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Security Breaches and Threat Prevention in the Internet of Things
01 Feb 2017-
TL;DR: Security Breaches and Threat Prevention in the Internet of Things provides a comprehensive examination of the latest strategies and methods for tracking and blocking threats within industries that work heavily with this technology.
Abstract: Security Breaches and Threat Prevention in the Internet of Things provides a comprehensive examination of the latest strategies and methods for tracking and blocking threats within industries that work heavily with this technology. Featuring chapters on emerging topics such as security threats in autonomous vehicles, digital forensics, secure communications, and image encryption, this critical reference source is a valuable tool for all academicians, graduate students, practitioners, professionals, and researchers who are interested in expanding their knowledge of security practices pertaining to the Internet of Things.
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TL;DR: To take advantage of the volume and variety of data captured by and stored in ubiquitous IoT services, forensic investigators need to draw upon evidence-acquisition methods and techniques from all areas of digital forensics and possibly create new IoT-specific investigation processes.
Abstract: The Internet of Things (IoT) brings a set of unique and complex challenges to the field of digital forensics. To take advantage of the volume and variety of data captured by and stored in ubiquitous IoT services, forensic investigators need to draw upon evidence-acquisition methods and techniques from all areas of digital forensics and possibly create new IoT-specific investigation processes. Although a number of conceptual process models have been developed to address the unique characteristics of the IoT, many challenges remain unresolved.
39 citations
01 Sep 2017
TL;DR: This paper evaluates ransomware attacks statistics for the past 2 years and the present year to estimate growth rate of the most emerging ransomware families from the last 3 years to evaluate most threatening ransomware attacks for IoT and presents a Cryptowall ransomware attack detection model based on the communication and behavioral study of cryptowall for IoT environment.
Abstract: Internet of things (IoT) is internetworking of various physical devices to provide a range of services and applications. IoT is a rapidly growing field, on an account of this; the security measurements for IoT should be at first concern. In the modern day world, the most emerging cyber-attack threat for IoT is ransomware attack. Ransomware is a kind of malware with the aim of rendering a victim's computer unusable or inaccessible, and then asking the user to pay a ransom to revert the destruction. In this paper we are evaluating ransomware attacks statistics for the past 2 years and the present year to estimate growth rate of the most emerging ransomware families from the last 3 years to evaluate most threatening ransomware attacks for IoT. Growth rate results shows that the number of attacks for Cryptowall and locky ransomware are notably increasing therefore, these ransomware families are potential threat to IoT. Moreover, we present a Cryptowall ransomware attack detection model based on the communication and behavioral study of Cryptowall for IoT environment. The proposed model observes incoming TCP/IP traffic through web proxy server then extracts TCP/IP header and uses command and control (C&C) server black listing to detect ransomware attacks.
34 citations
TL;DR: A survey on the most up-to-date chaos-based image encryption techniques and classifies them into spatial, temporal and spatio-temporal domains for better understanding is presented in this paper .
Abstract: Abstract Chaos-based cryptosystems have been an active area of research in recent years. Although these algorithms are not standardized like AES, DES, RSA, etc., chaos-based cryptosystems like Chebyshev polynomials can provide additional security when used with standard public key cryptosystems like RSA and El-gamal. Standard encryption algorithms such as AES have always been the primary choice, but when it comes to image or video encryption, many researchers recommend chaos-based encryption techniques due to their computational efficiency. This paper presents a survey on the most up-to-date chaos-based image encryption techniques and classifies them into spatial, temporal and spatiotemporal domains for better understanding. The significant improvements in the field of image encryption are discussed. In addition, comparative analysis is performed to validate the evaluation matrices for quantifying the encryption algorithms’ security and performance in recent papers.
33 citations
TL;DR: A survey on the most up-to-date chaos-based image encryption techniques and classifies them into spatial, temporal and spatio-temporal domains for better understanding is presented in this article .
Abstract: Abstract Chaos-based cryptosystems have been an active area of research in recent years. Although these algorithms are not standardized like AES, DES, RSA, etc., chaos-based cryptosystems like Chebyshev polynomials can provide additional security when used with standard public key cryptosystems like RSA and El-gamal. Standard encryption algorithms such as AES have always been the primary choice, but when it comes to image or video encryption, many researchers recommend chaos-based encryption techniques due to their computational efficiency. This paper presents a survey on the most up-to-date chaos-based image encryption techniques and classifies them into spatial, temporal and spatiotemporal domains for better understanding. The significant improvements in the field of image encryption are discussed. In addition, comparative analysis is performed to validate the evaluation matrices for quantifying the encryption algorithms’ security and performance in recent papers.
19 citations
01 Jun 2021
TL;DR: In this paper, the authors address the IoT security sensor tampering issue in an office environment and apply machine learning to detect sensor tampering using two methods: isolation forest-based unsupervised machine learning method and decision tree supervised method.
Abstract: With the rapid growth of the Internet of Things (IoT) applications in smart regions/cities, for example, smart healthcare, smart homes/offices, there is an increase in security threats and risks. The IoT devices solve real-world problems by providing real-time connections, data and information. Besides this, the attackers can tamper with sensors, add or remove them physically or remotely. In this study, we address the IoT security sensor tampering issue in an office environment. We collect data from real-life settings and apply machine learning to detect sensor tampering using two methods. First, a real-time view of the traffic patterns is considered to train our isolation forest-based unsupervised machine learning method for anomaly detection. Second, based on traffic patterns, labels are created, and the decision tree supervised method is used, within our novel Anomaly Detection using Machine Learning (AD-ML) system. The accuracy of the two proposed models is presented. We found 84% with silhouette metric accuracy of isolation forest. Moreover, the result based on 10 cross-validations for decision trees on the supervised machine learning model returned the highest classification accuracy of 91.62% with the lowest false positive rate.
12 citations
References
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01 Jan 2017
TL;DR: This chapter focuses on existing protocols and different proposed mechanisms in literature to secure communications in the IoT.
Abstract: The maturity of the IoT depends on the security of communications and the protection of end-user’s privacy. However, technological and material heterogeneities, and the asymmetric nature of communications between sensor nodes and ordinary Internet hosts, make the security in this case more problematic. Major problem facing the large deployment of IoT is the absence of a unified architecture and a lack of common agreement in defining protocols and standards for IoT parts. Many solutions have been proposed for the standardization of security concepts and protocols in IoT at different layers. Even though many advances and proposals were made for IoT adaptation as IPv6 for Low Power Wireless Personal Area Network (6LoWPAN), and at application layer with protocols such as XMPP, MQTT, CoAP, etc., security of the IoT remains a very challenging task and an open research topic. This chapter focuses on existing protocols and different proposed mechanisms in literature to secure communications in the IoT.
5 citations