1. |
- Aydin, Mustafa, et al.
(author)
-
Using Attribute-based Feature Selection Approaches and Machine Learning Algorithms for Detecting Fraudulent Website URLs
- 2020
-
In: 2020 10th Annual Computing and Communication Workshop and Conference, CCWC 2020. ; , s. 774-779
-
Conference paper (peer-reviewed)abstract
- Phishing is a malicious form of online theft and needs to be prevented in order to increase the overall trust of the public on the Internet. In this study, for that purpose, the authors present their findings on the methods of detecting phishing websites. Data mining algorithms along with classifier algorithms are used in order to achieve a satisfactory result. In terms of classifiers, the Naïve Bayes, SMO, and J48 algorithms are used. As for the feature selection algorithm; Gain Ratio Attribute and ReliefF Attribute are selected. The results are provided in a comparative way. Accordingly; SMO and J48 algorithms provided satisfactory results in the detection of phishing websites, however, Naïve Bayes performed poor and is the least recommended method among all.
|
|
2. |
- Butun, Ismail, 1981, et al.
(author)
-
Hardware security of fog end-devices for the internet of things
- 2020
-
In: Sensors. - : MDPI AG. - 1424-8220. ; 20:20, s. 1-28
-
Research review (peer-reviewed)abstract
- The proliferation of the Internet of Things (IoT) caused new application needs to emerge as rapid response ability is missing in the current IoT end-devices. Therefore, Fog Computing has been proposed to be an edge component for the IoT networks as a remedy to this problem. In recent times, cyber-attacks are on the rise, especially towards infrastructure-less networks, such as IoT. Many botnet attack variants (Mirai, Torii, etc.) have shown that the tiny microdevices at the lower spectrum of the network are becoming a valued participant of a botnet, for further executing more sophisticated attacks against infrastructural networks. As such, the fog devices also need to be secured against cyber-attacks, not only software-wise, but also from hardware alterations and manipulations. Hence, this article first highlights the importance and benefits of fog computing for IoT networks, then investigates the means of providing hardware security to these devices with an enriched literature review, including but not limited to Hardware Security Module, Physically Unclonable Function, System on a Chip, and Tamper Resistant Memory.
|
|
3. |
- Butun, Ismail, 1981, et al.
(author)
-
Intrusion Detection in Industrial Networks via Data Streaming
- 2020
-
In: Industrial IoT: Challenges, Design Principles, Applications, and Security. - Cham : Springer International Publishing. ; , s. 213-238
-
Book chapter (other academic/artistic)abstract
- Given the increasing threat surface of industrial networks due to distributed, Internet-of-Things (IoT) based system architectures, detecting intrusions in Industrial IoT (IIoT) systems is all the more important, due to the safety implications of potential threats. The continuously generated data in such systems form both a challenge but also a possibility: data volumes/rates are high and require processing and communication capacity but they contain information useful for system operation and for detection of unwanted situations. In this chapter we explain that stream processing (a.k.a. data streaming) is an emerging useful approach both for general applications and for intrusion detection in particular, especially since it can enable data analysis to be carried out in the continuum of edge-fog-cloud distributed architectures of industrial networks, thus reducing communication latency and gradually filtering and aggregating data volumes. We argue that usefulness stems also due to facilitating provisioning of agile responses, i.e. due to potentially smaller latency for intrusion detection and hence also improved possibilities for intrusion mitigation. In the chapter we outline architectural features of IIoT networks, potential threats and examples of state-of-the art intrusion detection methodologies. Moreover, we give an overview of how leveraging distributed and parallel execution of streaming applications in industrial setups can influence the possibilities of protecting these systems. In these contexts, we give examples using electricity networks (a.k.a. Smart Grid systems). We conclude that future industrial networks, especially their Intrusion Detection Systems (IDSs), should take advantage of data streaming concept by decoupling semantics from the deployment.
|
|
4. |
- Butun, Ismail, 1981
(author)
-
Preface to Industrial IoT
- 2020
-
In: Industrial IoT: Challenges, Design Principles, Applications, and Security. ; , s. IX-X
-
Book chapter (other academic/artistic)
|
|
5. |
- Butun, Ismail, 1981, et al.
(author)
-
Security and privacy in smart grids: Challenges, current solutions and future opportunities
- 2020
-
In: ICISSP 2020 - Proceedings of the 6th International Conference on Information Systems Security and Privacy. - : SCITEPRESS - Science and Technology Publications. ; , s. 733-741
-
Conference paper (peer-reviewed)abstract
- Smart grids are a promising upgrade to legacy power grids due to enhanced cooperation of involved parties, such as consumers and utility providers. These newer grids improve the efficiency of electricity generation and distribution by leveraging communication networks to exchange information between those different parties. However, the increased connection and communication also expose the control networks of the power grid to the possibility of cyber-attacks. Therefore, research on cybersecurity for smart grids is crucial to ensure the safe operation of the power grid and to protect the privacy of consumers. In this paper, we investigate the security and privacy challenges of the smart grid; present current solutions to these challenges, especially in the light of intrusion detection systems; and discuss how future grids will create new opportunities for cybersecurity.
|
|
6. |
- Gaba, Gurjot Singh, et al.
