Group 11's repository

challenges/Collaboration README.md

@@ -0,0 +1,18 @@
+
+
+This is collaboative work repository of group 11:
+
+Nada Saad 
+
+Fatima Malik 
+
+Kefah Albashityalshaer 
+
+Pierre Kenley MERVIL 
+
+Pyae Linn 
+
+Said Ibrahim
+
+Anna Shumylina
+

challenges/challenge1.py

@@ -26,3 +26,26 @@
 Interpret what the final expression means in the context of allowing or blocking a login attempt.
 
 """
+
+A=bool()
+B=bool()
+
+def simplify_expression(A, B):
+    # Original expression: ¬(A ∧ (B ∨ ¬B))
+    # Step 1: Simplify (B ∨ ¬B) to True
+    inner_expression = True  # Since B ∨ ¬B is always True
+    # Step 2: Simplify A ∧ True to A
+    intermediate_expression = A and inner_expression  # A ∧ True = A
+    # Step 3: Apply the negation
+    final_expression = not intermediate_expression  # ¬A
+    return final_expression
+
+# Example usage:
+A = True  # User has correct credentials
+B = True  # Login attempt is from a trusted device
+
+result = simplify_expression(A, B)
+
+if result:
+    print ('Login incorrect. Please enter valid login')
+else: print ('Login correct.')

challenges/challenge2.py

@@ -29,3 +29,33 @@
 # -*- coding: utf-8 -*-
 
 """
+finance_access = {"E0435", "E1021", "E3098", "E7642", "E8873", "E6590"}
+
+tech_access = {"E7642", "E8873", "E6590", "E9812", "E4520"}
+
+admin={"E0001"}
+
+new_employee={"E9999"}
+
+#Who has access to at least one type of data?
+Access_One_type=finance_access.union(tech_access).union(admin)
+
+#Who has access to both financial and technical data?
+Access_both_types=finance_access.intersection(tech_access).union(admin)
+
+#Who has exclusive access to only one type of data?
+Access_one_type_only=finance_access.symmetric_difference(tech_access)
+print (Access_one_type_only)
+
+#Which employees currently lack access (but exist in the system)?
+print ("New employee has no access!", new_employee)
+
+#Are there unnecessary overlaps in access that could pose a security risk?
+print("Access to both types is an unnecessary intersection.", Access_both_types) 
+
+#What changes would you recommend to enhance security and minimize excessive access?
+print("Security Recommendations: Restrict access according to the roles and responsibilities")
+
+
+
+

challenges/challenge3.py

@@ -20,3 +20,43 @@
 Are there risks? Indicate employees who might be exposed to unnecessary data.
 Your output should visually highlight these relationships without explicitly listing them in a simple table or list. Think beyond just printing data—use a format that helps detect patterns at a glance.
 """
+"""
+import matplotlib.pyplot as plt 
+from matplotlib_venn import venn2
+
+finance_access = {"E0435", "E1021", "E3098", "E7642", "E8873", "E6590"}
+
+tech_access = {"E7642", "E8873", "E6590", "E9812", "E4520"}
+
+admin={"E0001"}
+
+new_employee={"E9999"}
+
+venn_values = (finance_access, tech_access, admin, new_employee)
+venn_labels = ('Finance', 'Tech', 'Admin', 'New employee')
+
+venn=venn2(subsets=venn_values, set_labels=venn_labels)
+plt.show()
+
+"""
+
+from matplotlib_venn import venn2
+import matplotlib.pyplot as plt
+
+finance_access = {"E0435", "E1021", "E3098", "E7642", "E8873", "E6590"}
+tech_access = {"E7642", "E8873", "E6590", "E9812", "E4520"}
+admin = {"E0001"}
+new_employee = {"E9999"}
+
+#Venn diagram
+venn2(subsets=(len(finance_access - tech_access),
+               len(tech_access - finance_access),
+               len(finance_access.intersection(tech_access))),
+      set_labels=("Finance Access", "Tech Access"))
+
+# For adding title and colors
+plt.title("Employee Access Control Visualization")
+plt.annotate("Admin: Full Access", xy=(-0.6, -0.5))
+plt.annotate("New Employee: No Access", xy=(-0.6, -0.6))
+plt.show()
+