures and systems’ weak points are identified and exploited. Students will participate in numerous hands-on exercises throughout the course using the tools and techniques that form the basis for attacks on infrastructure, such as industrial control systems. A detailed accompanying theory precedes the exercises, and the course is structured as follows:Introduction <list list-type="bullet"> <list-item>ICS Cyber Kill Chain</list-item> <list-item>Types of information gathering</list-item> </list>Red Team Tools <list list-type="bullet"> <list-item>Nmap</list-item> <list-item>Maltego</list-item> <list-item>Shodan</list-item> <list-item>Google hacking</list-item> <list-item>The Harvester</list-item> <list-item>Wireshark</list-item> <list-item>GrassMarlin</list-item> <list-item>Metasploit Framework (MSF)</list-item> <list-item>John the Ripper</list-item> </list>Exercise 1 - Open Source Intelligence (OSINT) <list list-type="bullet"> <list-item>Gathering information with Maltego</list-item> <list-item>Find Remote Access with Google and Shodan</list-item> </list>Exercise 2 - Analysis of network recordings <list list-type="bullet"> <list-item>Analysis of ICS network recordings with Wireshark</list-item> <list-item>Analysis of ICS network recordings with GrassMarlin</list-item> </list>