(author)
-
MAKE-IT—A Lightweight Mutual Authentication and Key Exchange Protocol for Industrial Internet of Things
- 2020
-
In: Sensors. - : MDPI AG. - 1424-8220. ; 20:18, s. 1-21
-
Journal article (peer-reviewed)abstract
- Continuous development of the Industrial Internet of Things (IIoT) has opened up enormous opportunities for the engineers to enhance the efficiency of the machines. Despite the development, many industry administrators still fear to use Internet for operating their machines due to untrusted nature of the communication channel. The utilization of internet for managing industrial operations can be widespread adopted if the authentication of the entities are performed and trust is ensured. The traditional schemes with their inherent security issues and other complexities, cannot be directly deployed to resource constrained network devices. Therefore, we have proposed a strong mutual authentication and secret key exchange protocol to address the vulnerabilities of the existing schemes. We have used various cryptography operations such as hashing, ciphering, and so forth, for providing secure mutual authentication and secret key exchange between different entities to restrict unauthorized access. Performance and security analysis clearly demonstrates that the proposed work is energy efficient (computation and communication inexpensive) and more robust against the attacks in comparison to the traditional schemes
|
|
7. |
-
Industrial IoT: Challenges, design principles, applications, and security
- 2020
-
Editorial collection (peer-reviewed)abstract
- Proliferation of Internet of Things (IoT) enabled rapid enhancements for the applications not only in home and environment scenarios, but also in factory automation. Now, Industrial Internet of Things (IIoT) offers all the advantages of IoT to the industrial scenarios, applications ranging from remote sensing and actuating to de-centralization and autonomy. In this book, the editor aims at presenting the IIoT and its place during the industrial revolution (Industry 4.0), while they are taking us to a better, sustainable, automated and safer world. The book covers the cross relations and implications of IIoT with existing wired/wireless communication/networking and safety technologies of the Industrial Networks. Moreover, practical use-case scenarios from the industry, for the application of IIoT on smart factories, smart cities and smart grid are presented. Especially, IoT-driven advances in commercial and industrial building lighting and in street lighting are presented as a specific example to shed light on the application domain of IIoT. The state of the art in Industrial Automation is also presented not only to give a better understanding of the enabling technologies, potential advantages and challenges of the Industry 4.0 and IIoT but also to foster interest on exploring this promising area. Finally yet importantly, the security section of the book covers the cyber-security related needs of the IIoT users and the services that might address these needs. First, user privacy, data ownership, proprietary information handling related to IIoT networks are investigated. Then, the intrusion prevention, detection and mitigation part conclude the book.
|
|
8. |
- Marlind, Fredrik, et al.
(author)
-
Activation of LoRaWAN End Devices by Using Public Key Cryptography
- 2020
-
In: 2020 4th Cyber Security in Networking Conference, CSNet 2020.
-
Conference paper (peer-reviewed)abstract
- This paper aims to design a new process to assign root keys to the devices in Long Range Wide Area Network (LoRaWAN) by using Public Key Cryptography (PKC). This process is used to propose a new activation method called Public Key Over the Air Activation (PK-OTAA). The feasibility of the proposed method is also evaluated scientifically via experiments. The new activation method allows a device to get the root keys dynamically and for them to be replaced at will. However, PKC requires longer keys to get equivalent cryptographic strength to a symmetric encryption scheme. This increased key size in turn requires more processing power to use, thus increasing battery consumption. The feasibility of the new method is evaluated based on the increase in power usage since Internet of Things (IoT) devices are usually battery powered. It has been shown that by sacrificing very small portion of the energy available in the battery; a more flexible and secure key distribution scheme is integrated in LoRaWAN.
|
|
9. |
- Sari, Alparslan, et al.
(author)
-
Industrial networks and IIoT: Now and future trends
- 2020
-
In: Industrial IoT: Challenges, Design Principles, Applications, and Security. - Cham : Springer International Publishing. ; , s. 3-55
-
Book chapter (other academic/artistic)abstract
- Connectivity is the one word summary for Industry 4.0 revolution. The importance of Internet of Things (IoT) and Industrial IoT (IIoT) have been increased dramatically with the rise of industrialization and industry 4.0. As new opportunities bring their own challenges, with the massive interconnected devices of the IIoT, cyber security of those networks and privacy of their users have become an important aspect. Specifically, intrusion detection for industrial networks (IIoT) has great importance. For instance, it is a key factor in improving the safe operation of the smart grid systems yet protecting the privacy of the consumers at the same time. In the same manner, data streaming is a valid option when the analysis is to be pushed from the cloud to the fog for industrial networks to provide agile response, since it brings the advantage of fast action on intrusion detection and also can buy time for intrusion mitigation. In order to dive deep in industrial networks, basic ground needs to be settled. Hence, this chapter serves in this manner, by presenting basic and emerging technologies along with ideas and discussions: First, an introduction of semiconductor evolution is provided along with the up-to-date hi-tech wired/wireless communication solutions for industrial networks. This is followed by a thorough representation of future trends in industrial environments. More importantly, enabling technologies for industrial networks is also presented. Finally, the chapter is concluded with a summary of the presentations along with future projections of IIoT networks.
|
|