Monshizadeh and Khatri
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Some of the threats listed in Table 11.1 are described here:
● Probing: an attempt to monitor a robot and steal information such as open ports and
IP addresses of robots connected to the network;
● Remote access: this threat tries to access the robot without permission. The access is
made possible by exploiting a vulnerability;
● Man‐in‐the middle: occurs when an attacker gains access to the communication
channel established between robot and LRC, or between two robots. The attacker can
perform unauthorized activities, such as intercepting robot data or modifying communications to change the robot mission;
● IP spoofing: in this attack, an attacker creates IP packets with a false source IP address
to hide his/her identity, to be introduced himself/herself as another robot and steal
the data;
● Spyware: all kinds of software that monitors and steal robot’s information;
● Service injection: the attacker targets a robot service and injects malicious code to
corrupt the service;
● Botnet: a group of connected vulnerable robots in a network, which are remotely
controlled by a master computer (hacker). Like robots, they automatically perform
some functions that are predefined by the botmaster and forward the information
like viruses to target LRCs or robots, which could cause denial of service;
● Malware: refers to all kinds of software codes, i.e. viruses, worms, Trojans. These
attacks are programmed to perform malicious operations on a robot;
● Ransomware: any kind of software that locks a robot and demands some form of payment to make the robot unlock;
● Denial of Service (DoS): an attacker occupies the network resources by flooding it
with consecutive requests and cause denial of services to robots;
● Unavailability of robot or LRC: based on unexpected failure or any attack, robot’s and
LRC’s firmware or configuration could be lost or corrupted and make the robot
unavailable.
11.4.3 Robot Security Platform
As shown in Figure 11.6, the proposed Internet of the robot security platform has two
sections: robot section and mobile network section.
The robot section includes robots and Local Robot Controller (LRC). LRC is a central
node for all robots and responsible for connectivity between robots and the mobile
network. The first level of data monitoring and security analysis is done in LRC and
before data is forwarded to mobile network. The IoT service provider can be either a
mobile network operator or a Mobile Virtual Network Operator (MVNO). The MVNO
carries out advanced analysis of collected data from various LRCs, through data mining
mechanisms in an IoT anomaly detection module. The analyzed data would be used for
intrusion detection in the same or different MVNO. While a robot has been identified as
malicious in an MVNO, a notification will be sent to all MVNOs by an IoT orchestrator
to block the malicious robot and prevent re‐analysis of the malicious robot in future,
since the malicious robot may try to attack the cloud platform using other MVNOs.
Therefore, the distributed security platform reduces the computation processing for a
malicious robot that has been already identified as malicious in another MVNO.
256
Some of the threats listed in Table 11.1 are described here:
● Probing: an attempt to monitor a robot and steal information such as open ports and
IP addresses of robots connected to the network;
● Remote access: this threat tries to access the robot without permission. The access is
made possible by exploiting a vulnerability;
● Man‐in‐the middle: occurs when an attacker gains access to the communication
channel established between robot and LRC, or between two robots. The attacker can
perform unauthorized activities, such as intercepting robot data or modifying communications to change the robot mission;
● IP spoofing: in this attack, an attacker creates IP packets with a false source IP address
to hide his/her identity, to be introduced himself/herself as another robot and steal
the data;
● Spyware: all kinds of software that monitors and steal robot’s information;
● Service injection: the attacker targets a robot service and injects malicious code to
corrupt the service;
● Botnet: a group of connected vulnerable robots in a network, which are remotely
controlled by a master computer (hacker). Like robots, they automatically perform
some functions that are predefined by the botmaster and forward the information
like viruses to target LRCs or robots, which could cause denial of service;
● Malware: refers to all kinds of software codes, i.e. viruses, worms, Trojans. These
attacks are programmed to perform malicious operations on a robot;
● Ransomware: any kind of software that locks a robot and demands some form of payment to make the robot unlock;
● Denial of Service (DoS): an attacker occupies the network resources by flooding it
with consecutive requests and cause denial of services to robots;
● Unavailability of robot or LRC: based on unexpected failure or any attack, robot’s and
LRC’s firmware or configuration could be lost or corrupted and make the robot
unavailable.
11.4.3 Robot Security Platform
As shown in Figure 11.6, the proposed Internet of the robot security platform has two
sections: robot section and mobile network section.
The robot section includes robots and Local Robot Controller (LRC). LRC is a central
node for all robots and responsible for connectivity between robots and the mobile
network. The first level of data monitoring and security analysis is done in LRC and
before data is forwarded to mobile network. The IoT service provider can be either a
mobile network operator or a Mobile Virtual Network Operator (MVNO). The MVNO
carries out advanced analysis of collected data from various LRCs, through data mining
mechanisms in an IoT anomaly detection module. The analyzed data would be used for
intrusion detection in the same or different MVNO. While a robot has been identified as
malicious in an MVNO, a notification will be sent to all MVNOs by an IoT orchestrator
to block the malicious robot and prevent re‐analysis of the malicious robot in future,
since the malicious robot may try to attack the cloud platform using other MVNOs.
Therefore, the distributed security platform reduces the computation processing for a
malicious robot that has been already identified as malicious in another MVNO.