scholarly journals Investigating Malware Propagation and Behaviour Using System and Network Pixel-Based Visualisation

2021 ◽  
Vol 3 (1) ◽  
Author(s):  
Jacob Williams ◽  
Phil Legg
Keyword(s):  
Large Scale ◽  
Cyber Attacks ◽  
Network Activity ◽  
Malware Analysis ◽  
Activity Data ◽  
Malicious Software ◽  
High Profile ◽  
Complex Information ◽  
Malware Propagation ◽  
Key Characteristics

AbstractMalicious software, known as malware, is a perpetual game of cat and mouse between malicious software developers and security professionals. Recent years have seen many high profile cyber attacks, including the WannaCry and NotPetya ransomware attacks that resulted in major financial damages to many businesses and institutions. Understanding the characteristics of such malware, including how malware can propagate and interact between systems and networks is key for mitigating these threats and containing the infection to avoid further damage. In this study, we present visualisation techniques for understanding the propagation characteristics in dynamic malware analysis. We propose the use of pixel-based visualisations to convey large-scale complex information about network hosts in a scalable and informative manner. We demonstrate our approach using a virtualised network environment, whereby we can deploy malware variants and observe their propagation behaviours. As a novel form of visualising system and network activity data across a complex environment, we can begin to understand visual signatures that can help analysts identify key characteristics of the malicious behaviours, and, therefore, provoke response and mitigation against such attacks.

scholarly journals VPNFilter Malware Analysis on Cyber Threat in Smart Home Network

2019 ◽  
Vol 9 (13) ◽  
pp. 2763 ◽  
Author(s):  
Jose Costa Sapalo Sicato ◽  
Pradip Kumar Sharma ◽  
Vincenzo Loia ◽  
Jong Hyuk Park
Keyword(s):  
Smart Home ◽  
Large Scale ◽  
Defense Mechanism ◽  
Real Life ◽  
Cyber Attacks ◽  
Malware Analysis ◽  
Home Based ◽  
Specific Objective ◽  
Cyber Threat ◽  
The Impact

Recently, the development of smart home technologies has played a crucial role in enhancing several real-life smart applications. They help improve the quality of life through systems designed to enhance convenience, comfort, entertainment, health of the householders, and security. Note, however, that malware attacks on smart home devices are increasing in frequency and volume. As people seek to improve and optimize comfort in their home and minimize their daily home responsibilities at the same time, this makes them attractive targets for a malware attack. Thus, attacks on smart home-based devices have emerged. The goals of this paper are to analyze the different aspects of cyber-physical threats on the smart home from a security perspective, discuss the types of attacks including advanced cyber-attacks and cyber-physical system attacks, and evaluate the impact on a smart home system in daily life. We have come up with a taxonomy focusing on cyber threat attacks that can also have potential impact on a smart home system and identify some key issues about VPNFilter malware that constitutes large-scale Internet of Things (IoT)-based botnet malware infection. We also discuss the defense mechanism against this threat and mention the most infected routers. The specific objective of this paper is to provide efficient task management and knowledge related to VPNFilter malware attack.

scholarly journals Malware Detection Based on Code Visualization and Two-Level Classification

Information ◽  
2021 ◽  
Vol 12 (3) ◽  
pp. 118
Author(s):  
Vassilios Moussas ◽  
Antonios Andreatos
Keyword(s):  
Web Applications ◽  
Detection System ◽  
Malware Detection ◽  
Image Features ◽  
Malicious Code ◽  
Malware Analysis ◽  
Malicious Software ◽  
Antivirus Software ◽  
Malware Classification ◽  
Artificial Neural Network Ann

Malware creators generate new malicious software samples by making minor changes in previously generated code, in order to reuse malicious code, as well as to go unnoticed from signature-based antivirus software. As a result, various families of variations of the same initial code exist today. Visualization of compiled executables for malware analysis has been proposed several years ago. Visualization can greatly assist malware classification and requires neither disassembly nor code execution. Moreover, new variations of known malware families are instantly detected, in contrast to traditional signature-based antivirus software. This paper addresses the problem of identifying variations of existing malware visualized as images. A new malware detection system based on a two-level Artificial Neural Network (ANN) is proposed. The classification is based on file and image features. The proposed system is tested on the ‘Malimg’ dataset consisting of the visual representation of well-known malware families. From this set some important image features are extracted. Based on these features, the ANN is trained. Then, this ANN is used to detect and classify other samples of the dataset. Malware families creating a confusion are classified by a second level of ANNs. The proposed two-level ANN method excels in simplicity, accuracy, and speed; it is easy to implement and fast to run, thus it can be applied to antivirus software, smart firewalls, web applications, etc.

