In a virtual environment system a computer generates sensory impressions that are delivered to the human senses. The type and the quality of these impressions determine the level of immersion and the feeling of presence in VR. Ideally the high-resolution, high-quality and consistent over all the displays, information should be presented to all of the user’s senses. Moreover, the environment itself should react realistically to the user’s actions. The practice, however, is very different from this ideal case. Many applications stimulate only one or a few of the senses, very often with low-quality and unsynchronized information. We can group the VR systems accordingly to the level of immersion they offer to the user.
- Desktop VR – sometimes called Window on World (WoW) systems. This is the simplest type of virtual reality applications. It uses a conventional monitor to display the image (generally monoscopic) of the world. No other sensory output is supported.
- Fish Tank VR – improved version of Desktop VR. These systems support head tracking and therefore improve the feeling of “of being there” thanks to the motion parallax effect. They still use a conventional monitor (very often with LCD shutter glasses for stereoscopic viewing) but generally do not support sensory output.
- Immersive systems – the ultimate version of VR systems. They let the user totally immerse in computer generated world with the help of HMD that supports a stereoscopic view of the scene accordingly to the user’s position and orientation. These systems may be enhanced by audio, haptic and sensory interfaces.
Consider a business traveler who has a laptop configured to automatically update a remote DNS server with its current IP address. If the FQDN that was being updated by the laptop is known, or can be guessed, then anyone with modest computer skills can issue DNS queries on that name at regular intervals and monitor the current IP address.
As the traveler moves from one location to another, the IP address will change and the public DNS record for the FQDN will reflect this. The person monitoring the domain name will be able to observe the precise network locations used whenever the laptop connects to the Internet, as well as an approximate timestamp for when each event took place. Depending on the resources available to the monitor, most notably whether or not they work for law enforcement, they may be able to map that network location to a geographic location, possibly with a high degree of resolution.
The public DNS system is distributed across thousands of servers on the Internet and is used in a wide range of Internet protocols. Dynamic DNS monitoring uses nothing more than basic DNS queries and as such it offers effectively complete anonymity to the person doing the surveillance. Not only that, the target this is unable to detect that they are being observed in this manner. This represents a new form of surveillance that might be used by law enforcement for legitimate purposes or for unethical reasons by co-workers, competitors, or even stalkers, of the target.
Dynamic DNS is used by a large number of users for various reasons. For many of these, with static residential or business computers, monitoring poses no real privacy risk. But for those who travel with their laptop it could pose a serious risk to their personal privacy and business confidentiality. This risk has not been widely recognized thus far.
In stateful page evaluation, the browser history file and additional history stored by SpoofGuard are used to evaluate the referring page. Since it is important to minimize the number of false alarms, SpoofGuard does not issue any warnings for visiting a site that is in the user’s history file. The rationale for this is that if the user is warned the first time, and decides to proceed, the user is assumed to have sufficient reason to trust the site.
Domain check : If the domain of a page closely resembles a standard or previously visited domain, the page may be part of a spoof. Although crude, we currently compare domains by Hamming (edit) distance. For example example.com will raise the domain check if example.com is in the file of commonly spoofed sites or in the user history. Clearly, it is possible to improve our comparison algorithm by studying the way people are fooled; this is a significant direction for future work.
A related issue is that some businesses outsource some of their web operations to contractors with different domain names. This poses an interesting challenge that we believe can be addressed. However, outsourced web activity leads to false alarms in the current version of
Referring page When a user follows a link, the browser maintains a record of the referring page. Since the typical web spoofing attack begins with an email message, a referring page from a web site where the user may have been reading email (such as Hotmail) raises
the level of suspicion. One complication associated with Hotmail, for example, is that Hotmail uses numeric IP addresses instead of symbolic host names. Therefore, when a user clicks on a link in a Hotmail message, the browser provides a numeric IP address to SpoofGuard as the referring page. In this situation, SpoofGuard uses reverse DNS to find the domain name associated with a numeric address, allowing us to identify Hotmail as the referring site.
Image-domain associations The image check described on database associating images such as corporate logos with domains.
