Mr. Baki B. Yilmaz Profile

Baki B. Yilmaz

SPIE Involvement:

Author

Publications (3)

This will count as one of your downloads.

You will have access to both the presentation and article (if available).

DOWNLOAD NOW

This content is available for download via your institution's subscription. To access this item, please sign in to your personal account.

Email or Username Forgot your username?

Password Forgot your password?

Show

Keep me signed in

No SPIE account? Create an account

Proceedings Article | 24 April 2020 Presentation + Paper

Program profiling based on Markov models and EM emanations

Baki Berkay Yilmaz, Elvan Mert Ugurlu, Frank Werner, Milos Prvulovic, Alenka Zajic

Proceedings Volume 11417, 114170D (2020) https://doi.org/10.1117/12.2560808

KEYWORDS: Profiling, Data modeling, Principal component analysis, Feature extraction, Model-based design, Dimension reduction, Modulation

Read Abstract +

As one of the fundamental approaches for code optimization and performance analysis, profiling software activities can provide information on the existence of malware, code execution problems, etc. In this paper, we propose a methodology to profile a system with no overhead. The approach leverages electromagnetic (EM) emanations while executing a program, and exploits its flow diagram by constructing a Markov model. The states of the model are considered as the heavily executed blocks (called hot paths) of the program, and the transition between any two states is possible only if there exists a branching operation which enables execution of corresponding states without any intermediate state. To identify the state of the program, we utilize a supervised learning method. To do so, we first collect signals for each state, extract features, and generate a dictionary. The features are considered as the activated frequencies when the program is executed. The assumption here is that there exists at least one unique frequency component that is only active for one unique state. Moreover, to degrade the e↵ect of interruptions and other signals emanated from other parts of the device, and to obtain signals with high Signal-to-Noise Ratio (SNR), we average the output of Short-Time Fourier Transform (STFT). After extracting features, we apply Principle Component Analysis (PCA) for dimension reduction which helps monitoring systems in real time. Finally, we describe experimental setup and show results to demonstrate that the proposed methodology can detect malware activity with high accuracy.

Proceedings Article | 24 April 2020 Presentation + Paper

A novel clustering technique using backscattering side channel for counterfeit IC detection

Luong Nguyen, Baki Berkay Yilmaz, Chia-Lin Cheng, Milos Prvulovic, Alenka Zajić

Proceedings Volume 11417, 1141709 (2020) https://doi.org/10.1117/12.2561172

KEYWORDS: Backscatter, Manufacturing, Integrated circuits, Nondestructive evaluation

Read Abstract +

Over the past few years, globalization of the semiconductor supply chain has led companies to outsource much of the production cycle for integrated circuits (ICs). While outsourcing helps companies significantly reduce their cost and time-to-market, it also introduces concerns about the trustworthiness of an IC. One of the most serious problems is counterfeiting of ICs, which not only negatively impacts innovation and economic growth of the IC industry, but also creates serious threats and risks for systems that incorporate those counterfeit ICs. This paper proposes a novel method that uses the backscattering side-channel to cluster ICs such that counterfeits are separated from legitimate ICs. The backscattering side-channel, which has been introduced only recently, has been proven to outperform other side-channels in detecting hardware Trojan horses (HTs), i.e. ICs where additional logic gates (and connections to existing logic gates) have been added. In this work we use it to robustly separate ICs into legitimate and counterfeit ones, even when only layout or placement of the IC has changed, without any added logic or connections. We evalute our technique on a set of ten boards over six different counterfeit IC designs, and find that our technique tolerates manufacturing variations among different hardware instances, detecting counterfeit ICs with 100% accuracy and 0% false positives.

Proceedings Article | 17 May 2019 Paper

Instruction level program tracking using electromagnetic emanations

Baki Berkay Yilamz, Elvan Mert Ugurlu, Alenka Zajic, Milos Prvulovic

Proceedings Volume 11011, 110110H (2019) https://doi.org/10.1117/12.2522620

KEYWORDS: Signal processing, Clocks, Electromagnetism, Solids, Field programmable gate arrays, Computing systems, Receivers, Signal generators, Software, Inspection

Read Abstract +

Monitoring computer system activities on the instruction level provides more resilience to malware attacks because these attacks can be analyzed better by observing the changes on the instruction level. Assuming the source code is available, many training signals can be collected to track the instruction sequence to detect whether a malware is injected or the system works properly. However, training signals have to be collected with high sampling rate to ensure that the significant features of these signals do not vanish. Since the clock frequencies of the current computer systems are extremely high, we need to have a commercial device with high sampling rate, i.e. 10GHz, which either costs remarkably high, or does not exist. To eliminate the deficiencies regarding the insufficient sampling rate, we propose a method to increase the sampling rate with the moderate commercial devices for training symbols. In that respect, we first generate some random instruction sequences which exist in the inspected source code. Then, these sequences are executed in a for-loop, and emanated electromagnetic (EM) signals from the processor are collected by a commercially available device with moderate sampling rate, i.e. sampling rate is much smaller than the clock frequency. Lastly, we apply a mapping of the gathered samples by utilizing modulo of their timings with respect to execution time of overall instruction sequence. As the final step, we provide some experimental results to illustrate that we successfully track the instruction sequence by applying the proposed approach.

My Library

You currently do not have any folders to save your paper to! Create a new folder below.

Folder Name

Folder Description

View contact details

UPDATE YOUR PROFILE

Is this your profile? Update it now.

Sign into your SPIE.org account

Don’t have a profile and want one?

Create an account on SPIE.org

Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks. You are receiving this notice because your organization may not have SPIE eBooks access.*

*Shibboleth/Open Athens users─please sign in to access your institution's subscriptions.

To obtain this item, you may purchase the complete book in print or electronic format on SPIE.org.

ORGANIZATIONAL
Sign in with credentials provided by your organization.

Organizational Username

Organizational Password

Show/Hide Password

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members:

Non-members: ADD TO CART

Keywords/Phrases

Search In:

Publication Years