Nesnelerin İnternetinde Çok Katmanlı Algılayıcı Kullanarak Zamanlama Analizi Saldırısı ile Özel Anahtar Tahminlemesi

Year 2021, Volume: IDAP-2021 : 5th International Artificial Intelligence and Data Processing symposium Issue: Special, 385 - 390, 20.10.2021

Muhammed Saadetdin Kaya , Kenan İnce

https://doi.org/10.53070/bbd.990849

Abstract

Doğrudan kaynağa erişim olmasa bile, gizlenmek istenen veriler hakkında bilgi sahibi olunmasını sağlayan yan kanal saldırılarından biri olan Zamanlama Analizi Saldırıları; bir işlemin veya algoritmanın farklı şartlar altında harcadığı sürelerin yorumlanmasıyla, sistem hakkında bilgi edinmeyi amaçlayan bir saldırı türüdür. Bu çalışmada, belirlenmiş bir senaryodaki özel anahtarın zamanlama analizi yöntemiyle Çok Katmanlı Algılayıcı (MLP – Multilayer Perceptron) kullanılarak sistem analiz edilmiştir. Analiz sonucunda zamanlama bilgisi kullanılarak gizli anahtarın tahminlenmesi amaçlanmıştır. Yapılan çalışma sonucunda sunulan yöntemle, %95’in üzerinde doğruluk oranına sahip bir şekilde gizli anahtar tahminlenmiş olup, Nesnelerin İnterneti (IoT – Internet of Things) alanında zamanlama analizi saldırılarının ciddi bir tehdit oluşturabileceği ortaya koyulmuştur.

Keywords

Yan-kanal Saldırıları, Zamanlama Analizi Saldırıları, Çok Katmanlı Algılayıcı, Nesnelerin İnterneti

Supporting Institution

İnönü Üniversitesi

Project Number

FBG-2020-2143

Thanks

Bu çalışma, İnönü Üniversitesi Bilimsel Araştırma Projeleri Bölümü'nün (BAPB) FBG-2020-2143 sayılı projesi ile desteklenmiştir. Yazar, değerli geri bildirimleri için İnönü Üniversitesi BAPB’ye teşekkür eder.

Timing Analysis Attack For Private Key Prediction Using Multilayer Perceptron in IoT

Abstract

Timing Analysis Attacks are one of the side channel attacks that allows to be informed about the data that is wanted to be hidden, even if there is no direct access to the source. It is a type of attack aimed at learning about the system by interpreting the amount of time that a process of algorithm spends under different circumstances. In this study, the system was analyzed using a multilayer sensor (MLP – Multilayer Perceptron) by timing analysis of the private key in a specified scenario. As a result of the analysis, it is aimed to estimate the secret key using timing information. As a result of the analysis, it is aimed to estimate the secret key using timing information. As a result of the study, the secret key was estimated with an accuracy rate of more than 95% and it was revealed that timing analysis attacks could pose a serious threat in the Internet of Things (IoT) area.

Keywords

Side-channel Attacks, Timing Analysis Attacks, Multilayer Perceptron (MLP), Internet of Things (IoT)

Project Number

FBG-2020-2143

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