385 research outputs found
Cybersecurity: Past, Present and Future
The digital transformation has created a new digital space known as
cyberspace. This new cyberspace has improved the workings of businesses,
organizations, governments, society as a whole, and day to day life of an
individual. With these improvements come new challenges, and one of the main
challenges is security. The security of the new cyberspace is called
cybersecurity. Cyberspace has created new technologies and environments such as
cloud computing, smart devices, IoTs, and several others. To keep pace with
these advancements in cyber technologies there is a need to expand research and
develop new cybersecurity methods and tools to secure these domains and
environments. This book is an effort to introduce the reader to the field of
cybersecurity, highlight current issues and challenges, and provide future
directions to mitigate or resolve them. The main specializations of
cybersecurity covered in this book are software security, hardware security,
the evolution of malware, biometrics, cyber intelligence, and cyber forensics.
We must learn from the past, evolve our present and improve the future. Based
on this objective, the book covers the past, present, and future of these main
specializations of cybersecurity. The book also examines the upcoming areas of
research in cyber intelligence, such as hybrid augmented and explainable
artificial intelligence (AI). Human and AI collaboration can significantly
increase the performance of a cybersecurity system. Interpreting and explaining
machine learning models, i.e., explainable AI is an emerging field of study and
has a lot of potentials to improve the role of AI in cybersecurity.Comment: Author's copy of the book published under ISBN: 978-620-4-74421-
Lux junior 2023: 16. Internationales Forum für den lichttechnischen Nachwuchs, 23. – 25. Juni 2023, Ilmenau : Tagungsband
Während des 16. Internationales Forums für den lichttechnischen Nachwuchs präsentieren Studenten, Doktoranden und junge Absolventen ihre Forschungs- und Entwicklungsergebnisse aus allen Bereichen der Lichttechnik. Die Themen bewegen sich dabei von Beleuchtungsanwendungen in verschiedensten Bereichen über Lichtmesstechnik, Kraftfahrzeugbeleuchung, LED-Anwendung bis zu nichtvisuellen Lichtwirkungen. Das Forum ist speziell für Studierende und junge Absolventen des Lichtbereiches konzipiert. Es bietet neben den Vorträgen und Postern die Möglichkeit zu Diskussionen und individuellem Austausch. In den 30 Jahren ihres Bestehens entwickelte sich die zweijährig stattfindende Tagung zu eine Traditionsveranstaltung, die das Fachgebiet Lichttechnik der TU Ilmenau gemeinsam mit der Bezirksgruppe Thüringen-Nordhessen der Deutschen Lichttechnischen Gesellschaft LiTG e. V. durchführt
Milestones in Autonomous Driving and Intelligent Vehicles Part \uppercase\expandafter{\romannumeral1}: Control, Computing System Design, Communication, HD Map, Testing, and Human Behaviors
Interest in autonomous driving (AD) and intelligent vehicles (IVs) is growing
at a rapid pace due to the convenience, safety, and economic benefits. Although
a number of surveys have reviewed research achievements in this field, they are
still limited in specific tasks and lack systematic summaries and research
directions in the future. Our work is divided into 3 independent articles and
the first part is a Survey of Surveys (SoS) for total technologies of AD and
IVs that involves the history, summarizes the milestones, and provides the
perspectives, ethics, and future research directions. This is the second part
(Part \uppercase\expandafter{\romannumeral1} for this technical survey) to
review the development of control, computing system design, communication, High
Definition map (HD map), testing, and human behaviors in IVs. In addition, the
third part (Part \uppercase\expandafter{\romannumeral2} for this technical
survey) is to review the perception and planning sections. The objective of
this paper is to involve all the sections of AD, summarize the latest technical
milestones, and guide abecedarians to quickly understand the development of AD
and IVs. Combining the SoS and Part \uppercase\expandafter{\romannumeral2}, we
anticipate that this work will bring novel and diverse insights to researchers
and abecedarians, and serve as a bridge between past and future.Comment: 18 pages, 4 figures, 3 table
University of Windsor Undergraduate Calendar 2023 Spring
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Performance analysis of real-time and general-purpose operating systems for path planning of the multi-robot systems
In general, modern operating systems can be divided into two essential parts, real-time operating systems (RTOS) and general-purpose operating systems (GPOS). The main difference between GPOS and RTOS is the system istime-critical or not. It means that; in GPOS, a high-priority thread cannot preempt a kernel call. But, in RTOS, a low-priority task is preempted by a high-priority task if necessary, even if it’s executing a kernel call. Most Linux distributions can be used as both GPOS and RTOS with kernel modifications. In this study, two Linux distributions, Ubuntu and Pardus, were analyzed and their performances were compared both as GPOS and RTOS for path planning of the multi-robot systems. Robot groups with different numbers of members were used to perform the path tracking tasks using both Ubuntu and Pardus as GPOS and RTOS. In this way, both the performance of two different Linux distributions in robotic applications were observed and compared in two forms, GPOS, and RTOS
A Software Vulnerabilities Odysseus: Analysis, Detection, and Mitigation
Programming has become central in the development of human activities while not
being immune to defaults, or bugs. Developers have developed specific methods and
sequences of tests that they implement to prevent these bugs from being deployed in
releases. Nonetheless, not all cases can be thought through beforehand, and automation
presents limits the community attempts to overcome. As a consequence, not all bugs
can be caught.