scholarly journals Comparison of Different Analytical Methods for the On-Site Analysis of Traces at Clandestine Drug Laboratories

2021 ◽  
Vol 11 (9) ◽  
pp. 3754
Author(s):  
René Reiss ◽  
Frank Hauser ◽  
Sven Ehlert ◽  
Michael Pütz ◽  
Ralf Zimmermann
Keyword(s):  
Large Scale ◽  
Ambient Pressure ◽  
Relevant Information ◽  
Information Value ◽  
Site Analysis ◽  
Complex Information ◽  
Skilled Operator ◽  
Validation Parameters ◽  
Clandestine Laboratories ◽  
To Receive

While fast and reliable analytical results are crucial for first responders to make adequate decisions, these can be difficult to establish, especially at large-scale clandestine laboratories. To overcome this issue, multiple techniques at different levels of complexity are available. In addition to the level of complexity their information value differs as well. Within this publication, a comparison between three techniques that can be applied for on-site analysis is performed. These techniques range from ones with a simple yes or no response to sophisticated ones that allows to receive complex information about a sample. The three evaluated techniques are immunoassay drug tests representing easy to handle and fast to explain systems, ion mobility spectrometry as state-of-the-art equipment that needs training and experience prior to use and ambient pressure laser desorption with the need for a highly skilled operator as possible future technique that is currently under development. In addition to the measurement of validation parameters, real case samples are investigated to obtain practically relevant information about the capabilities and limitations of these techniques for on-site operations. Results demonstrate that in general all techniques deliver valid results, but the bandwidth of information widely varies between the investigated techniques.

The academic profession in Russia’s two capitals: The impact of 20 years of transition

2017 ◽  
Vol 16 (5) ◽  
pp. 626-644 ◽  
Author(s):  
Elizaveta Sivak ◽  
Maria Yudkevich
Keyword(s):  
Large Scale ◽  
Academic Career ◽  
Academic Profession ◽  
University Faculty ◽  
Key Characteristics ◽  
Personal Strain ◽  
High Degree ◽  
The Impact ◽  
Russian Universities

This paper studies the dynamics of key characteristics of the academic profession in Russia based on the analysis of university faculty in the two largest cities in Russia – Moscow and St Petersburg. We use data on Russian university faculty from two large-scale comparative studies of the academic profession (‘The Carnegie Study’ carried out in 1992 in 14 countries, including Russia, and ‘The Changing Academic Profession Study’, 2007–2012, with 19 participating countries and which Russia joined in 2012) to look at how faculty’s characteristics and attitudes toward different aspects of their academic life changed over 20 years (1992–2011) such as faculty’s views on reasons to leave or to stay at a university, on university’s management and the role of faculty in decision making. Using the example of universities in the two largest Russian cities, we demonstrate that the high degree of overall centralization of governance in Russian universities barely changed in 20 years. Our paper provides comparisons of teaching/research preferences and views on statements concerning personal strain associated with work, academic career perspectives, etc., not only in Russian universities between the years 1992 and 2012, but also in Russia and other ‘Changing Academic Profession’ countries.

So what's new? A survey of the education policies of orchestras and opera companies

1996 ◽  
Vol 13 (3) ◽  
pp. 259-270 ◽  
Author(s):  
Julia Winterson
Keyword(s):  
Large Scale ◽  
Full Scale ◽  
School Teachers ◽  
Education Policies ◽  
Art Galleries ◽  
High Profile ◽  
Creative Music ◽  
Direct Support

Originally, the creative music workshop involving professional players was intended to give direct support to school teachers and to enhance music in the classroom, but today's large-scale, high-profile projects mounted by orchestras and opera companies appear to be developing into a full-scale industry on their own. Their role in partnership with schools and colleges now requires clarification: a survey of education policies has revealed some confusion of aims with few bodies looking closely at objectives, outcomes and effects. Music companies could profit from the experience of museums and art galleries.

