app

attack_node_assign(nodes, federation, attack, poisoned_node_percent, poisoned_sample_percent, poisoned_noise_percent)

Identify which nodes will be attacked

Source code in nebula/frontend/app.py

def attack_node_assign(
    nodes,
    federation,
    attack,
    poisoned_node_percent,
    poisoned_sample_percent,
    poisoned_noise_percent,
):
    """Identify which nodes will be attacked"""
    import math
    import random

    attack_matrix = []
    n_nodes = len(nodes)
    if n_nodes == 0:
        return attack_matrix

    nodes_index = []
    # Get the nodes index
    if federation == "DFL":
        nodes_index = list(nodes.keys())
    else:
        for node in nodes:
            if nodes[node]["role"] != "server":
                nodes_index.append(node)

    n_nodes = len(nodes_index)
    # Number of attacked nodes, round up
    num_attacked = int(math.ceil(poisoned_node_percent / 100 * n_nodes))
    if num_attacked > n_nodes:
        num_attacked = n_nodes

    # Get the index of attacked nodes
    attacked_nodes = random.sample(nodes_index, num_attacked)

    # Assign the role of each node
    for node in nodes:
        node_att = "No Attack"
        attack_sample_persent = 0
        poisoned_ratio = 0
        if (node in attacked_nodes) or (nodes[node]["malicious"]):
            node_att = attack
            attack_sample_persent = poisoned_sample_percent / 100
            poisoned_ratio = poisoned_noise_percent / 100
        nodes[node]["attacks"] = node_att
        nodes[node]["poisoned_sample_percent"] = attack_sample_persent
        nodes[node]["poisoned_ratio"] = poisoned_ratio
        attack_matrix.append([node, node_att, attack_sample_persent, poisoned_ratio])
    return nodes, attack_matrix

mobility_assign(nodes, mobile_participants_percent)

Assign mobility to nodes

Source code in nebula/frontend/app.py

def mobility_assign(nodes, mobile_participants_percent):
    """Assign mobility to nodes"""
    import random

    # Number of mobile nodes, round down
    num_mobile = math.floor(mobile_participants_percent / 100 * len(nodes))
    if num_mobile > len(nodes):
        num_mobile = len(nodes)

    # Get the index of mobile nodes
    mobile_nodes = random.sample(list(nodes.keys()), num_mobile)

    # Assign the role of each node
    for node in nodes:
        node_mob = False
        if node in mobile_nodes:
            node_mob = True
        nodes[node]["mobility"] = node_mob
    return nodes