Answer:
The answer is by using a covert channel like shared memory objects such as files, directories,messages, etc since both the user and the sender of the document are on same network of the company.
Explanation:
The Bell LaPadula MultiLevel Security model was a security policy developed by Bell and LaPadula in 1973 in response to a security issue raised by the US Air Force regarding file-sharing mainframe computers . Actually, many people with networked systems have realized by early 1970s that the protection purportedly offered by many commercial operating systems was poor, and wa not getting better any time soon. This was observed when it was noticed that as one operating system error was fixed, some other vulnerability would be discovered. There was also the constant worry that various unskilled users would discover loopholes in the operating system during usage and use them to their own advantage.
Information release may take place via shared memory objects such as files, directories, messages, and so on. Thus, a Trojan Horse acting on behalf of a user could release user-private information using legitimate operating system requests. Although developers can build various mechanisms within an operating system to restrict the activity of programs (and Trojan Horses) operating on behalf of a user , there is no general way, short of implementing nondiscretionary policy models, to restrict the activity of such programs. Thus, given that discretionary models cannot prevent the release of sensitive information through legitimate program activity, it is not meaningful to consider how these programs might release information illicitly by using covert channels.
For example, for someone with higher integrity level (SECRET) to send an accounts payable application to a user, if the untrusted accounts payable application contains a Trojan Horse, the Trojan Horse program could send a (legal) message to the said user process running at a lower integrity level (CONFIDENTIAL), thereby initiating the use of a covert channel. In this covert channel, the Trojan Horse is the receiver of (illegal) lower integrity-level input and the user process is the sender of this input.
Answer: sales promotion
Explanation:
Sales promotion are special incentives or excitement-building programs that encourage consumers to purchase a particular product, often used in conjunction with advertising or personal selling programs.
Answer:
The answer is "Departmental interdependence".
Explanation:
In the given question some information is missing, that is an option, which can be described s follows:
A. Work independently across organizations.
B. Departmental interdependence.
C. As an individually small department or as a team.
D. Each organization functions as a separate business entity.
There are separate positions in each organization, but the departments can not actually interact with each other, in the hierarchical paradigm of interdependence and can not rely explicitly on each other, each division presents the same ultimate problem, and other choices were wrong, that is described as follows:
- In option A, It is wrong because in the organization there are some protocol which will be followed by all.
- Option C and Option D both are wrong because each organization's function is not separated by the business entity, and it is not small.
QR codes make up the basic structure of a relational database with columns containing field data and rows containing record information.
Answer:
accounting system
Explanation:
The most common response variable modeled for cropping systems is yield, whether of grain, tuber, or forage biomass yield. This yield is harvested at a single point in time for determinate annual crops, while indeterminate crops and grasslands may be harvested multiple times. Although statistical models may be useful for predicting these biological yields in response to some combination of weather conditions, nutrient levels, irrigation amounts, etc. (e.g., Schlenker and Lobell, 2010, Lobell et al., 2011), they do not predict responses to nonlinearities and threshold effects outside the range of conditions in data used to develop them.
In contrast, dynamic cropping and grassland system models may simulate these biological yields and other responses important to analysts, such as crop water use, nitrogen uptake, nitrate leaching, soil erosion, soil carbon, greenhouse gas emissions, and residual soil nutrients. Dynamic models can also be used to estimate responses in places and for time periods and conditions for which there are no prior experiments. They can be used to simulate experiments and estimate responses that allow users to evaluate economic and environmental tradeoffs among alternative systems. Simulation experiments can predict responses to various climate and soil conditions, genetics, and management factors that are represented in the model. “Hybrid” agricultural system models that combine dynamic crop simulations with appropriate economic models can simulate policy-relevant “treatment effects” in an experimental design of climate impact and adaptation (Antle and Stockle, 2015).
