Best Practices for Facing the Security Challenges of Internet of Things Devices Focusing on Software Development Life Cycle

• URL: http://arxiv.org/abs/2402.07832v1
• Date: Mon, 12 Feb 2024 17:43:02 GMT
• Title: Best Practices for Facing the Security Challenges of Internet of Things Devices Focusing on Software Development Life Cycle
• Authors: Md Rafid Islam, Ratun Rahman
• Abstract summary: Security for IoT devices is now a top priority due to the growing number of threats. The objective of the study is to raise awareness of potential threats, emphasizing the secure software development lifecycle. The study will also serve as a point of reference for future developments.
• Score: 0.0
• License: http://creativecommons.org/publicdomain/zero/1.0/
• Abstract: In the past few years, the number of IoT devices has grown substantially, and this trend is likely to continue. An increasing amount of effort is being put into developing software for the ever-increasing IoT devices. Every IoT system at its core has software that enables the devices to function efficiently. But security has always been a concern in this age of information and technology. Security for IoT devices is now a top priority due to the growing number of threats. This study introduces best practices for ensuring security in the IoT, with an emphasis on guidelines to be utilized in software development for IoT devices. The objective of the study is to raise awareness of potential threats, emphasizing the secure software development lifecycle. The study will also serve as a point of reference for future developments and provide a solid foundation for securing IoT software and dealing with vulnerabilities.

Related papers

• IoT in the Cloud: Exploring Security Challenges and Mitigations for a Connected World [18.36339203254509]
  The Internet of Things (IoT) has seen remarkable advancements in recent years, leading to a paradigm shift in the digital landscape. IoT devices, inherently connected to the internet, are susceptible to various forms of attacks. IoT services often handle sensitive user data, which could be exploited by malicious actors or unauthorized service providers.
  arXiv  Detail & Related papers  (2024-02-01T05:55:43Z)
• Classification of cyber attacks on IoT and ubiquitous computing devices [49.1574468325115]
  This paper provides a classification of IoT malware. Major targets and used exploits for attacks are identified and referred to the specific malware. The majority of current IoT attacks continue to be of comparably low effort and level of sophistication and could be mitigated by existing technical measures.
  arXiv  Detail & Related papers  (2023-12-01T16:10:43Z)
• 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)
• From Generative AI to Generative Internet of Things: Fundamentals, Framework, and Outlooks [82.964958051535]
  Generative Artificial Intelligence (GAI) possesses the capabilities of generating realistic data and facilitating advanced decision-making. By integrating GAI into modern Internet of Things (IoT), Generative Internet of Things (GIoT) is emerging and holds immense potential to revolutionize various aspects of society.
  arXiv  Detail & Related papers  (2023-10-27T02:58:11Z)
• Towards Artificial General Intelligence (AGI) in the Internet of Things (IoT): Opportunities and Challenges [55.82853124625841]
  Artificial General Intelligence (AGI) possesses the capacity to comprehend, learn, and execute tasks with human cognitive abilities. This research embarks on an exploration of the opportunities and challenges towards achieving AGI in the context of the Internet of Things. The application spectrum for AGI-infused IoT is broad, encompassing domains ranging from smart grids, residential environments, manufacturing, and transportation to environmental monitoring, agriculture, healthcare, and education.
  arXiv  Detail & Related papers  (2023-09-14T05:43:36Z)
• Navigating the IoT landscape: Unraveling forensics, security issues, applications, research challenges, and future [6.422895251217666]
  This paper reviews forensic and security issues associated with IoT in different fields. Most IoT devices are vulnerable to attacks due to a lack of standardized security measures. To fulfil the security-conscious needs of consumers, IoT can be used to develop a smart home system.
  arXiv  Detail & Related papers  (2023-09-06T04:41:48Z)
• Machine and Deep Learning for IoT Security and Privacy: Applications, Challenges, and Future Directions [0.0]
  The integration of the Internet of Things (IoT) connects a number of intelligent devices with a minimum of human interference. Current security approaches can also be improved to protect the IoT environment effectively. Deep learning (DL)/ machine learning (ML) methods are essential to turn IoT systems protection from simply enabling safe contact between IoT systems to intelligence systems in security.
  arXiv  Detail & Related papers  (2022-10-24T19:02:27Z)
• Autonomous Maintenance in IoT Networks via AoI-driven Deep Reinforcement Learning [73.85267769520715]
  Internet of Things (IoT) with its growing number of deployed devices and applications raises significant challenges for network maintenance procedures. We formulate a problem of autonomous maintenance in IoT networks as a Partially Observable Markov Decision Process. We utilize Deep Reinforcement Learning algorithms (DRL) to train agents that decide if a maintenance procedure is in order or not and, in the former case, the proper type of maintenance needed.
  arXiv  Detail & Related papers  (2020-12-31T11:19:51Z)
• Smart Home, security concerns of IoT [91.3755431537592]
  The IoT (Internet of Things) has become widely popular in the domestic environments. People are renewing their homes into smart homes; however, the privacy concerns of owning many Internet connected devices with always-on environmental sensors remain insufficiently addressed. Default and weak passwords, cheap materials and hardware, and unencrypted communication are identified as the principal threats and vulnerabilities of IoT devices.
  arXiv  Detail & Related papers  (2020-07-06T10:36:11Z)
• Machine Learning Based Solutions for Security of Internet of Things (IoT): A Survey [8.108571247838206]
  IoT platforms have been developed into a global giant that grabs every aspect of our daily lives by advancing human life with its unaccountable smart services. There are existing security measures that can be applied to protect IoT. Traditional techniques are not as efficient with the advancement booms as well as different attack types and their severeness. A huge technological advancement has been noticed in Machine Learning (ML) which has opened many possible research windows to address ongoing and future challenges in IoT.
  arXiv  Detail & Related papers  (2020-04-11T03:08:24Z)
• IoT Device Identification Using Deep Learning [43.0717346071013]
  The growing use of IoT devices in organizations has increased the number of attack vectors available to attackers. The widely adopted bring your own device (BYOD) policy which allows an employee to bring any IoT device into the workplace and attach it to an organization's network also increases the risk of attacks. In this study, we applied deep learning on network traffic to automatically identify IoT devices connected to the network.
  arXiv  Detail & Related papers  (2020-02-25T12:24:49Z)

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.