Grand Challenges for Embedded Security Research in a Connected World
- URL: http://arxiv.org/abs/2005.06585v1
- Date: Wed, 13 May 2020 21:01:57 GMT
- Title: Grand Challenges for Embedded Security Research in a Connected World
- Authors: Wayne Burleson, Kevin Fu, Denise Anthony, Jorge Guajardo, Carl Gunter,
Kyle Ingols, Jean-Baptiste Jeannin, Farinaz Koushanafar, Carl Landwehr, and
Susan Squires
- Abstract summary: The Computing Community Consortium (CCC) held a one-day visioning workshop to explore these issues.
Report synthesizes the results of that workshop and develops a list of strategic goals for research and education over the next 5-10 years.
- Score: 6.1916614285252
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Protecting embedded security is becoming an increasingly challenging research
problem for embedded systems due to a number of emerging trends in hardware,
software, networks, and applications. Without fundamental advances in, and an
understanding of embedded security it will be difficult for future engineers to
provide assurance for the Internet of Things (IoT) and Operational Technology
(OT) in wide ranging applications, from home automation and autonomous
transportation to medical devices and factory floors. Common to such
applications are cyberphysical risks and consequences stemming from a lack of
embedded security. The Computing Community Consortium (CCC) held a one-day
visioning workshop to explore these issues. The workshop focused on five major
application areas of embedded systems, namely (1) medical/wearable devices, (2)
autonomous systems (drones, vehicles, robots), (3) smart homes, (4) industry
and supply chain, and (5) critical infrastructure. This report synthesizes the
results of that workshop and develops a list of strategic goals for research
and education over the next 5-10 years.
Embedded security in connected devices presents challenges that require a
broad look at the overall systems design, including human and societal
dimensions as well as technical. Particular issues related to embedded security
are a subset of the overall security of the application areas, which must also
balance other design criteria such as cost, power, reliability, usability and
function. Recent trends are converging to make the security of embedded systems
an increasingly important and difficult objective, requiring new
trans-disciplinary approaches to solve problems on a 5-10 year horizon.
Related papers
- Adaptive Lightweight Security for Performance Efficiency in Critical Healthcare Monitoring [1.1874952582465603]
The Internet of Things (IoT) with its diverse technologies has become an integral component of future healthcare systems.
The evolving healthcare paradigm requires adaptive security procedures and technologies that can adapt to the varying resource constraints of IoT devices.
This article brings forth the unique healthcare monitoring requirements and studies the existing encryption-based security approaches to provide the necessary security.
arXiv Detail & Related papers (2024-06-06T06:55:16Z) - The Security and Privacy of Mobile Edge Computing: An Artificial Intelligence Perspective [64.36680481458868]
Mobile Edge Computing (MEC) is a new computing paradigm that enables cloud computing and information technology (IT) services to be delivered at the network's edge.
This paper provides a survey of security and privacy in MEC from the perspective of Artificial Intelligence (AI)
We focus on new security and privacy issues, as well as potential solutions from the viewpoints of AI.
arXiv Detail & Related papers (2024-01-03T07:47:22Z) - Multi-Tier Computing-Enabled Digital Twin in 6G Networks [50.236861239246835]
In Industry 4.0, industries such as manufacturing, automotive, and healthcare are rapidly adopting DT-based development.
The main challenges to date have been the high demands on communication and computing resources, as well as privacy and security concerns.
To achieve low latency and high security services in the emerging DT, multi-tier computing has been proposed by combining edge/fog computing and cloud computing.
arXiv Detail & Related papers (2023-12-28T13:02:53Z) - Blockchain-Based Security Architecture for Unmanned Aerial Vehicles in B5G/6G Services and Beyond: A Comprehensive Approach [4.552065156611815]
Unmanned Aerial Vehicles (UAVs) have evolved into indispensable tools for effectively managing disasters and responding to emergencies.
It is substantial to identify and consider the different security challenges in the research and development associated with advanced UAV-based B5G/6G architectures.
arXiv Detail & Related papers (2023-12-12T01:55:04Z) - A Survey of the Security Challenges and Requirements for IoT Operating Systems [0.0]
The Internet of Things (IoT) is becoming an integral part of our modern lives as we converge towards a world surrounded by ubiquitous connectivity.
The inherent complexity presented by the vast IoT ecosystem ends up in an insufficient understanding of individual system components and their interactions.
There is a need for a unifying operating system (OS) that can act as a cornerstone regulating the development of stable and secure solutions.
arXiv Detail & Related papers (2023-10-27T19:19:07Z) - Proceedings of the Artificial Intelligence for Cyber Security (AICS)
Workshop at AAAI 2022 [55.573187938617636]
The workshop will focus on the application of AI to problems in cyber security.
Cyber systems generate large volumes of data, utilizing this effectively is beyond human capabilities.
arXiv Detail & Related papers (2022-02-28T18:27:41Z) - Inspect, Understand, Overcome: A Survey of Practical Methods for AI
Safety [54.478842696269304]
The use of deep neural networks (DNNs) in safety-critical applications is challenging due to numerous model-inherent shortcomings.
In recent years, a zoo of state-of-the-art techniques aiming to address these safety concerns has emerged.
Our paper addresses both machine learning experts and safety engineers.
arXiv Detail & Related papers (2021-04-29T09:54:54Z) - Artificial Intelligence for IT Operations (AIOPS) Workshop White Paper [50.25428141435537]
Artificial Intelligence for IT Operations (AIOps) is an emerging interdisciplinary field arising in the intersection between machine learning, big data, streaming analytics, and the management of IT operations.
Main aim of the AIOPS workshop is to bring together researchers from both academia and industry to present their experiences, results, and work in progress in this field.
arXiv Detail & Related papers (2021-01-15T10:43:10Z) - A Research Ecosystem for Secure Computing [4.212354651854757]
Security of computers, systems, and applications has been an active area of research in computer science for decades.
Challenges range from security and trust of the information ecosystem to adversarial artificial intelligence and machine learning.
New incentives and education are at the core of this change.
arXiv Detail & Related papers (2021-01-04T22:42:28Z) - Dos and Don'ts of Machine Learning in Computer Security [74.1816306998445]
Despite great potential, machine learning in security is prone to subtle pitfalls that undermine its performance.
We identify common pitfalls in the design, implementation, and evaluation of learning-based security systems.
We propose actionable recommendations to support researchers in avoiding or mitigating the pitfalls where possible.
arXiv Detail & Related papers (2020-10-19T13:09:31Z) - Safety, Security, and Privacy Threats Posed by Accelerating Trends in
the Internet of Things [13.286330786426278]
The Internet of Things (IoT) is already transforming industries, cities, and homes.
The economic value of this transformation across all industries is estimated to be trillions of dollars.
Alongside potential benefits of interconnected smart devices comes increased risk and potential for abuse.
arXiv Detail & Related papers (2020-07-31T18:04:20Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.