VITI: A Tiny Self-Calibrating Sensor for Power-Variation Measurement in FPGAs (original) (raw)
Related papers
UCloD: Small Clock Delays to Mitigate Remote Power Analysis Attacks
IEEE Access
This paper presents UCloD, a novel random clock delay-based robust and scalable countermeasure against recently discovered remote power analysis (RPA) attacks. UCloD deploys very small clock delays (in the picosecond range) generated using the tapped delays lines (TDLs) to mitigate RPA attacks. UCloD provides the most robust countermeasures demonstrated thus far against RPA attacks. RPA attacks use delay sensors, such as Time to Digital Converters (TDC) or Ring Oscillators (ROs) to measure voltage fluctuations occurring in power delivery networks (PDNs) of Field Programmable Gate Arrays (FPGAs). These voltage fluctuations reveal secret information, such as secret keys of cryptographic circuits. The only countermeasure proposed thus far activates ROs to consume significant power and has managed to secure Advanced Encryption Standard (AES) circuits for up to 300,000 encryptions. Using TDLs available in FPGAs, UCloD randomly varies the clock to the cryptographic circuits under attack to induce noise in the adversary's delay sensor(s). We demonstrate correlation power analysis (referred to as CPA) attack resistance of UCloD AES implementations for up to one million encryptions. Compared to an unprotected AES circuit, UCloD implementations have minimal overheads (0.2% Slice LUT overhead and 4.8% Slice register overhead for Xilinx implementations and 0.5% LogicCells overhead for Lattice Semiconductor implementations).
Updates on the security of FPGAs against power analysis attacks
2006
This paper reports on the security of cryptographic algorithms implemented on FPGAs against power analysis attacks. We first present some improved experiments against these reconfigurable devices, due to an improved measurement process. Although it is usually believed that FPGAs are noisy targets for such attacks, it is shown that simple power consumption models can nearly perfectly correlate with actual measurements.
Intensive Analysis of Physical Parameters of Power Sensors for Remote Side-Channel Attacks
The ISC International Journal of Information Security, 2021
Side-channel analysis methods can reveal the secret information of digital electronic systems by analyzing the dependency between the power consumption of implemented cryptographic algorithms and the secret data. Recent studies show that it is possible to gather information about power consumption from FPGAs without any physical access. High flexibilities of modern FPGAs cause that they are used for cloud accelerator in Platform as a Service (PaaS) system; however, new serious vulnerabilities emerged for these platforms. Although there are some reports about how switching activities from one region of FPGA affect other regions, details of this technique are not analyzed. In this paper, we analyzed the strength of this kind of attack and examined the impact of geometrical and electrical parameters of the victim/attacker modules on the efficiency of this attack. We utilized a Zynq-based Xilinx platform as the device under attack. Experimental results and analyses show that the distance between the victim module and the sensor modules is not the only effective parameter on the quality of attack; the influence of the relational location of victim/attacker modules could be more considerable on the quality of attack. Results of this analysis can help the FPGA manufacturer and IP developers to protect their systems against this serious attack. https://www.isecure-journal.com/article\_132589.html
IEEE Transactions on Circuits and Systems I: Regular Papers, 2019
Modern power analysis attacks (PAAs) and existing countermeasures pose unique challenges on the design of simultaneously secure, power efficient, and high-performance ICs. In a typical PAA, power information is collected with a monitoring circuit connected to the compromised device. The non-typical voltage variations induced on a power distribution network (PDN) by such a malicious probing are sensed with on-chip sensors and exploited in this paper for detecting PAAs in real-time using statistical analysis. A closed-form expression for the voltage variations caused by malicious probing is provided. Guidelines with respect to the PDN characteristics and number of sensors are proposed for securing power delivery. The PAA detection system is designed in a 45-nm standard CMOS process. Based on the simulation results, a PAA on an IBM benchmarked microprocessor is detected with the accuracy of 88% with 30 on-chip sensors. Power overhead of 0.34% and 14.3% is demonstrated in, respectively, the IBM microprocessor and a typical advanced encryption standard system. In a practical cryptographic device, security sensitive PDN regions can be identified, significantly reducing the number of the on-chip sensors.