Digital Mega-Studies as a New Research Paradigm: Governing the Health Research of the Future

2021 ◽  
pp. 155626462110414
Author(s):  
Jessica Bell ◽  
Megan Prictor ◽  
Lauren Davenport ◽  
Lynda O’Brien ◽  
Melissa Wake
Keyword(s):  
Large Scale ◽  
Group Processes ◽  
Research Paradigm ◽  
Multiple Sources ◽  
Individual Level ◽  
Key Characteristics ◽  
Governance Challenges ◽  
Technological Developments ◽  
Multi Stakeholder ◽  
New Research

‘Digital Mega-Studies’ are entirely or extensively digitised, longitudinal, population-scale initiatives, collecting, storing, and making available individual-level research data of different types and from multiple sources, shaped by technological developments and unforeseeable risks over time. The Australian ‘Gen V’ project exemplifies this new research paradigm. In 2019, we undertook a multidisciplinary, multi-stakeholder process to map Digital Mega-Studies’ key characteristics, legal and governance challenges and likely solutions. We conducted large and small group processes within a one-day symposium and directed online synthesis and group prioritisation over subsequent weeks. We present our methods (including elicitation, affinity mapping and prioritisation processes) and findings, proposing six priority governance principles across three areas—data, participation, trust—to support future high-quality, large-scale digital research in health.

Societal discontent will increase in Bahrain

2021 ◽  
Keyword(s):  
Large Scale ◽  
Political Representation ◽  
Social Protest ◽  
Small Scale ◽  
Content Type ◽  
High Profile ◽  
Arab Uprisings ◽  
Base Level

Significance Although large-scale social protest in Bahrain has been cowed over the ten years since the ‘Arab uprisings’, small-scale demonstrations recur, reflecting a base level of discontent. Mobilising issues include economic pressures, limited political representation (especially of the Shia majority) and, most recently, ties with Israel. Impacts Despite protests, Israel’s and Bahrain’s respective ambassadors will keep up high-profile activity and statements. The authorities are likely to exaggerate the role of Iranian interference in order to deepen the Sunni-Shia divide. If Riyadh manages to extricate itself from the Yemen war, that could partly reduce the pressure on Manama.

Enriching Activity-Based Models using Smartphone-Based Travel Surveys

2018 ◽  
Vol 2672 (42) ◽  
pp. 280-291 ◽  
Author(s):  
Bat-hen Nahmias-Biran ◽  
Yafei Han ◽  
Shlomo Bekhor ◽  
Fang Zhao ◽  
Christopher Zegras ◽  
...  
Keyword(s):  
Travel Behavior ◽  
Large Scale ◽  
Leisure Activities ◽  
Behavior Modeling ◽  
Machine Learning Techniques ◽  
Initial Field ◽  
Activity Data ◽  
Large Variability ◽  
Tel Aviv ◽  
Household Travel Surveys

Smartphone-based travel surveys have attracted much attention recently, for their potential to improve data quality and response rate. One of the first such survey systems, Future Mobility Sensing (FMS), leverages sensors on smartphones, and machine learning techniques to collect detailed personal travel data. The main purpose of this research is to compare data collected by FMS and traditional methods, and study the implications of using FMS data for travel behavior modeling. Since its initial field test in Singapore, FMS has been used in several large-scale household travel surveys, including one in Tel Aviv, Israel. We present comparative analyses that make use of the rich datasets from Singapore and Tel Aviv, focusing on three main aspects: (1) richness in activity behaviors observed, (2) completeness of travel and activity data, and (3) data accuracy. Results show that FMS has clear advantages over traditional travel surveys: it has higher resolution and better accuracy of times, locations, and paths; FMS represents out-of-work and leisure activities well; and reveals large variability in day-to-day activity pattern, which is inadequately captured in a one-day snapshot in typical traditional surveys. FMS also captures travel and activities that tend to be under-reported in traditional surveys such as multiple stops in a tour and work-based sub-tours. These richer and more complete and accurate data can improve future activity-based modeling.

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