2,882 research outputs found
Creation and detection of hardware trojans using non-invasive off-the-shelf technologies
As a result of the globalisation of the semiconductor design and fabrication processes, integrated circuits are becoming increasingly vulnerable to malicious attacks. The most concerning threats are hardware trojans. A hardware trojan is a malicious inclusion or alteration to the existing design of an integrated circuit, with the possible effects ranging from leakage of sensitive information to the complete destruction of the integrated circuit itself. While the majority of existing detection schemes focus on test-time, they all require expensive methodologies to detect hardware trojans. Off-the-shelf approaches have often been overlooked due to limited hardware resources and detection accuracy. With the advances in technologies and the democratisation of open-source hardware, however, these tools enable the detection of hardware trojans at reduced costs during or after production. In this manuscript, a hardware trojan is created and emulated on a consumer FPGA board. The experiments to detect the trojan in a dormant and active state are made using off-the-shelf technologies taking advantage of different techniques such as Power Analysis Reports, Side Channel Analysis and Thermal Measurements. Furthermore, multiple attempts to detect the trojan are demonstrated and benchmarked. Our simulations result in a state-of-the-art methodology to accurately detect the trojan in both dormant and active states using off-the-shelf hardware
Homomorphic Data Isolation for Hardware Trojan Protection
The interest in homomorphic encryption/decryption is increasing due to its
excellent security properties and operating facilities. It allows operating on
data without revealing its content. In this work, we suggest using homomorphism
for Hardware Trojan protection. We implement two partial homomorphic designs
based on ElGamal encryption/decryption scheme. The first design is a
multiplicative homomorphic, whereas the second one is an additive homomorphic.
We implement the proposed designs on a low-cost Xilinx Spartan-6 FPGA. Area
utilization, delay, and power consumption are reported for both designs.
Furthermore, we introduce a dual-circuit design that combines the two earlier
designs using resource sharing in order to have minimum area cost. Experimental
results show that our dual-circuit design saves 35% of the logic resources
compared to a regular design without resource sharing. The saving in power
consumption is 20%, whereas the number of cycles needed remains almost the sam
Trojans in Early Design Steps—An Emerging Threat
Hardware Trojans inserted by malicious foundries
during integrated circuit manufacturing have received substantial
attention in recent years. In this paper, we focus on a different
type of hardware Trojan threats: attacks in the early steps of
design process. We show that third-party intellectual property
cores and CAD tools constitute realistic attack surfaces and that
even system specification can be targeted by adversaries. We
discuss the devastating damage potential of such attacks, the
applicable countermeasures against them and their deficiencies
A Touch of Evil: High-Assurance Cryptographic Hardware from Untrusted Components
The semiconductor industry is fully globalized and integrated circuits (ICs)
are commonly defined, designed and fabricated in different premises across the
world. This reduces production costs, but also exposes ICs to supply chain
attacks, where insiders introduce malicious circuitry into the final products.
Additionally, despite extensive post-fabrication testing, it is not uncommon
for ICs with subtle fabrication errors to make it into production systems.
While many systems may be able to tolerate a few byzantine components, this is
not the case for cryptographic hardware, storing and computing on confidential
data. For this reason, many error and backdoor detection techniques have been
proposed over the years. So far all attempts have been either quickly
circumvented, or come with unrealistically high manufacturing costs and
complexity.
This paper proposes Myst, a practical high-assurance architecture, that uses
commercial off-the-shelf (COTS) hardware, and provides strong security
guarantees, even in the presence of multiple malicious or faulty components.
The key idea is to combine protective-redundancy with modern threshold
cryptographic techniques to build a system tolerant to hardware trojans and
errors. To evaluate our design, we build a Hardware Security Module that
provides the highest level of assurance possible with COTS components.
