1,445 research outputs found
Forensic investigation of small-scale digital devices: a futuristic view
Small-scale digital devices like smartphones, smart toys, drones, gaming consoles, tablets, and other personal data assistants have now become ingrained constituents in our daily lives. These devices store massive amounts of data related to individual traits of users, their routine operations, medical histories, and financial information. At the same time, with continuously evolving technology, the diversity in operating systems, client storage localities, remote/cloud storages and backups, and encryption practices renders the forensic analysis task multi-faceted. This makes forensic investigators having to deal with an array of novel challenges. This study reviews the forensic frameworks and procedures used in investigating small-scale digital devices. While highlighting the challenges faced by digital forensics, we explore how cutting-edge technologies like Blockchain, Artificial Intelligence, Machine Learning, and Data Science may play a role in remedying concerns. The review aims to accumulate state-of-the-art and identify a futuristic approach for investigating SSDDs
Forensic Authentication of WhatsApp Messenger Using the Information Retrieval Approach
The development of telecommunications has increased very rapidly since the internet-based instant messaging service has spread rapidly to Indonesia. WhatsApp is the most popular instant messaging application compared to other instant messaging services, according to the statista website users of WhatsApp services in 2018 showed significant growth by gathering 1.5 billion monthly active users or monthly active users (MAU). That number increased 14 percent compared to MAU WhatsApp in July 2017 which amounted to 1.3 billion. Daily active users aka DAU are in the range of one billion. WhatsApp handles more than 60 billion message exchanges between users around the world. This growth is predicted to continue to increase, along with the wider internet penetration. Along with WhatsApp updates with various features embedded in this application including Web-based Whatsapp for computers, this feature makes it easier for users to share data and can be synchronized with their smartphone or user's computer. Besides the positive side found in the application, WhatsApp also provides a security gap for user privacy, one of which is tapping conversations involving both smartphone and computer devices. The handling of crimes involving digital devices needs to be emphasized so that they can help the judicial process of the effects they have caused Mobile Forensics Investigation also took part in suppressing the misuse of WhatsApp's instant messaging service features, including investigating the handling of cases of WhatsApp conversations through a series of standard steps according to digital forensics procedures. Exploration of evidence (digital evidence) WhatsApp conversations will be a reference to the crime of telecommunication tapping which will then be carried out forensic investigation report involving evidence of the smartphone and computer of the victim.
Keywords: Authentication, Mobile Forensics, Instant Messenger, and WhatsApp Messenger
The Digital Detective\u27s Discourse - A toolset for forensically sound collaborative dark web content annotation and collection
In the last decade, the proliferation of machine learning (ML) algorithms and their application on big data sets have benefited many researchers and practitioners in different scientific areas. Consequently, the research in cybercrime and digital forensics has relied on ML techniques and methods for analyzing large quantities of data such as text, graphics, images, videos, and network traffic scans to support criminal investigations. Complete and accurate training data sets are indispensable for efficient and effective machine learning models. An essential part of creating complete and accurate data sets is annotating or labelling data. We present a method for law enforcement agency investigators to annotate and store specific dark web content. Using a design science strategy, we design and develop tools to enable and extend web content annotation. The annotation tool was implemented as a plugin for the Tor browser. It can store web content, thus automatically creating a dataset of dark web data pertinent to criminal investigations. Combined with a central storage management server, enabling annotation sharing and collaboration, and a web scraping program, the dataset becomes multifold, dynamic, and extensive while maintaining the forensic soundness of the data saved and transmitted. To manifest our toolset\u27s fitness of purpose, we used our dataset as training data for ML based classification models. A five cross-fold validation technique was used to evaluate the classifiers, which reported an accuracy score of 85 - 96%. In the concluding sections, we discuss the possible use-cases of the proposed method in real-life cybercrime investigations, along with ethical concerns and future extensions
Cognitive-Behavioral Therapy for Treating Videogame Dependence in School-aged Children
This study examined the effectiveness of cognitive-behaviour therapy on schoolchildren with videogame dependency in a sample of Nigerian schoolchildren. This study was conducted in Enugu metropolis Enugu State Nigeria. A randomized-controlled pretest and posttest design was adopted. Out of 86 schoolchildren that participated in the study, 43 children were exposed to the intervention while 43 did not receive treatment as usual (TAU). The treatment lasted for eight weeks with one session per week. During the study, the participants were assessed at three time points using videogame addiction scale for children. The data collected were statistically analyzed using the multivariate statistical tool. The multivariate statistical result showed that cognitive-behaviour therapy in reducing videogame dependency among schoolchildren. The practice implications, limitations, and conclusions were also drawn in line with the outcome of this study. This study is one among the few studies in Nigeria that have investigated videogame dependency. Another strength is that study tested the participants at three time points to ascertain the impacts of the intervention
Computer Crime and Control in Hong Kong
This Article is a first attempt to study cyberspace governance and computer crime control in Hong Kong. It begins with a discussion of how computer crime was discovered as a cognizable object of control. Next, it explores the nature, prevalence and distribution of computer crime in Hong Kong before embarking on a comprehensive review and critical analysis of the Hong Kong government\u27s cyberspace governance philosophy and computer crime control policy. The Article closes with a number of recommendations for improving Hong Kong cyberspace governance, which focus on developing a broad, overarching policy that both meets the public\u27s goals and addresses private sector concerns
Artificial Intelligence, Smart Class Rooms and Online Education in the 21st Century: Implications for Human Development.
