5 results
Search Results
Now showing 1 - 5 of 5
Conference Object Security Requirements in Iot Environments(Springer Science and Business Media Deutschland GmbH, 2022) Binglaw,F.; Koyuncu,M.; Pusatlı,T.The Internet of Things (IoT) is a relatively new concept as it connects things (or objects) that do not have high computational power. The IoT helps these things see, listen, and take action by interoperating with minimal human intervention to make people’s lives easier. However, these systems are vulnerable to attacks and security threats that could potentially undermine consumer confidence in them. For this reason, it is critical to understand the characteristics of IoT security and their requirements before starting to discuss how to protect them. In this scope, the present work reviews the importance of security in IoT applications, factors that restrict the use of traditional security methods to protect IoTs, and the basic requirements necessary to judge them as secure environments. © 2022, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.Conference Object Securing the Internet of Things: Challenges and Complementary Overview of Machine Learning-Based Intrusion Detection(Institute of Electrical and Electronics Engineers Inc., 2024) Isin, L.I.; Dalveren, Y.; Leka, E.; Kara, A.The significant increase in the number of IoT devices has also brought with it various security concerns. The ability of these devices to collect a lot of data, including personal information, is one of the important reasons for these concerns. The integration of machine learning into systems that can detect security vulnerabilities has been presented as an effective solution in the face of these concerns. In this review, it is aimed to examine the machine learning algorithms used in the current studies in the literature for IoT network security. Based on the authors' previous research in physical layer security, this research also aims to investigate the intersecting lines between upper layers of security and physical layer security. To achieve this, the current state of the area is presented. Then, relevant studies are examined to identify the key challenges and research directions as an initial overview within the authors' ongoing project. © 2024 IEEE.Article Citation - WoS: 75Citation - Scopus: 93Co-Fais: Cooperative Fuzzy Artificial Immune System for Detecting Intrusion in Wireless Sensor Networks(Academic Press Ltd- Elsevier Science Ltd, 2014) Shamshirband, Shahaboddin; Anuar, Nor Badrul; Kiah, Miss Laiha Mat; Rohani, Vala Ali; Petkovic, Dalibor; Misra, Sanjay; Khan, Abdul NasirDue to the distributed nature of Denial-of-Service attacks, it is tremendously challenging to identify such malicious behavior using traditional intrusion detection systems in Wireless Sensor Networks (WSNs). In the current paper, a bio-inspired method is introduced, namely the cooperative-based fuzzy artificial immune system (Co-FATS). It is a modular-based defense strategy derived from the danger theory of the human immune system. The agents synchronize and work with one another to calculate the abnormality of sensor behavior in terms of context antigen value (CAV) or attackers and update the fuzzy activation threshold for security response. In such a multi-node circumstance, the sniffer module adapts to the sink node to audit data by analyzing the packet components and sending the log file to the next layer. The fuzzy misuse detector module (FMDM) integrates with a danger detector module to identify the sources of danger signals. The infected sources are transmitted to the fuzzy Q-learning vaccination modules (FQVM) in order for particular, required action to enhance system abilities. The Cooperative Decision Making Modules (Co-DMM) incorporates danger detector module with the fuzzy Q-learning vaccination module to produce optimum defense strategies. To evaluate the performance of the proposed model, the Low Energy Adaptive Clustering Hierarchy (LEACH) was simulated using a network simulator. The model was subsequently compared against other existing soft computing methods, such as fuzzy logic controller (FLC), artificial immune system (AIS), and fuzzy Q-learning (FQL), in terms of detection accuracy, counter-defense, network lifetime and energy consumption, to demonstrate its efficiency and viability. The proposed method improves detection accuracy and successful defense rate performance against attacks compared to conventional empirical methods. (C) 2014 Elsevier Ltd. All rights reserved.Review Do Users Sacrifice Security for Speed and Ease-Of on Smartphones? a Case Study on Attitude(IGI Global, 2020) Pusatli,T.; Koyuncu,M.; Nakip,M.Storing credentials on smartphones to perform online activities increases ease-of-use (EoU) and speed. However, such practices increase security risks, especially if users use a number of applications or store data on their smartphones. Risks become more complicated by keeping smartphones online. This work aims to find potential relationships between security perceptions of smartphone users and their ease-of-use and speed preferences. Two user attitudes are defined as “not considering risk” and “risk exaggeration.” User ease-of-use and speed preferences are limited with the factors related to storing credentials on a smartphone and always keeping the device online. A survey of 154 participants was conducted through convenience sampling. Through regression analyses, logarithmic causality relations are found between EoU and speed and attitudes of not considering risk or risk exaggeration; so the participants preferred to take advantage of EoU and speed despite the fact that they were aware of the risks. Copyright © 2020, IGI Global.Article Citation - WoS: 41Citation - Scopus: 88Attributes Impacting Cybersecurity Policy Development: an Evidence From Seven Nations(Elsevier Advanced Technology, 2022) Mishra, Alok; Alzoubi, Yehia Ibrahim; Anwar, Memoona Javeria; Gill, Asif QumerCyber threats have risen as a result of the growing usage of the Internet. Organizations must have effec-tive cybersecurity policies in place to respond to escalating cyber threats. Individual users and corpora-tions are not the only ones who are affected by cyber-attacks; national security is also a serious concern. Different nations' cybersecurity rules make it simpler for cybercriminals to carry out damaging actions while making it tougher for governments to track them down. Hence, a comprehensive cybersecurity policy is needed to enable governments to take a proactive approach to all types of cyber threats. This study investigates cybersecurity regulations and attributes used in seven nations in an attempt to fill this research gap. This paper identified fourteen common cybersecurity attributes such as telecommunication, network, Cloud computing, online banking, E-commerce, identity theft, privacy, and smart grid. Some na-tions seemed to focus, based on the study of key available policies, on certain cybersecurity attributes more than others. For example, the USA has scored the highest in terms of online banking policy, but Canada has scored the highest in terms of E-commerce and spam policies. Identifying the common poli-cies across several nations may assist academics and policymakers in developing cybersecurity policies. A survey of other nations' cybersecurity policies might be included in the future research.(c) 2022 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license ( http://creativecommons.org/licenses/by/4.0/ )