Specifically, we employ more than a hundred COTS secure crypto-coprocessors,
verified to FIPS140-2 Level 4 tamper-resistance standards, and use them to
realize high-confidentiality random number generation, key derivation, public
key decryption and signing. Our experiments show a reasonable computational
overhead (less than 1% for both Decryption and Signing) and an exponential
increase in backdoor-tolerance as more ICs are added
Ingress of threshold voltage-triggered hardware trojan in the modern FPGA fabric–detection methodology and mitigation
The ageing phenomenon of negative bias temperature instability (NBTI) continues to challenge the dynamic thermal management of modern FPGAs. Increased transistor density leads to thermal accumulation and propagates higher and non-uniform temperature variations across the FPGA. This aggravates the impact of NBTI on key PMOS transistor parameters such as threshold voltage and drain current. Where it ages the transistors, with a successive reduction in FPGA lifetime and reliability, it also challenges its security. The ingress of threshold voltage-triggered hardware Trojan, a stealthy and malicious electronic circuit, in the modern FPGA, is one such potential threat that could exploit NBTI and severely affect its performance. The development of an effective and efficient countermeasure against it is, therefore, highly critical. Accordingly, we present a comprehensive FPGA security scheme, comprising novel elements of hardware Trojan infection, detection, and mitigation, to protect FPGA applications against the hardware Trojan. Built around the threat model of a naval warship’s integrated self-protection system (ISPS), we propose a threshold voltage-triggered hardware Trojan that operates in a threshold voltage region of 0.45V to 0.998V, consuming ultra-low power (10.5nW), and remaining stealthy with an area overhead as low as 1.5% for a 28 nm technology node. The hardware Trojan detection sub-scheme provides a unique lightweight threshold voltage-aware sensor with a detection sensitivity of 0.251mV/nA. With fixed and dynamic ring oscillator-based sensor segments, the precise measurement of frequency and delay variations in response to shifts in the threshold voltage of a PMOS transistor is also proposed. Finally, the FPGA security scheme is reinforced with an online transistor dynamic scaling (OTDS) to mitigate the impact of hardware Trojan through run-time tolerant circuitry capable of identifying critical gates with worst-case drain current degradation
Adversarial Deep Learning and Security with a Hardware Perspective
Adversarial deep learning is the field of study which analyzes deep learning in the presence of adversarial entities. This entails understanding the capabilities, objectives, and attack scenarios available to the adversary to develop defensive mechanisms and avenues of robustness available to the benign parties. Understanding this facet of deep learning helps us improve the safety of the deep learning systems against external threats from adversaries. However, of equal importance, this perspective also helps the industry understand and respond to critical failures in the technology. The expectation of future success has driven significant interest in developing this technology broadly. Adversarial deep learning stands as a balancing force to ensure these developments remain grounded in the real-world and proceed along a responsible trajectory. Recently, the growth of deep learning has begun intersecting with the computer hardware domain to improve performance and efficiency for resource constrained application domains. The works investigated in this dissertation constitute our pioneering efforts in migrating adversarial deep learning into the hardware domain alongside its parent field of research
Runtime Detection of a Bandwidth Denial Attack from a Rogue Network-on-Chip
Chips with high computational power are the crux of today’s pervasive complex digital systems. Microprocessor circuits are evolving towards many core designs with the integration of hundreds of processing cores, memory elements and other devices on a single chip to sustain high performance computing while maintaining low design costs. Two decisive paradigm shifts in the semiconductor industry have made this evolution possible: (a) architectural and (b) organizational.
At the heart of the architectural innovation is a scalable high speed data communication structure, the network-on-chip (NoC). NoC is an interconnect network for the glueless integration of on-chip components in the modern complex communication centric designs. In the recent days, NoC has replaced the traditional bus based architecture owing to its structured and modular design, scalability and low design cost. The organizational revolution has resulted in a globalized and collaborative supply chain with pervasive use of third party intellectual properties to reduce the time-to-market and overall design costs.
Despite the advantages of these paradigm shifts, modern system-on-chips pose a plethora of security vulnerabilities. This work explores a threat model arising from a malicious NoC IP embedded with a hardware trojan affecting the resource availability of on-chip components. A rigorous simulation infrastructure is established to evaluate the feasibility and potency of such an attack. Further, a non-invasive runtime monitoring technique is proposed and thoroughly investigated to ensure the trustworthiness of a third party NoC IP with low overheads
- …