Browsing the modern kitchen - a feast of gender, place and culture (part 1)

Assembling 10 essays from around the globe which engage variously with the space in which food preparation occurs—the kitchen—revealed stunning diversity but also commonalities. In this first of two sets of theme papers on this vital but often unexamined domestic space, the discourse of modernity unites the look and use of twentieth-century kitchens in Australia, Britain and Finland. Imbued with notions of scientific management, the modern kitchen had some common designs which prescribed women's place within it—first as the main occupant and then as the family overseer. The construction of this semi-private space also involved particular domestic technologies which, as the new century dawns, now literally connect the kitchen to the world beyond via the internet fridge. This Introduction begins the two-part feast of gender, place and culture—with an overview of Australia and sketch of subsequent essays—Supski on mid-century migrant Australia, Saarikangas on Finland, Bennett on rural Britain and Watkins on the fridge.

The power of play-break for automatic detection and browsing of self-consumable sport video highlights

To enable content-based retrieval, highlights extraction from broadcasted sport video has been an active research topic in the last decade. There is a well-known theory that high-level semantic, such as goal in soccer can be detected based on the occurrences of specific audio and visual features that can be extracted automatically. However, there is yet a definitive solution for the scope (i.e. start and end) of the detection for self consumable highlights. Thus, in this paper we will primarily demonstrate the benefits of using play-break for this purpose. Moreover, we also propose a browsing scheme that is based on integrated play-break and highlights (extended from [1]). To validate our approach, we will present the results from some experiments and a user study.

Piggyback hunting-browsing the internet in Australia via unsecured wireless networks : virtual theft or acceptable behaviour in an online world?

In a world that is increasingly dominated by the Internet, there is a growing demand for low cost access at the users convenience. The expansion of wireless Internet networks, in particular unsecured wireless Internet networks, gives rise to novel challenges for the regulation of Internet access. The ability to access unsecured wireless Internet networks with ease and with very little impact upon the owner of the network suggests that such 'piggybacking' may be criminal behaviour or may amount to an actionable civil wrong. This paper will explore the legal ramifications of piggybacking an unsecured wireless network with knowledge that there is no entitlement to the use of the network and will consider what Australian authorities should do about this situation. This paper will look at the position in Australia and juxtapose this with that of the United Kingdom and the United States of America. In both the United Kingdom and the United States of America prosecutions have taken place of individuals who knowingly accessed unsecured wireless
networks for their own personal use.

Anonymous web browsing through predicted pages

Anonymous web browsing is an emerging hot topic with many potential applications for privacy and security. However, research on low latency anonymous communication, such as web browsing, is quite limited; one reason is the intolerable delay caused by the current dominant dummy packet padding strategy, as a result, it is hard to satisfy perfect anonymity and limited delay at the same time for web browsing. In this paper, we extend our previous proposal on using prefetched web pages as cover traffic to obtain perfect anonymity for anonymous web browsing, we further explore different aspects in this direction. Based on Shannon’s perfect secrecy theory, we formally established a mathematical model for the problem, and defined a metric to measure the cost of achieving perfect anonymity. The experiments on a real world data set demonstrated that the proposed strategy can reduce delay more than ten times compared to the dummy packet padding methods, which confirmed the vast potentials of the proposed strategy.

Efficient web browsing with perfect anonymity using page prefetching

Anonymous web browsing is a hot topic with many potential applications for privacy reasons. The current dominant strategy to achieve anonymity is packet padding with dummy packets as cover traffic. However, this method introduces extra bandwidth cost and extra delay. Therefore, it is not practical for anonymous web browsing applications. In order to solve this problem, we propose to use the predicted web pages that users are going to access as the cover traffic rather than dummy packets. Moreover, we defined anonymity level as a metric to measure anonymity degrees, and established a mathematical model for anonymity systems, and transformed the anonymous communication problem into an optimization problem. As a result, users can find tradeoffs among anonymity level and cost. With the proposed model, we can describe and compare our proposal and the previous schemas in a theoretical style. The preliminary experiments on the real data set showed the huge potential of the proposed strategy in terms of resource saving.

Attacking anonymous web browsing at local area networks through browsing dynamics

The majority of current anonymous systems focus on improving anonymity at the network and website level in order to defend against traffic analysis attacks. However, the vulnerability of the connections between end users and the anonymous network do not attract any attention yet. For the first time, we reveal an end user browsing dynamics based attack on anonymous browsing systems at the LAN where the victim locates. This new attack method is fundamentally different from existing attack methodologies. In general, web surfers browse the web following certain patterns, such as requesting a web page, viewing it and requesting another page. The browsing pattern of a victim can be clearly observed by a local adversary when the victim is viewing the web without protection. Unfortunately, browsing dynamics releases rich information for attacking even though the web page content is encrypted. In order to show how a local eavesdropper can decipher which pages have been viewed with the knowledge of user browsing dynamics and the public information of a given website, we established a specific hidden Markov model to represent browsing dynamics for the website. By using this model, we can then identify the optimal of the accessed pages using the Viterbi algorithm. In order to confirm the effectiveness of the revealed attack method, we have conducted extensive experiments on a real data set. The results demonstrated that the attack accuracy can be more than 80%. A few possible counter-attack strategies are discussed at the end of the paper.