The initial static database can be assembled using a web crawler or other tool, or it can be augmented using an individual’s browsing history. An early version of SpoofGuard used a fixed database; the current SpoofGuard implementation uses a hashed image history file.
The identification of applicable laws in the absence of any explicit choice by the parties involved is difficult in relation to any information society service, and cloud computing service models are certainly no exception. In a European context, the provisions of the eCommerce Directive play a central role, as it contains specific rules on applicable law for information society services. However, it is clear that this will be insufficient to address all questions in this domain: the rules established by the Directive obviously apply only in Member States, and in a non-European international context will not be able to solve conflicts of law. In addition, applicability of the law remains linked to the geographical location of the information society service provider, and in a cloud model it may be difficult to identify this entity or its geographical location. Finally, certain issues including contractual consumer protection clauses and intellectual property protection are excluded from the Directive’s scope, meaning that answers to conflicts of law in these domains will have to be sought elsewhere. Thus, it is already very complicated to identify the starting point for the establishment of trust, namely the specific laws that will apply in the absence of a choice by the parties. Globally, voluntary choice of applicable law by the stakeholders in a cloud service model may be the only viable solution to identify applicable law. In practice, the importance of this issue should not be overstated, as the choice of an applicable legal system on a contractual basis has indeed become standard practice in information society service contracts.
We can specify any of the conflict resolution policies enumerated above for rules having the same security level. However, if there are rules belonging to different security levels, the conflict resolution policy must always favor the dominated rule. This is because delaying
a rule at the dominated level because of the execution of a rule at the dominating level may give rise to a timing channel.
In a multilevel secure active database system we can also specify priorities, but the requirement is that no dominating rule must have a higher priority than a dominated rule. Thus, if priorities are specified by ordering the set of rules, then all rules at dominated levels must be ordered before any rule at the dominating level.
If numeric priorities are to be specified, one approach is to make the priority specification have two parts: one for the security level and the other for the number. For rules having different security levels, the dominated rules will get preference over the dominating rules. For rules having the same security level, the number will decide which rule is chosen for execution.
Home Phoneline Networking Alliance (Home PNA) [HPNA] has standardized a technology which allows networking of devices using the existing telephone wiring of the home.
There is no need for a central control unit in the network, but each device is required to have a Home PNA adapter. Those come either in the form of PCI cards or Ethernet to Home PNA adapters, which allow connecting a standard Ethernet device to a Home PNA network, as shown in Figure 1.
Figure 1. Basic home networking with Home PNA
Home PNA Version 2.0 is designed to reach up to 300 meters between any two adapters. If the network has more than two Home PNA adapters, all of the adapters must be within 300 meters of each other. The actual distance may be longer or perhaps shorter depending on the type of wire, noise conditions and topology of the telephone wiring within the home. Theoretical maximum speed of the Home PNA technology is 10 Mbps, which is quite low compared to competing previously mentioned standards.
Video codecs use various compression techniques to fit a video signal into the allotted channel bandwidth. These compression
techniques can affect the resulting quality of the video in different ways. An understanding of encoding principles can help a
content provider determine what content will look best on a mobile device, and highlight some of the expected trade offs when
producing multimedia files.
Quick bandwidth reduction can be achieved by using video compression techniques such as:
- Removing statistical redundancies
- Reducing resolution size (for example, CIF ➔ QCIF)
- Using fewer frames per second (for example, 15 fps ➔ 10 fps)
Further bandwidth reduction can be achieved by leveraging the patterns within the video data and removing redundancies. Image
compression relies on discarding information that is indiscernible to the viewer. Motion compensation provides interpolation
between frames, using less data to represent the change. The goal of a video encoder is to remove redundancies in the video
stream and to encode as little data as possible. To achieve this goal, the encoder samples the video stream in two ways:
- In time intervals from consecutive frames (temporal domain)
- Between adjacent pixels in the same frame (spatial domain)
A video decoder pieces the video stream together by reversing the encoding process. The decoder reconstructs the video stream
by adding together the pixel differences and frame differences to form a complete video.
This is an overly simplified look at compression, but it is useful to remember that a compressed video stream provides the deltas
between previously encoded data, instead of a complete representation of each frame.