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aleksandrvk [35]
1 year ago
7

owever, sitting in a corner of the store, a hacker had just set up an open "rogue" wireless hotspot posing as the coffee shop’s

wireless network. when
Computers and Technology
1 answer:
Ivenika [448]1 year ago
6 0

However, sitting in a corner of the store, a hacker had just placed up an open “rogue” wireless hotspot posing as the coffee shop’s wireless network. When Sarah logged onto her bank’s website, the hacker hijacked her session and gained access to her bank accounts. Another term for rogue wireless hotspots exists as “evil twin” hotspots.

<h3>What is meant by wireless network?</h3>

A computer network is referred to as a wireless network if radio frequency (RF) links are used to connect network nodes. A common solution for households, companies, and telecommunications networks is wireless networking. Wi-Fi is a wireless networking technology that enables printers and video cameras to connect to the Internet as well as computers (laptops and desktops), mobile devices (smart phones, wearables, etc.), and other devices.

Increased Mobility: Wireless networks give mobile users access to real-time data, enabling them to move freely across the premises of your firm without losing network connectivity. This improves collaboration and production across the entire organisation, which is not achievable with traditional networks.

Hence, However, sitting in a corner of the store, a hacker had just placed up an open “rogue” wireless hotspot posing as the coffee shop’s wireless network. When Sarah logged onto her bank’s website, the hacker hijacked her session and gained access to her bank accounts. Another term for rogue wireless hotspots exists as “evil twin” hotspots.

To learn more about wireless network refer to:

brainly.com/question/26956118

#SPJ4

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Alex Ar [27]

Answer:

Explanation:

Problem statement:

to simulate a binary search algorithm on an array of random values.

Binary Search: Search a sorted array by repeatedly dividing the search interval in half. Begin with an interval covering the whole array. If the value of the search key is less than the item in the middle of the interval, narrow the interval to the lower half. Otherwise narrow it to the upper half. Repeatedly check until the value is found or the interval is empty.

Input/output description

Input:

Size of array: 4

Enter array:10  20 30 40

Enter element to be searched:40

The Output will look like this:

Element is present at index 3

Algorithm and Flowchart:

We basically ignore half of the elements just after one comparison.

Compare x with the middle element.

If x matches with middle element, we return the mid index.

Else If x is greater than the mid element, then x can only lie in right half subarray after the mid element. So we recur for right half.

Else (x is smaller) recur for the left half.

The Flowchart can be seen in the first attached image below:

Program listing:

// C++ program to implement recursive Binary Search

#include <bits/stdc++.h>

using namespace std;

// A recursive binary search function. It returns

// location of x in given array arr[l..r] is present,

// otherwise -1

int binarySearch(int arr[], int l, int r, int x)

{

   if (r >= l) {

       int mid = l + (r - l) / 2;

       // If the element is present at the middle

       // itself

       if (arr[mid] == x)

           return mid;

       // If element is smaller than mid, then

       // it can only be present in left subarray

       if (arr[mid] > x)

           return binarySearch(arr, l, mid - 1, x);

       // Else the element can only be present

       // in right subarray

       return binarySearch(arr, mid + 1, r, x);

   }

   // We reach here when element is not

   // present in array

   return -1;

}

int main(void)

{ int n,x;

cout<<"Size of array:\n";

cin >> n;

int arr[n];

cout<<"Enter array:\n";

for (int i = 0; i < n; ++i)

{ cin >> arr[i]; }

cout<<"Enter element to be searched:\n";

cin>>x;

int result = binarySearch(arr, 0, n - 1, x);

   (result == -1) ? cout << "Element is not present in array"

                  : cout << "Element is present at index " << result;

   return 0;

}

The Sample test run of the program can be seen in the second attached image below.

Time(sec) :

0

Memory(MB) :

3.3752604177856

The Output:

Size of array:4

Enter array:10  20 30 40

Enter element to be searched:40

Element is present at index 3

Conclusions:

Time Complexity:

The time complexity of Binary Search can be written as

T(n) = T(n/2) + c  

The above recurrence can be solved either using Recurrence T ree method or Master method. It falls in case II of Master Method and solution of the recurrence is Theta(Logn).

Auxiliary Space: O(1) in case of iterative implementation. In case of recursive implementation, O(Logn) recursion call stack space.

8 0
3 years ago
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