Browsing behavior mimicking attacks on popular web sites for large botnets

With the significant growth of botnets, application layer DDoS attacks are much easier to launch using large botnet, and false negative is always a problem for intrusion detection systems in real practice. In this paper, we propose a novel application layer DDoS attack tool, which mimics human browsing behavior following three statistical distributions, the Zipf-like distribution for web page popularity, the Pareto distribution for page request time interval for an individual browser, and the inverse Gaussian distribution for length of browsing path. A Markov model is established for individual bot to generate attack request traffic. Our experiments indicated that the attack traffic that generated by the proposed tool is pretty similar to the real traffic. As a result, the current statistics based detection algorithms will result high false negative rate in general. In order to counter this kind of attacks, we discussed a few preliminary solutions at the end of this paper.

Temporal semantic compression for video browsing

We present a video browsing approach, termed Temporal Semantic Compression (TSC), that uses automated measures of interest to support today's foraging behaviours. Conventional browsers 'compress' a video stream using simple 2x or 8x fast-forward. TSC browsers dynamically filter video based on a single user gesture to leave out more or less of the boring bits. We demonstrate a browser with an example interest measure, derived from an automated estimate of movie tempo, to forage in terms of narrative structures such as crises, climaxes, and action sequence book-ends. Media understanding algorithms facilitate browsing, and interactivity enables the human-in-the-loop to cope when those algorithms fail to cross the semantic gap.

Interactively browsing movies in terms of action, foreshadowing and resolution

We describe a novel video player that uses Temporal Semantic Compression (TSC) to present a compressed summary of a movie. Compression is based on tempo which is derived from film rhythms. The technique identifies periods of action, drama, foreshadowing and resolution, which can be mixed in different amounts to vary the kind of summary presented. The compression algorithm is embedded in a video player, so that the summary can be interactively recomputed during playback.

Social reader: towards browsing the social web

We describe Social Reader, a feed-reader-plus-social-network aggregator that mines comments from social media in order to display a user’s relational neighborhood as a navigable social network. Social Reader’s network visualization enhances mutual awareness of blogger communities, facilitates their exploration and growth with a fully dragn- drop interface, and provides novel ways to filter and summarize people, groups, blogs and comments. We discuss the architecture behind the reader, highlight tasks it adds to the workflow of a typical reader, and assess their cost. We also explore the potential of mood-based features in social media applications. Mood is particularly relevant to social media, reflecting the personal nature of the medium. We explore two prototype mood-based features: colour coding the mood of recent posts according to a valence/arousal map, and a mood-based abstract of recent activity using image media. A six week study of the software involving 20 users confirmed the usefulness of the novel visual display, via a quantitative analysis of use logs, and an exit survey.

Predicted packet padding for anonymous web browsing against traffic analysis attacks

Anonymous communication has become a hot research topic in order to meet the increasing demand for web privacy protection. However, there are few such systems which can provide high level anonymity for web browsing. The reason is the current dominant dummy packet padding method for anonymization against traffic analysis attacks. This method inherits huge delay and bandwidth waste, which inhibits its use for web browsing. In this paper, we propose a predicted packet padding strategy to replace the dummy packet padding method for anonymous web browsing systems. The proposed strategy mitigates delay and bandwidth waste significantly on average. We formulated the traffic analysis attack and defense problem, and defined a metric, cost coefficient of anonymization (CCA), to measure the performance of anonymization. We thoroughly analyzed the problem with the characteristics of web browsing and concluded that the proposed strategy is better than the current dummy packet padding strategy in theory. We have conducted extensive experiments on two real world data sets, and the results confirmed the advantage of the proposed method.

Effectiveness of Milorganite® as a Repellent to Protect Ornamental and Agronomic Plants From Deer Over-Browsing

When deer populations become locally overabundant, browsing of ornamental and agronomic plants negatively affects plant establishment, survival, and productivity. Milorganite® is a slow-release, organic fertilizer produced from human sewage. We tested Milorganite® as a deer repellent on chrysanthemums (Chrysanthemums morifolium) in an urban/suburban environment, and soybeans (Gycine max) in a rural agriculture environment. Six beds of chrysanthemums at two sites were monitored for 28 to 35 days. Treatment plants received a top dressing of 104 grams of Milorganite® (1120.9 kg/ha). Milorganite® treated plants had more (P < 0.001) terminal buds and achieved greater height (P < 0.002) compared to controls at one site, however damage observed was similar at the second site. In a second experiment, 0.2-ha plots of soybeans (Glycine max) were planted on five rural properties in northeastern Georgia and monitored for ≥ 30 days. Treated areas received 269 kg/ha of Milorganite®. In 4 of 5 sites, Milorganite® delayed browsing on treated plants from 1 week to > 5 weeks post-planting. Duration of the protection appeared to be related to the difference in deer density throughout most of the study areas. Results of this study indicate Milorganite® has potential use as a deer repellent.