SecSens - Security Architecture for Wireless Sensor Networks

Bagci, Faruk; Ungerer, Theo; Bagherzadeh, Nader

doi:10.1109/sensorcomm.2009.74

Cited by 18 publications

(4 citation statements)

References 8 publications

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“…WiFi signals include a "preamble" which is used by the receiver to determine channel state. One approach that can be used to detect tampering is to monitor channel state variation (Bagci, 2016).…”

Section: Wireless Tamperingmentioning

confidence: 99%

Changepoint Detection in the Presence of Outliers

Fearnhead

Rigaill

2018

Journal of the American Statistical Association

142

138

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Many traditional methods for identifying changepoints can struggle in the presence of outliers, or when the noise is heavy-tailed. Often they will infer additional changepoints in order to fit the outliers. To overcome this problem, data often needs to be pre-processed to remove outliers, though this is difficult for applications where the data needs to be analysed online. We present an approach to changepoint detection that is robust to the presence of outliers. The idea is to adapt existing penalised cost approaches for detecting changes so that they use loss functions that are less sensitive to outliers. We argue that loss functions that are bounded, such as the classical biweight loss, are particularly suitable -as we show that only bounded loss functions are robust to arbitrarily extreme outliers. We present an efficient dynamic programming algorithm that can find the optimal segmentation under our penalised cost criteria. Importantly, this algorithm can be used in settings where the data needs to be analysed online. We show that we can consistently estimate the number of changepoints, and accurately estimate their locations, using the biweight loss function. We demonstrate the usefulness of our approach for applications such as analysing well-log data, detecting copy number variation, and detecting tampering of wireless devices.

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Section: Wireless Tamperingmentioning

confidence: 99%

Changepoint Detection in the Presence of Outliers

Fearnhead

Rigaill

2018

Journal of the American Statistical Association

142

138

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“…Cryptographic protocols and infrastructures have been developed for securing communication in sensor networks [2]. However, neither can extend the trust perimeter to include the sensing element itself.…”

Section: A Related Workmentioning

confidence: 99%

Sensor physical unclonable functions

Rosenfeld

Gavas

Karri

2010

2010 IEEE International Symposium on Hardware-Oriented Security and Trust (HOST)

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We propose a novel variety of sensor that extends the functionality of conventional physical unclonable functions to provide authentication, unclonability, and verification of a sensed value. This new class of device addresses the vulnerability in typical sensing systems whereby an attacker can spoof measurements by interfering with the analog signals that pass from the sensor element to the embedded microprocessor. The concept can be applied to any type of analog sensor.

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“…Recently, phishers have also begun to use images to evade detection by text-based anti-phishing filters. While certified cryptographic protocols and infrastructures have been developed for securing the communication channels [4], they cannot prevent false pretenses from masquerading as trustworthy imaging devices in the electronic communications. This security hole can be closed up by integrating dedicated security functions into the image sensor [5].…”

Section: Introductionmentioning

confidence: 99%

CMOS Image Sensor Based Physical Unclonable Function for Coherent Sensor-Level Authentication

Cao

Zhang

Zalivaka

et al. 2015

IEEE Trans. Circuits Syst. I

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In the applications of biometric authentication and video surveillance, the image sensor is expected to provide certain degree of trust and resiliency. This paper presents a new low-cost CMOS image sensor based physical unclonable function (PUF) targeting a variety of security, privacy and trusted protocols that involves image sensor as a trusted entity. The proposed PUF exploits the intrinsic imperfection during the image sensor manufacturing process to generate unique and reliable digital signatures. The proposed differential readout stabilizes the response bits extracted from the random fixed pattern noises of selected pixel pairs determined by the applied challenge against supply voltage and temperature variations. The threshold of difference can be tightened to winnow out more unstable response bits from the challenge-response space offered by modern image sensors to enhance the reliability under harsher operating conditions and loosened to improve its resiliency against masquerade attacks in routine operating environment. The proposed design can be classified as a weak PUF which is resilient to modeling attacks, with direct access to its challenge-response pair restricted by the linear feedback shift register. Our experiments on the reset voltages extracted from a 64×64 image sensor fabricated in 180 nm 3.3 V CMOS technology demonstrated that robust and reliable challengeresponse pairs can be generated with a uniqueness of 49.37% and a reliability of 99.80% under temperature variations of 15∼115 • C and supply voltage variations of 3∼3.6 V.

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SecSens - Security Architecture for Wireless Sensor Networks

Cited by 18 publications

References 8 publications

Changepoint Detection in the Presence of Outliers

Changepoint Detection in the Presence of Outliers

Sensor physical unclonable functions

CMOS Image Sensor Based Physical Unclonable Function for Coherent Sensor-Level Authentication

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