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Bako Ali

Bio: Bako Ali is an academic researcher from Luleå University of Technology. The author has contributed to research in topics: Physical security & Asset (computer security). The author has an hindex of 1, co-authored 1 publications receiving 150 citations.

Papers
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Journal ArticleDOI
08 Mar 2018-Sensors
TL;DR: The key goals of this study are to highlight the various security vulnerabilities of IoT-based smart homes, to present the risks on home inhabitants, and to propose approaches to mitigating the identified risks.
Abstract: The Internet of Things (IoT) is an emerging paradigm focusing on the connection of devices, objects, or "things" to each other, to the Internet, and to users. IoT technology is anticipated to become an essential requirement in the development of smart homes, as it offers convenience and efficiency to home residents so that they can achieve better quality of life. Application of the IoT model to smart homes, by connecting objects to the Internet, poses new security and privacy challenges in terms of the confidentiality, authenticity, and integrity of the data sensed, collected, and exchanged by the IoT objects. These challenges make smart homes extremely vulnerable to different types of security attacks, resulting in IoT-based smart homes being insecure. Therefore, it is necessary to identify the possible security risks to develop a complete picture of the security status of smart homes. This article applies the operationally critical threat, asset, and vulnerability evaluation (OCTAVE) methodology, known as OCTAVE Allegro, to assess the security risks of smart homes. The OCTAVE Allegro method focuses on information assets and considers different information containers such as databases, physical papers, and humans. The key goals of this study are to highlight the various security vulnerabilities of IoT-based smart homes, to present the risks on home inhabitants, and to propose approaches to mitigating the identified risks. The research findings can be used as a foundation for improving the security requirements of IoT-based smart homes.

236 citations


Cited by
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Journal ArticleDOI
TL;DR: Recent and in-depth research of relevant works that deal with several intelligent techniques and their applied intrusion detection architectures in computer networks with emphasis on the Internet of Things and machine learning are aimed at.

299 citations

Journal ArticleDOI
24 Aug 2018-Sensors
TL;DR: This paper is presenting an overview about different layered architectures of IoT and attacks regarding security from the perspective of layers, and suggested a new secure layered architecture of IoT to overcome these issues.
Abstract: The use of the Internet is growing in this day and age, so another area has developed to use the Internet, called Internet of Things (IoT). It facilitates the machines and objects to communicate, compute and coordinate with each other. It is an enabler for the intelligence affixed to several essential features of the modern world, such as homes, hospitals, buildings, transports and cities. The security and privacy are some of the critical issues related to the wide application of IoT. Therefore, these issues prevent the wide adoption of the IoT. In this paper, we are presenting an overview about different layered architectures of IoT and attacks regarding security from the perspective of layers. In addition, a review of mechanisms that provide solutions to these issues is presented with their limitations. Furthermore, we have suggested a new secure layered architecture of IoT to overcome these issues.

294 citations

Journal ArticleDOI
01 Dec 2018
TL;DR: A comprehensive survey of the latest IDSs designed for the IoT model, with a focus on the corresponding methods, features, and mechanisms, and deep insight into the IoT architecture, emerging security vulnerabilities, and their relation to the layers of the IoT Architecture is provided.
Abstract: One of the goals of smart environments is to improve the quality of human life in terms of comfort and efficiency. The Internet of Things (IoT) paradigm has recently evolved into a technology for building smart environments. Security and privacy are considered key issues in any real-world smart environment based on the IoT model. The security vulnerabilities in IoT-based systems create security threats that affect smart environment applications. Thus, there is a crucial need for intrusion detection systems (IDSs) designed for IoT environments to mitigate IoT-related security attacks that exploit some of these security vulnerabilities. Due to the limited computing and storage capabilities of IoT devices and the specific protocols used, conventional IDSs may not be an option for IoT environments. This article presents a comprehensive survey of the latest IDSs designed for the IoT model, with a focus on the corresponding methods, features, and mechanisms. This article also provides deep insight into the IoT architecture, emerging security vulnerabilities, and their relation to the layers of the IoT architecture. This work demonstrates that despite previous studies regarding the design and implementation of IDSs for the IoT paradigm, developing efficient, reliable and robust IDSs for IoT-based smart environments is still a crucial task. Key considerations for the development of such IDSs are introduced as a future outlook at the end of this survey.

240 citations

Journal ArticleDOI
TL;DR: This paper provides an in-depth survey about the social engineering attacks, their classifications, detection strategies, and prevention procedures.
Abstract: The advancements in digital communication technology have made communication between humans more accessible and instant. However, personal and sensitive information may be available online through social networks and online services that lack the security measures to protect this information. Communication systems are vulnerable and can easily be penetrated by malicious users through social engineering attacks. These attacks aim at tricking individuals or enterprises into accomplishing actions that benefit attackers or providing them with sensitive data such as social security number, health records, and passwords. Social engineering is one of the biggest challenges facing network security because it exploits the natural human tendency to trust. This paper provides an in-depth survey about the social engineering attacks, their classifications, detection strategies, and prevention procedures.

200 citations

Journal ArticleDOI
01 Jun 2021
TL;DR: A taxonomy that taps into the three-layer IoT architecture as a reference to identify security properties and requirements for each layer is built upon, classifying the potential IoT security threat and challenges by an architectural view.
Abstract: Internet of Things (IoT) is one of the most promising technologies that aims to enhance humans’ quality of life (QoL). IoT plays a significant role in several fields such as healthcare, automotive industries, agriculture, education, and many cross-cutting business applications. Addressing and analyzing IoT security issues is crucial because the working mechanisms of IoT applications vary due to the heterogeneity nature of IoT environments. Therefore, discussing the IoT security concerns in addition to available and potential solutions would assist developers and enterprises to find appropriate and timely solutions to tackle specific threats, providing the best possible IoT-based services. This paper provides a comprehensive study on IoT security issues, limitations, requirements, and current and potential solutions. The paper builds upon a taxonomy that taps into the three-layer IoT architecture as a reference to identify security properties and requirements for each layer. The main contribution of this survey is classifying the potential IoT security threat and challenges by an architectural view. From there, IoT security challenges and solutions are further grouped by the layered architecture for readers to get a better understanding on how to address and adopt best practices to avoid the current IoT security threats on each layer.

187 citations