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  1. The globalization of the manufacturing process and the supply chain for electronic hardware has been driven by the need to maximize profitability while lowering risk in a technologically advanced silicon sector. However, many hardware IPs’ security features have been broken because of the rise in successful hardware attacks. Existing security efforts frequently ignore numerous dangers in favor of fixing a particular vulnerability. This inspired the development of a unique method that uses emerging spin-based devices to obfuscate circuitry to secure hardware intellectual property (IP) during fabrication and the supply chain. We propose an Optimized and Automated Secure IC (OASIC) Design Flow, a defense-in-depth approach that can minimize overhead while maximizing security. Our EDA tool flow uses a dynamic obfuscation method that employs dynamic lockboxes, which include switch boxes and magnetic random access memory (MRAM)-based look-up tables (LUT) while offering minimal overhead and being flexible and resilient against modern SAT-based attacks and power side-channel attacks. An EDA tool flow for optimized lockbox insertion is also developed to generate SAT-resilient design netlists with the least power and area overhead. PPA metrics and security (SAT attack time) are provided to the designer for each lockbox insertion run. A verification methodology is provided to verify locked and unlocked designs for functional correctness. Finally, we use ISCAS’85 benchmarks to show that the EDA tool flow provides a secure hardware netlist with maximum security while considering power and area constraints. Our results indicate that the proposed OASIC design flow can maximize security while incurring less than 15% area overhead and maintaining a similar power footprint compared to the original design. OASIC design flow demonstrates improved performance as design size increases, which demonstrates the scalability of the proposed approach. 
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    Free, publicly-accessible full text available April 1, 2025
  2. Modern semiconductor manufacturing often leverages a fabless model in which design and fabrication are partitioned. This has led to a large body of work attempting to secure designs sent to an untrusted third party through obfuscation methods. On the other hand, efficient de-obfuscation attacks have been proposed, such as Boolean Satisfiability attacks (SAT attacks). However, there is a lack of frameworks to validate the security and functionality of obfuscated designs. Additionally, unconventional obfuscated design flows, which vary from one obfuscation to another, have been key impending factors in realizing logic locking as a mainstream approach for securing designs. In this work, we address these two issues for Lookup Table-based obfuscation. We study both Volatile and Non-volatile versions of LUT-based obfuscation and develop a framework to validate SAT runtime using machine learning. We can achieve unparallel SAT-resiliency using LUT-based obfuscation while incurring 7% area and less than 1% power overheads. Following this, we discuss and implement a validation flow for obfuscated designs. We then fabricate a chip consisting of several benchmark designs and a RISC-V CPU in TSMC 65nm for post functionality validation. We show that the design flow and SAT-runtime validation can easily integrate LUT-based obfuscation into existing CAD tools while adding minimal verification overhead. Finally, we justify SAT-resilient LUT-based obfuscation as a promising candidate for securing designs. 
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  3. This paper presents RAPTA, a customized Representation-learning Architecture for automation of feature engineering and predicting the result of Path-based Timing-Analysis early in the physical design cycle. RAPTA offers multiple advantages compared to prior work: 1) It has superior accuracy with errors std ranges 3.9ps~16.05ps in 32nm technology. 2) RAPTA's architecture does not change with feature-set size, 3) RAPTA does not require manual input feature engineering. To the best of our knowledge, this is the first work, in which Bidirectional Long Short-Term Memory (Bi-LSTM) representation learning is used to digest raw information for feature engineering, where generation of latent features and Multilayer Perceptron (MLP) based regression for timing prediction can be trained end-to-end. 