Secured-by-design FPGA against side-channel attacks based on power consumption
2017
Power Analysis Attacks pose serious threats to hardware implementations of cryptographic systems. To retrieve the secret key, the attackers can exploit the mutual information between power consumption and processed data / operations through monitoring the power consumption of the cryptosystems. Field Programmable Gate Arrays (FPGA) have emerged as attractive implementation platforms for providing hardware-like performance and software-like flexibility for cryptosystem developers. These features come at the expense of larger power consumption, which makes FPGAs more vulnerable to power attacks. Different countermeasures have been introduced in the literature, but as they have originally been developed for Application-Specific Integrated Circuits (ASIC), mapping them onto FPGAs degrades their effectiveness. In this work we propose a logic
Enhancing power analysis attacks against cryptographic devices
IET Circuits, Devices & Systems, 2008
A current-measuring technique is introduced, which promises to substantially enhance power analysis attacks against cryptographic co-processors. The proposed technique exploits an active circuit to measure the instantaneous current consumption of a device under attack while supplying, at the same time, the device with a stable voltage. Higher gain-bandwidth product, higher sensitivity and lower insertion error are the main advantages with respect to a resistor-based measurement. Experimental results when the proposed circuit is used to measure the current consumption of an FPGA are reported, and the achievable advantage in terms of sensitivity is discussed. Results of a differential power analysis attack are reported too.
Power-analysis attacks on an FPGA–first experimental results
Cryptographic Hardware and Embedded …, 2003
Field Programmable Gate Arrays (FPGAs) are becoming increasingly popular, especially for rapid prototyping. For implementations of cryptographic algorithms, not only the speed and the size of the circuit are important, but also their security against implementation attacks such as side-channel attacks. Power-analysis attacks are typical examples of side-channel attacks, that have been demonstrated to be effective against implementations without special countermeasures. The flexibility of FPGAs is an important advantage in real applications but also in lab environments. It is therefore natural to use FPGAs to assess the vulnerability of hardware implementations to power-analysis attacks. To our knowledge, this paper is the first to describe a setup to conduct power-analysis attacks on FPGAs. We discuss the design of our hand-made FPGA-board and we provide a first characterization of the power consumption of a Virtex 800 FPGA. Finally we provide strong evidence that implementations of elliptic curve cryptosystems without specific countermeasures are indeed vulnerable to simple power-analysis attacks.
Experiments in attacking FPGA-based embedded systems using differential power analysis
2008
In the decade since the concept was publicly introduced, power analysis attacks on cryptographic systems have become an increasingly studied topic in the computer security community. Research into countermeasures for these cryptographic systems has intensified as well. Experiments have been conducted showing the potential effectiveness of power analysis attacks and preventative techniques on both software (e.g. smartcard, DSP) and hardware (e.g. ASIC, FPGA) processing elements. One key observation that motivates our work is that the majority of the research into power analysis on FPGA-based cryptographic systems has been a) theoretical in nature, b) evaluated through simulation, or c) experimented using custom hardware that does not closely mirror real-world systems. In this paper, we look to bridge this gap between theory and practice by detailing our experience in performing a Differential Power Analysis (DPA) attack on a commercial FPGA development board. We present an automated data acquisition and analysis design for an FPGA-based implementation of the Data Encryption Standard (DES), and discuss some of the challenges and obstacles that we encountered when performing the DPA attack on our chosen commercial platform.
Real-Time Detection of Power Analysis Attacks by Machine Learning of Power Supply Variations On-Chip
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 2018
Reliably and power efficiently securing integrated systems against advanced power analysis attacks is a significant design challenge in modern ICs. Power masking and hiding are typical countermeasures for increasing system resilience for power attacks at the expense of the overall system performance and power efficiency. These method are however not able to alert the user or trigger additional protective actions in case of the attack. In this paper, a method for detecting power attacks in real-time is proposed. The proposed approach exploits statistical methods to analyze the on-chip voltage variations across an onchip power grid and detect the attacker probe connected to the system. The problem of the full security coverage of the power grid is formulated and solved in this paper. Adjusting the density of the on-chip sensors and exploiting sparse analysis techniques is considered to simultaneously enhance the accuracy and power efficiency of the proposed solution. The proposed attack detection system is designed, simulated, and evaluated in Simulink based on IBM microprocessor benchmark data. Machine learning models are trained in Python and with scikit-learn machine learning library. The proposed system has been demonstrated to efficiently detect power analysis attack within a period of time that is orders of magnitude shorter than a typical attack duration length. The system is expected to exhibit high detection accuracy and power efficiency across a wide spectrum of integrated systems.
Method for dynamic power monitoring on FPGAs
2014 24th International Conference on Field Programmable Logic and Applications (FPL), 2014
The ever-increasing integration densities make it possible to configure multi-core systems composed of hundreds of blocks on existing FPGAs that may influence overall consumption differently. Observing total consumption is not sufficient to accurately assess internal circuit activity to be able to deploy effective adaptation strategies. In this case monitoring techniques are required. This paper presents a CAD flow for high-level dynamic power estimation on FPGAs. The method is based on the monitoring of toggling activity for relevant signals by introducing event counters. The appropriate signals are selected using the Greedy Stepwise filter. Our approach is based on a generic method that is able to produce a power model for any block-based circuit. We evaluated our contribution on a SoC RTL model implemented on Spartan3, Virtex5, and Spartan6 FPGAs. A power model and monitors are automatically generated to achieve the best tradeoff between accuracy and overhead.