These defaults are causing particular concerns in case bugs can be exploited to
breach the program’s security policy. They are then called vulnerabilities and provide
specific actors with undesired access to the resources a program manages. It damages
the trust in the program and in its developers, and may eventually impact the adoption
of the program. Hence, to attribute a specific attention to vulnerabilities appears as a
natural outcome. In this regard, this PhD work targets the following three challenges:
(1) The research community references those vulnerabilities, categorises them, reports
and ranks their impact. As a result, analysts can learn from past vulnerabilities in
specific programs and figure out new ideas to counter them. Nonetheless, the resulting
quality of the lessons and the usefulness of ensuing solutions depend on the quality and
the consistency of the information provided in the reports.
(2) New methods to detect vulnerabilities can emerge among the teachings this
monitoring provides. With responsible reporting, these detection methods can provide
hardening of the programs we rely on. Additionally, in a context of computer perfor-
mance gain, machine learning algorithms are increasingly adopted, providing engaging
promises.
(3) If some of these promises can be fulfilled, not all are not reachable today.
Therefore a complementary strategy needs to be adopted while vulnerabilities evade
detection up to public releases. Instead of preventing their introduction, programs can
be hardened to scale down their exploitability. Increasing the complexity to exploit
or lowering the impact below specific thresholds makes the presence of vulnerabilities
an affordable risk for the feature provided. The history of programming development
encloses the experimentation and the adoption of so-called defence mechanisms. Their
goals and performances can be diverse, but their implementation in worldwide adopted
programs and systems (such as the Android Open Source Project) acknowledges their
pivotal position.
To face these challenges, we provide the following contributions:
• We provide a manual categorisation of the vulnerabilities of the worldwide adopted
Android Open Source Project up to June 2020. Clarifying to adopt a vulnera-
bility analysis provides consistency in the resulting data set. It facilitates the
explainability of the analyses and sets up for the updatability of the resulting
set of vulnerabilities. Based on this analysis, we study the evolution of AOSP’s
vulnerabilities. We explore the different temporal evolutions of the vulnerabilities affecting the system for their severity, the type of vulnerability, and we provide a
focus on memory corruption-related vulnerabilities.
• We undertake the replication of a machine-learning based detection algorithms
that, besides being part of the state-of-the-art and referenced to by ensuing works,
was not available. Named VCCFinder, this algorithm implements a Support-
Vector Machine and bases its training on Vulnerability-Contributing Commits
and related patches for C and C++ code. Not in capacity to achieve analogous
performances to the original article, we explore parameters and algorithms, and
attempt to overcome the challenge provided by the over-population of unlabeled
entries in the data set. We provide the community with our code and results as a
replicable baseline for further improvement.
• We eventually list the defence mechanisms that the Android Open Source Project
incrementally implements, and we discuss how it sometimes answers comments
the community addressed to the project’s developers. We further verify the extent
to which specific memory corruption defence mechanisms were implemented in the
binaries of different versions of Android (from API-level 10 to 28). We eventually
confront the evolution of memory corruption-related vulnerabilities with the
implementation timeline of related defence mechanisms
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