Moving Target Defense Mechanism for Side-Channel Attacks

Vuppala, Satyanarayana; Mady, Alie El‐Din; Kuenzi, Adam

doi:10.1109/jsyst.2019.2922589

Cited by 11 publications

(8 citation statements)

References 24 publications

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“…Therefore, it is essential to enable IoT devices to perform secure and powerful processing with low power consumption [18]. Another type of timing attack that exploits information leaked through timing measurements of a system's activities is called a timing-based side-channel attack [33]. It enables an attacker to explore a device's vulnerabilities and extract secrets to use in his attack when it has weak computing capabilities and takes a long time to respond.…”

Section: Timing Attackmentioning

confidence: 99%

An Overview of Iot Architecture Security Issues and Countermeasures

Khalaifat

2024

AJRCoS

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The Internet of Things (IoT) has revolutionized the way we interact with our surroundings. As the number of IoT devices continues to increase, along with limited resources and diverse technologies, the risk of security attacks increases. Therefore, it is important to integrate security measures throughout the development process and system architecture. However, it is crucial to continually assess and update security measures to avoid emerging threats and ensure the confidentiality, integrity, and availability of IoT systems. This study aims to explore security issues in the IoT, highlighting the associated challenges. It examines various threats, attacks, and vulnerabilities that arise within a three-layer architecture and discusses potential solutions to enhance security in each layer. By addressing these concerns, it is possible to establish a secure and reliable foundation for expanding IoT systems.

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Section: Timing Attackmentioning

confidence: 99%

An Overview of Iot Architecture Security Issues and Countermeasures

Khalaifat

2024

AJRCoS

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“…Vuppala et al [30] presented a security technique for resisting electromagnetic attacks. Furthermore, the study model emphasizes controlling overhead using the rekeying mechanism.…”

Section: Existing Approachesmentioning

confidence: 99%

“…(iii) The proposed scheme facilitates the verification of adjacent nodes as well as all other actors in a non-iterative way, which acts as a dual layer of security and increases the frequency of authentication suitable for an extensive dynamic network, unlike the existing approaches , which assess only single target nodes. iv) The proposed scheme is capable of resisting differential fault attacks, power-based attacks, timing attacks and cache attacks, which opens up many opportunities for fighting multiple variants of side-channel attacks, whereas existing approaches [24][25][26][27][28][29][30][31][32][33][34][35][36][37][38] are reported to resist only singular forms of attack.…”

Section: Accomplished Outcomementioning

confidence: 99%

Decentralized Blockchain Network for Resisting Side-Channel Attacks in Mobility-Based IoT

et al. 2022

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The inclusion of mobility-based Internet-of-Things (IoT) devices accelerates the data transmission process, thereby catering to IoT users’ demands; however, securing the data transmission in mobility-based IoT is one complex and challenging concern. The adoption of unified security architecture has been identified to prevent side-channel attacks in the IoT, which has been discussed extensively in developing security solutions. Despite blockchain’s apparent superiority in withstanding a wide range of security threats, a careful examination of the relevant literature reveals that some common pitfalls are associated with these methods. Therefore, the proposed scheme introduces a novel computational security framework wherein a branched and decentralized blockchain network is formulated to facilitate coverage from different variants of side-channel IoT attacks that are yet to be adequately reported. A unique blockchain-based authentication approach is designed to secure communication among mobile IoT devices using multiple stages of security implementation with Smart Agreement and physically unclonable functions. Analytical modeling with lightweight finite field encryption is used to create this framework in Python. The study’s benchmark results show that the proposed scheme offers 4% less processing time, 5% less computational overhead, 1% more throughput, 12% less latency, and 30% less energy consumption compared to existing blockchain methods.

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“…This paper [2] presents ASNI: Attenuated Signature Noise Injection with AES-128 encryption as general measures for lower efficiency and display SCA properties. This enterprise integration [3] technologies include new major updates and technologies hidden at regular intervals. It is driven by a maximum of side-by-side leak traces required for a trace VM side-channel attack.…”

Section: Related Workmentioning

confidence: 99%

Implementation of Block-Level Double Encryption Based on Machine Learning Techniques for Attack Detection and Prevention

Gnanavel

Narayana

Jayashree

et al. 2022

Wireless Communications and Mobile Computing

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Cloud computing is one of the most important business models of modern information technology. It provides a minimum of various services to the user interaction and low cost (hardware and software). Cloud services are based on the newline architectures on virtualization by using the multitenancy for better resource management and newline strong isolation between several virtual machines (VMs). The spying on a victim VM is challenging, particularly when one wants to use per-core microarchitectural features as a side channel. For example, the cache contains the most potential for damaging side channels, but shared information across different cores affects the cloud information. To overcome this problem, propose the Secure Block-Level Double Encryption (SBLDE) algorithm for user signature verification in the cloud server. It uses identity-based detection techniques to monitor the colocated VMs to identify abnormal cache data and channel behaviors typically during VM data transformation. The identity-based linear classification (IBLC) method is used for classifying the attacker channel when the data is transferred/retrieved from the VM cloud server. This cloud controller finds the channel misbehavior to block the port or channel, changing other available ports’ communication. The service verification provides strong user access permission on the cloud server when the unknown request to the cloud server suddenly executes the key authentication to verify the user permission. This linear classification trains the existing side-channel attack datasets to the classifier and identifies the VM cloud’s attack channel. The study focused on preventing attacks from interrupting the system and serves as an effective means for cross-VM side-channel attacks. This proposed method protects the cloud data and prevents cross-VM channel attack detection efficiently, compared to other existing methods. In this overall proposed method, SBLDE’s performance is to be evaluated and then compared with the existing method.

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Moving Target Defense Mechanism for Side-Channel Attacks

Cited by 11 publications

References 24 publications

An Overview of Iot Architecture Security Issues and Countermeasures

An Overview of Iot Architecture Security Issues and Countermeasures

Decentralized Blockchain Network for Resisting Side-Channel Attacks in Mobility-Based IoT

Implementation of Block-Level Double Encryption Based on Machine Learning Techniques for Attack Detection and Prevention

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