Answer: a replay attack, a replay attack is used so that the attacker can go sniff out the hash, and get whatever they are trying to get, then once it goes to the attacker it will go back to the original connection after replaying the hash
Answer: Sounds like you are talking about “Distributed memory systems” which use multiple computers to solve a common problem, with computation distributed among the connected computers (nodes) and using message-passing to communicate between the nodes.
Answer:
#here is code in python.
#read number of shares
num_share = int(input("Enter number of shares:"))
#read purchase price
buy_p = float(input("Enter purchase price:"))
#read sell price
sell_p = float(input("Enter sale price:"))
#total buying cost
buy_cost=buy_p*1.03*num_share
#total selling cost
sell_cost=sell_p*0.97*num_share
#if net profit
if(sell_cost>buy_cost):
print("After the transaction, you made " +str(sell_cost-buy_cost)+ " dollars.")
#if net loss
else:
print("After the transaction, you lost " +str(buy_cost-sell_cost)+ " dollars.")
Explanation:
Read the total number of shares from user.Then read buying price of a share and selling price of a share.Then calculate total buying cost including commission.Calculate total selling cost excluding the commission.If total buying cost is greater than total selling cost the print the profit else print the loss in the transaction.
Output:
Enter number of shares:10
Enter purchase price:10
Enter sale price:10
After the transaction, you lost 6.0 dollars.
Solution:
The process of transaction can guarantee the reliability of business applications. Locking resources is widely used in distributed transaction management (e.g; two phase commit, 2PC) to keep the system consistent. The locking mechanism, however, potentially results in various deadlocks. In service oriented architecture, the deadlock problem becomes even worse because multiple transactions try to lock shared resources in the unexpectable way due to the more randomicity of transaction requests, which has not been solved by existing research results. In this paper, we investigate how to prevent local deadlocks, caused by the resource competition among multiple sub-transactions of a gl obal transaction, and global deadlocks from the competition among different global transactions. We propose a replication based approach to avoid the local deadlocks, and a timestamp based approach to significantly mitigate the global deadlocks. A general algorithm is designed for both local and global deadlock prevention. The experimental results demonstrate the effectiveness and efficiency of our deadlock prevention approach. Further, it is also proved that our approach provides higher system performance than traditional resource allocation schemes.
This is the required answer.
The item that you would most likely to keep in a database is a Payroll record. Payroll records are numbers and inputs/outputs of employees of a certain company. Numbers are easier to manipulate and easier to manage than statements, letters and addresses that are basically letters.
