As the concept of the Smart Home is being embraced globally, IoT devices such as the Amazon Echo, Google Home, and Nest Thermostat are becoming a part of more and more households. In the data-driven world we live in today, internet service providers (ISPs) and companies are collecting large amounts of data and using it to learn about their customers. As a result, it is becoming increasingly important to understand what information ISPs are capable of collecting. IoT devices in particular exhibit distinct behavior patterns and specific functionality which make them especially likely to reveal sensitive information. Collection of this data provides valuable information and can have some serious privacy implications. In this work I present an approach to fingerprinting IoT devices behind private networks while only examining last-mile internet traffic . Not only does this attack only rely on traffic that would be available to an ISP, it does not require changes to existing infrastructure. Further, it does not rely on packet contents, and therefore works despite encryption. Using a database of 64 million packets logged over 15 weeks I was able to train machine learning models to classify the Amazon Echo Dot, Amazon Echo Show, Eufy Genie, and Google Home consistently. This approach combines unsupervised and supervised learning and achieves a precision of 99.95\%, equating to one false positive per 2,000 predictions. Finally, I discuss the implication of identifying devices within a home.

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Media such as movies and images are nowadays produced and distributed digitally. It is usually simple to make copies of digital content. Consequently illegal pirate copies can be duplicated and distributed in large quantities. One way to deter authorized content receivers from illegally redistributing the media is watermarking. If individual watermarks are contained in the digital media and a receiver is a pirate and redistributes it, the pirate at the same time distributes his identity. Thus a located pirate copy can be traced back to the pirate. The watermarked media should otherwise be indistinguishable from the original media content. To distribute media content scalable transmission methods such as broadcast and multicast should be used. This way the distributor will only need to transmit the media once to reach all his authorized receivers. But since the same content is distributed to all receivers the requirement of individual watermarks seems to be contradictory. In this thesis we will show how individually watermarked media content can be transmitted in a scalable way. Known methods will be reviewed and a new method will be presented. The new method is independent of what type of distribution that is used. A system with robust watermarks that are difficult to remove is described. Only small parts of the media content will be needed to identify the pirates. The method will only give a small data expansion compared to distribution of non-watermarked media. We will also show how information theory tools can be used to expand the amount of data in the watermarks given a specific size of the media used for the watermarking. These tools can also be used to identify parts of the watermark that have been changed by deliberate deterioration of the watermarked media, made by pirates. / <p>Report code: LiU-Tek-Lic-2005:67.</p>

Molecular genetic protocols have been developed to provide evidence in infractions of wildlife statutes in Canada. We have utilized DNA marker systems to address specific questions in wildlife investigations based on their different levels of genetic variability. Multilocus DNA fingerprinting has been applied to poaching infractions to determine if tissue samples associated with a suspected poacher originated from the remains of an animal at a known illegal kill site. The hypervariability of the variable number of tandem repeat (VNTR) loci detected by multilocus DNA fingerprinting allows the individual identification of samples. Highly repetitive satellite DNA markers have been applied to determining the species of origin of unknown tissue samples based on their species-specificity. Satellite DNA profiling have provided evidence in illegal commercialization investigations involving species such as moose (Alcesalces) and white-tailed deer (Odocoileus virginianus), including the illegal addition of game meat in processed meat products. A sex-specific DNA locus, the sex-determining region on the Y-chromosome (Sry), has been utilized to determine the sex of cervid samples that have had gender-specific physical characteristics, antlers and genitalia removed in violation of the validation tag system. Finally, a polymerase chain reaction (PCR) based protocol has been established for the species identification of samples that produce minute amounts of DNA or degraded DNA. Cytochrome b sequences demonstrate low intra-specific levels of sequence divergence and higher inter-specific levels of sequence divergence. Cytochrome b sequence analysis has been applied to fish, game and domestic species commonly involved in wildlife investigations and to the identification o fa number of species, mostly seal species, involved in the trade of animal parts. / Thesis / Master of Science (MSc)

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