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  4. Maximizing profits while minimizing risk in a technologically advanced silicon industry has motivated the globalization of the fabrication process and electronic hardware supply chain. However, with the increasing magnitude of successful hardware attacks, the security of many hardware IPs has been compromised. Many existing security works have focused on resolving a single vulnerability while neglecting other threats. This motivated to propose a novel approach for securing hardware IPs during the fabrication process and supply chain via logic obfuscation by utilizing emerging spin-based devices. Our proposed dynamic obfuscation approach uses reconfigurable logic and interconnects blocks (RIL-Blocks), consisting of Magnetic Random Access Memory (MRAM)-based Look Up Tables and switch boxes flexibility and resiliency against state-of-the-art SAT-based attacks and power side-channel attacks while incurring a small overhead. The proposed Scan Enabled Obfuscation circuitry obfuscates the oracle circuit’s responses and further fortifies the logic and routing obfuscation provided by the RIL-Blocks, resembling a defense-in-depth approach. The empirical evaluation of security provided by the proposed RIL-Blocks on the ISCAS benchmark and common evaluation platform (CEP) circuit shows that resiliency comes with reduced overhead while providing resiliency to various hardware security threats. 
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  5. To enable trust in the IC supply chain, logic locking as an IP protection technique received significant attention in recent years. Over the years, by utilizing Boolean satisfiability (SAT) solver and its derivations, many de-obfuscation attacks have undermined the security of logic locking. Nonetheless, all these attacks receive the inputs (locked circuits) in a very simplified format (Bench or remapped and translated Verilog) with many limitations. This raises the bar for the usage of the existing attacks for modeling and assessing new logic locking techniques, forcing the designers to undergo many troublesome translations and simplifications. This paper introduces the RANE Attack, an open-source CAD-based toolbox for evaluating the security of logic locking mechanisms that implement a unique interface to use formal verification tools without a need for any translation or simplification. The RANE attack not only performs better compared to the existing de-obfuscation attacks, but it can also receive the library-dependent logic-locked circuits with no limitation in written, elaborated, or synthesized standard HDL, such as Verilog. We evaluated the capability/performance of RANE on FOUR case studies, one is the first de-obfuscation attack model on FSM locking solutions (e.g., HARPOON) in which the key is not a static bit-vector but a sequence of input patterns. 
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  6. null (Ed.)
    Logic locking has been widely evaluated as a proactive countermeasure against the hardware security threats within the IC supply chain. However, the introduction of the SAT attack, and many of its derivatives, has raised big concern about this form of countermeasure. In this paper, we explore the possibility of exploiting chaos computing as a new means of logic locking. We introduce the concept of chaotic logic locking, called ChaoLock, in which, by leveraging asymmetric inputs in digital chaotic Boolean gates, we define the concept of programmability (key-configurability) to the sets of underlying initial conditions and system parameters. These initial conditions and system parameters determine the operation (functionality) of each digital chaotic Boolean gate. Also, by proposing dummy inputs in chaotic Boolean gates, we show that during reverse-engineering, the dummy inputs conceal the main functionality of the chaotic Boolean gates, which make the reverse-engineering almost impossible. By performing a security analysis of ChaoLock, we show that with no restriction on conventional CMOS-based ASIC implementation and with no test/debug compromising, none of the state-of-the-art attacks on logic locking, including the SAT attack, could reformulate chaotic Boolean gates while dummy inputs are involved and their parameters are locked. Our analysis and experimental results show that with a low number of chaotic Boolean gates mixed with CMOS digital gates, ChaoLock can guarantee resiliency against the state-of-the-art attacks on logic locking at low overhead. 
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  7. null (Ed.)
    Deep convolutional neural networks have shown high efficiency in computer visions and other applications. However, with the increase in the depth of the networks, the computational complexity is growing exponentially. In this paper, we propose a novel solution to reduce the computational complexity of convolutional neural network models used for many class image classification. Our proposed technique breaks the classification task into two steps: 1) coarse-grain classification, in which the input samples are classified among a set of hyper-classes, 2) fine-grain classification, in which the final labels are predicted among those hyper-classes detected at the first step. We illustrate that our proposed classifier can reach the level of accuracy reported by the best in class classification models with less computational complexity (Flop Count) by only activating parts of the model that are needed for the image classification. 
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