While the advent of Artificial Intelligence (AI) technologies in the education sector has largely taken
over conventional class rooms and revolutionize the way education is conducted in the 21st century
to the admiration of many, there are scholars who believe it is too early to celebrate the benefits of
AI in the education sector, since modern AI teaching systems now raises long‐term issues about the
place of the teacher in AI education. The Marxist Alienation theory was considered for this paper.
The Ex‐post factor method of analysis and Deidra’s critical analytic method was utilized for attaining
the objectives of the paper. The paper faults recent attempts at eulogizing the impact of AI in the
education sector and on human development. Extensive research is proposed as necessary for
contemporary scholars in the field of AI and education technology before proper appropriation is
made of its gains in education and human development
An Artist’s Expert System: second order cybernetics for matching users to bespoke books
All books should be intelligent, but how can books be produced which use computerised systems and analytical methods, processes more commonly deployed in business intelligence or medicine, to analyse readers and learn from them? This paper investigates the use of an Expert System for matching users to bespoke books.
The author’s artistic practice is concerned with the interface of technology and storytelling, the work presented here is used as a case study,investigating the limits and possibilities of Good Old Fashioned Artificial Intelligence and its presence within an art and design context, as well as outlining the process and intentions of developing an intelligent system for matching users to books
Impact and key challenges of insider threats on organizations and critical businesses
The insider threat has consistently been identified as a key threat to organizations and governments. Understanding the nature of insider threats and the related threat landscape can help in forming mitigation strategies, including non-technical means. In this paper, we survey and highlight challenges associated with the identification and detection of insider threats in both public and private sector organizations, especially those part of a nation’s critical infrastructure. We explore the utility of the cyber kill chain to understand insider threats, as well as understanding the underpinning human behavior and psychological factors. The existing defense techniques are discussed and critically analyzed, and improvements are suggested, in line with the current state-of-the-art cyber security requirements. Finally, open problems related to the insider threat are identified and future research directions are discussed
Safeguarding the Evidential Value of Forensic Cryptocurrency Investigations
Analyzing cryptocurrency payment flows has become a key forensic method in
law enforcement and is nowadays used to investigate a wide spectrum of criminal
activities. However, despite its widespread adoption, the evidential value of
obtained findings in court is still largely unclear. In this paper, we focus on
the key ingredients of modern cryptocurrency analytics techniques, which are
clustering heuristics and attribution tags. We identify internationally
accepted standards and rules for substantiating suspicions and providing
evidence in court and project them onto current cryptocurrency forensics
practices. By providing an empirical analysis of CoinJoin transactions, we
illustrate possible sources of misinterpretation in algorithmic clustering
heuristics. Eventually, we derive a set of legal key requirements and translate
them into a technical data sharing framework that fosters compliance with
existing legal and technical standards in the realm of cryptocurrency
forensics. Integrating the proposed framework in modern cryptocurrency
analytics tools could allow more efficient and effective investigations, while
safeguarding the evidential value of the analysis and the fundamental rights of
affected persons
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