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Figure 6.1: Block Diagram representing the Experimental Methodology In recent times, online or web advertising has become an easy way to distribute

Figure 6 1: Block Diagram representing the Experimental Methodology In recent times, online or web advertising has become an easy way to distribute

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ment environment, they are sometimes deployed in a production environment, making
ment environment, they are sometimes deployed in a production environment, making
3. Ensuring correct compile time procedures to separate development environment
3. Ensuring correct compile time procedures to separate development environment
Figure 3.2: Communicate interface - example send and secureSend functions to perfor! a connection using HTTP and HTTPS protocols.
Figure 3.2: Communicate interface - example send and secureSend functions to perfor! a connection using HTTP and HTTPS protocols.
trusted authority. security depends on performing checks with reference to content published by a
trusted authority. security depends on performing checks with reference to content published by a
Figure 3.4: Sequence Diagram showing the Push Model
Figure 3.4: Sequence Diagram showing the Push Model
Figure 3.5: Sequence Diagram showing the Pull Model
Figure 3.5: Sequence Diagram showing the Pull Model
secure channel establishment and because of the potential privacy concerns
secure channel establishment and because of the potential privacy concerns
tool consistently obtains a given domain, edge, or resource that the other tool rarely or
tool consistently obtains a given domain, edge, or resource that the other tool rarely or
of the page loads of A. We compute this separately for both Crawlium and ZBrowse.
of the page loads of A. We compute this separately for both Crawlium and ZBrowse.
webpages (Table 4.3). large number (26) is required for obtaining over 90% of the edges from over 90% of the
webpages (Table 4.3). large number (26) is required for obtaining over 90% of the edges from over 90% of the
graph in a single page load would require two page loads. For instance, with 6 = 1, websites like wikipedia.org that return the entire inclusion
graph in a single page load would require two page loads. For instance, with 6 = 1, websites like wikipedia.org that return the entire inclusion
How many page loads were needed in the rest of our study? Figure 4.8 shows the
How many page loads were needed in the rest of our study? Figure 4.8 shows the
Figure 5.1: Fraction of Alexa top-100k sites that invoke each given resource hint (x-axis ordered by Alexa ranking, binned into buckets of size 1,000).
Figure 5.1: Fraction of Alexa top-100k sites that invoke each given resource hint (x-axis ordered by Alexa ranking, binned into buckets of size 1,000).
Figure 5.2: DNS Prefetch Usage (bucket size 1,000). relation to the specific second-level domains that are being referenced by resource hints.
Figure 5.2: DNS Prefetch Usage (bucket size 1,000). relation to the specific second-level domains that are being referenced by resource hints.
half of the resources. Recall that Prefetch states that websites should fetch content for
half of the resources. Recall that Prefetch states that websites should fetch content for
Figure 5.7: CDF of File Sizes of Unused Preloaded Links of prerender will be more detrimental than beneficial to load speeds. eavy, which may be a repelling factor for websites in deciding to use it. Incorrect usage
Figure 5.7: CDF of File Sizes of Unused Preloaded Links of prerender will be more detrimental than beneficial to load speeds. eavy, which may be a repelling factor for websites in deciding to use it. Incorrect usage
Figure 6.4: Example: Alexa graph for tribunnews.com highlighting the root and bad nodes
Figure 6.4: Example: Alexa graph for tribunnews.com highlighting the root and bad nodes
loaded indirectly. Figure 6.5: Alexa graph for tribunnews.com highlighting the nodes and edges in the back- propagation graph
loaded indirectly. Figure 6.5: Alexa graph for tribunnews.com highlighting the nodes and edges in the back- propagation graph
propagation nodes and edges. The back-propagation graph for tribunnews.com is shown
propagation nodes and edges. The back-propagation graph for tribunnews.com is shown
Table 6.1: Graph properties for more popular websites. domains that are 10 hops away, 4 that are 11 hops away and | that is 12 hops away.
Table 6.1: Graph properties for more popular websites. domains that are 10 hops away, 4 that are 11 hops away and | that is 12 hops away.
Table 6.2: Graph properties for Jess popular websites.
Table 6.2: Graph properties for Jess popular websites.
Figure 6.8: Plot of the frequency as a cumulative fraction of the number of domains.
Figure 6.8: Plot of the frequency as a cumulative fraction of the number of domains.
https://tpc.googlesyndication.com which loads 58 and 63 different bad domains
https://tpc.googlesyndication.com which loads 58 and 63 different bad domains
Figure 6.12: Distribution of the hop count as a cumulative fraction of the number of (domain, bad domain) pairs.
Figure 6.12: Distribution of the hop count as a cumulative fraction of the number of (domain, bad domain) pairs.
blocklisted node in the path.
blocklisted node in the path.
Table 6.5: Bad domains classification for More Popular Websites
Table 6.5: Bad domains classification for More Popular Websites
Table 6.7: For different threshold on Scalar trust metric, the percentage of back- Num. of times the domain loads a bad domain ar ast tas = Total num. times the domain 1s loaded by all Alexa websites that N5 is comparatively less harmful compared to N6. Thus, we define the trust metric as:
Table 6.7: For different threshold on Scalar trust metric, the percentage of back- Num. of times the domain loads a bad domain ar ast tas = Total num. times the domain 1s loaded by all Alexa websites that N5 is comparatively less harmful compared to N6. Thus, we define the trust metric as:
Table 6.8: For different threshold on Scalar trust metric, the percentage of back-
Table 6.8: For different threshold on Scalar trust metric, the percentage of back-
domains leads to more bad domains being prevented. of using scalar trust metric, we can see that avoiding the use of fewer back-propagation
domains leads to more bad domains being prevented. of using scalar trust metric, we can see that avoiding the use of fewer back-propagation
There are several heuristic methods available to solve an integer programming prob- sponds to a Sparse Binary Integer Linear Programming Problem which is NP-complete. lem, but due to the size of the matrices, the available solutions are not suitable. Another
There are several heuristic methods available to solve an integer programming prob- sponds to a Sparse Binary Integer Linear Programming Problem which is NP-complete. lem, but due to the size of the matrices, the available solutions are not suitable. Another
in the Peter Lowe’s blocklist. propagation nodes. Trivially, we only use those domains that are not currently in present
in the Peter Lowe’s blocklist. propagation nodes. Trivially, we only use those domains that are not currently in present
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