TL;DR: In this paper, the authors examine specific methods for analyzing power consumption measurements to find secret keys from tamper resistant devices. And they also discuss approaches for building cryptosystems that can operate securely in existing hardware that leaks information.
Abstract: Cryptosystem designers frequently assume that secrets will be manipulated in closed, reliable computing environments. Unfortunately, actual computers and microchips leak information about the operations they process. This paper examines specific methods for analyzing power consumption measurements to find secret keys from tamper resistant devices. We also discuss approaches for building cryptosystems that can operate securely in existing hardware that leaks information.
TL;DR: By carefully measuring the amount of time required to perform private key operalions, attackers may be able to find fixed Diffie-Hellman exponents, factor RSA keys, and break other cryptosystems.
Abstract: By carefully measuring the amount of time required tm perform private key operalions, attackers may be able to find fixed Diffie-Hellman exponents, factor RSA keys, and break other cryptosystems. Against, a valnerable system, the attack is computationally inexpensive and often requires only known ciphertext. Actual systems are potentially at risk, including cryptographic tokens, network-based cryptosystems, and other applications where attackers can make reasonably accurate timing measurements. Techniques for preventing the attack for RSA and Diffie-Hellman are presented. Some cryptosystems will need to be revised to protect against the attack, and new protocols and algorithms may need to incorporate measures to prevenl timing attacks.
TL;DR: A classical model is used for the power consumption of cryptographic devices based on the Hamming distance of the data handled with regard to an unknown but constant reference state, which allows an optimal attack to be derived called Correlation Power Analysis.
Abstract: A classical model is used for the power consumption of cryptographic devices. It is based on the Hamming distance of the data handled with regard to an unknown but constant reference state. Once validated experimentally it allows an optimal attack to be derived called Correlation Power Analysis. It also explains the defects of former approaches such as Differential Power Analysis.
TL;DR: In this paper, the authors examined the noise characteristics of the power signals and developed an approach to model the signal-to-noise ratio (SNR) using a multiple-bit attack.
Abstract: This paper examines how monitoring power consumption signals might breach smart-card security. Both simple power analysis and differential power analysis attacks are investigated. The theory behind these attacks is reviewed. Then, we concentrate on showing how power analysis theory can be applied to attack an actual smart card. We examine the noise characteristics of the power signals and develop an approach to model the signal-to-noise ratio (SNR). We show how this SNR can be significantly improved using a multiple-bit attack. Experimental results against a smart-card implementation of the Data Encryption Standard demonstrate the effectiveness of our multiple-bit attack. Potential countermeasures to these attacks are also discussed.
TL;DR: Spectre as mentioned in this paper is a side channel attack that can leak the victim's confidential information via side channel to the adversary. And it can read arbitrary memory from a victim's process.
Abstract: Modern processors use branch prediction and speculative execution to maximize performance. For example, if the destination of a branch depends on a memory value that is in the process of being read, CPUs will try to guess the destination and attempt to execute ahead. When the memory value finally arrives, the CPU either discards or commits the speculative computation. Speculative logic is unfaithful in how it executes, can access the victim's memory and registers, and can perform operations with measurable side effects. Spectre attacks involve inducing a victim to speculatively perform operations that would not occur during correct program execution and which leak the victim's confidential information via a side channel to the adversary. This paper describes practical attacks that combine methodology from side channel attacks, fault attacks, and return-oriented programming that can read arbitrary memory from the victim's process. More broadly, the paper shows that speculative execution implementations violate the security assumptions underpinning numerous software security mechanisms, including operating system process separation, containerization, just-in-time (JIT) compilation, and countermeasures to cache timing and side-channel attacks. These attacks represent a serious threat to actual systems since vulnerable speculative execution capabilities are found in microprocessors from Intel, AMD, and ARM that are used in billions of devices. While makeshift processor-specific countermeasures are possible in some cases, sound solutions will require fixes to processor designs as well as updates to instruction set architectures (ISAs) to give hardware architects and software developers a common understanding as to what computation state CPU implementations are (and are not) permitted to leak.