TL;DR: It is shown that arbiter-based PUFs are realizable and well suited to build key-cards that need to be resistant to physical attacks and to be identified securely and reliably over a practical range of environmental variations such as temperature and power supply voltage.
Abstract: Modern cryptographic protocols are based on the premise that only authorized participants can obtain secret keys and access to information systems. However, various kinds of tampering methods have been devised to extract secret keys from conditional access systems such as smartcards and ATMs. Arbiter-based physical unclonable functions (PUFs) exploit the statistical delay variation of wires and transistors across integrated circuits (ICs) in manufacturing processes to build unclonable secret keys. We fabricated arbiter-based PUFs in custom silicon and investigated the identification capability, reliability, and security of this scheme. Experimental results and theoretical studies show that a sufficient amount of inter-chip variation exists to enable each IC to be identified securely and reliably over a practical range of environmental variations such as temperature and power supply voltage. We show that arbiter-based PUFs are realizable and well suited to build, for example, key-cards that need to be resistant to physical attacks.
TL;DR: This paper quantifies tradeoffs faced in allocating bandwidth, granting access, and queuing, as well as throughput requirements, and concludes that an arbitered channel design is the best choice.
Abstract: This paper discusses connectivity between neuromorphic chips, which use the timing of fixed-height fixed-width pulses to encode information. Address-events (log/sub 2/(N)-bit packets that uniquely identify one of N neurons) are used to transmit these pulses in real time on a random-access time-multiplexed communication channel. Activity is assumed to consist of neuronal ensembles-spikes clustered in space and in time. This paper quantifies tradeoffs faced in allocating bandwidth, granting access, and queuing, as well as throughput requirements, and concludes that an arbitered channel design is the best choice. The arbitered channel is implemented with a formal design methodology for asynchronous digital VLSI CMOS systems, after introducing the reader to this top-down synthesis technique. Following the evolution of three generations of designs, it is shown how the overhead of arbitrating, and encoding and decoding, can be reduced in area (from N to /spl radic/N) by organizing neurons into rows and columns, and reduced in time (from log/sub 2/(N) to 2) by exploiting locality in the arbiter tree and in the row-column architecture, and clustered activity. Throughput is boosted by pipelining and by reading spikes in parallel. Simple techniques that reduce crosstalk in these mixed analog-digital systems are described.
TL;DR: Numerical modeling attacks on several proposed strong physical unclonable functions (PUFs) are discussed, leading to new design requirements for secure electrical Strong PUFs, and will be useful to PUF designers and attackers alike.
Abstract: We discuss numerical modeling attacks on several proposed strong physical unclonable functions (PUFs). Given a set of challenge-response pairs (CRPs) of a Strong PUF, the goal of our attacks is to construct a computer algorithm which behaves indistinguishably from the original PUF on almost all CRPs. If successful, this algorithm can subsequently impersonate the Strong PUF, and can be cloned and distributed arbitrarily. It breaks the security of any applications that rest on the Strong PUF's unpredictability and physical unclonability. Our method is less relevant for other PUF types such as Weak PUFs. The Strong PUFs that we could attack successfully include standard Arbiter PUFs of essentially arbitrary sizes, and XOR Arbiter PUFs, Lightweight Secure PUFs, and Feed-Forward Arbiter PUFs up to certain sizes and complexities. We also investigate the hardness of certain Ring Oscillator PUF architectures in typical Strong PUF applications. Our attacks are based upon various machine learning techniques, including a specially tailored variant of logistic regression and evolution strategies. Our results are mostly obtained on CRPs from numerical simulations that use established digital models of the respective PUFs. For a subset of the considered PUFs-namely standard Arbiter PUFs and XOR Arbiter PUFs-we also lead proofs of concept on silicon data from both FPGAs and ASICs. Over four million silicon CRPs are used in this process. The performance on silicon CRPs is very close to simulated CRPs, confirming a conjecture from earlier versions of this work. Our findings lead to new design requirements for secure electrical Strong PUFs, and will be useful to PUF designers and attackers alike.
TL;DR: This paper describes Fastpass, a datacenter network architecture built using this principle that achieves high throughput comparable to current networks at a 240x reduction is queue lengths, and achieves much fairer and consistent flow throughputs than the baseline TCP.
Abstract: An ideal datacenter network should provide several properties, including low median and tail latency, high utilization (throughput), fair allocation of network resources between users or applications, deadline-aware scheduling, and congestion (loss) avoidance. Current datacenter networks inherit the principles that went into the design of the Internet, where packet transmission and path selection decisions are distributed among the endpoints and routers. Instead, we propose that each sender should delegate control---to a centralized arbiter---of when each packet should be transmitted and what path it should follow. This paper describes Fastpass, a datacenter network architecture built using this principle. Fastpass incorporates two fast algorithms: the first determines the time at which each packet should be transmitted, while the second determines the path to use for that packet. In addition, Fastpass uses an efficient protocol between the endpoints and the arbiter and an arbiter replication strategy for fault-tolerant failover. We deployed and evaluated Fastpass in a portion of Facebook's datacenter network. Our results show that Fastpass achieves high throughput comparable to current networks at a 240x reduction is queue lengths (4.35 Mbytes reducing to 18 Kbytes), achieves much fairer and consistent flow throughputs than the baseline TCP (5200x reduction in the standard deviation of per-flow throughput with five concurrent connections), scalability from 1 to 8 cores in the arbiter implementation with the ability to schedule 2.21 Terabits/s of traffic in software on eight cores, and a 2.5x reduction in the number of TCP retransmissions in a latency-sensitive service at Facebook.
TL;DR: In this article, the authors describe a system and methodology for automated or proactive network security (active firewall) which includes methodology for verifying or authenticating communications between network components (e.g., sensor, arbiter, and actor) using cryptographic keys or digital certificates.
Abstract: System and methodology providing automated or “proactive” network security (“active” firewall) are described. The system implements methodology for verifying or authenticating communications, especially between network security components thereby allowing those components to share information. In one embodiment, a system implementing an active firewall is provided which includes methodology for verifying or authenticating communications between network components (e.g., sensor(s), arbiter, and actor(s)), using cryptographic keys or digital certificates. Certificates may be used to digitally sign a message or file and, in a complementary manner, to verify a digital signature. At the outset, particular software components that may participate in authenticated communication are specified, including creating a digital certificate for each such software component. Upon detection by a sensor that an event of interest that has occurred in the computer network system, the system may initiate authenticated communication between the sensor component and a central arbiter (e.g., “event orchestrator”) component, so that the sensor may report the event to the arbiter or “brain.” Thereafter, the arbiter (if it chooses to act on that information) initiates authenticated communication between itself and a third software component, an “actor” component (e.g., “firewall”). The arbiter may indicate to the actor how it should handle the event. The actor or firewall, upon receiving the information, may now undertake appropriate action, such as dynamically creating or modifying rules for appropriately handling the event, or it may choose to simply ignore the information.