DoS Attack Detection and Path Collision Localization in NoC-Based MPSoC Architectures

Abstract

Denial of Service (DoS) attacks are an increasing threat for Multiprocessor System-on-Chip (MPSoC) architectures. By exploiting the shared resources on the chip, an attacker is able to prevent completion or degrade the performance of a task. This is extremely dangerous for MPSoCs used in critical applications. The Network-on-Chip (NoC), as a central MPSoC infrastructure, is exposed to this attack. In order to maintain communication availability, NoCs should be enhanced with an effective and precise attack detection mechanism that allows the triggering of effective attack mitigation mechanisms. Previous research works demonstrate DoS attacks on NoCs and propose detection methods being implemented in NoC routers. These countermeasures typically led to a significantly increased router complexity and to a high degradation of the MPSoC’s performance. To this end, we present two contributions. First, we provide an analysis of information that helps to narrow down the location of the attacker in the MPSoC, achieving up to a 69% search space reduction for locating the attacker. Second, we propose a low cost mechanism for detecting the location and direction of the interference, by enhancing the communication packet structure and placing communication degradation monitors in the NoC routers. Our experiments show that our NoC router architecture detects single-source DoS attacks and determines, with high precision, the location and direction of the collision, while incurring a low area and power overhead.

Evaluation Approach for Efficient Countermeasure Techniques Against Denial-of-Service Attack on MPSoC-Based IoT Using Multi-Criteria Decision-Making

“…As we mentioned, the CRITIC approach has six steps to be applied to compute the DM criteria weights. The obtained weights after applying Equation (11) to normalize the DM into the interval of (0 to 1) then using Equation (12) to determine the intensity of the contrast using the standard deviation of normalized criterion values. Moreover, Equation ( 13) was utilized after obtaining a symmetric matrix to express the criteria's correlation coefficient.…”

“…This section categorizes the DoS attacks in the context of MPSoC-based IoT according to the threat motel. The threat model is a methodology based on pre-identified steps implemented by a system attacker [39]. In general, DoS attacks almost shares the same characteristics regarding threat models in the context of MPSoCs-based IoT except for a few improvements by attackers or system designers in terms of improving their DoS attacks countermeasure techniques against proposed DoS strategies (e.g., DoS and DDoS) attacks.…”

A Survey of Software-Defined Networks-on-Chip: Motivations, Challenges and Opportunities

“…However, the downloaded software may be malicious and modify the system operation, retrieve secret information, or disrupt their services. Since the NoC is a shared medium is the preferred center of hackers’ attacks, it will affect computation and communication services [ 33 ]. In the IoT context, NoC-based systems integrate cryptographic hardware core for confidentiality and authentication security services.…”

Detection and Classification of Malicious Flows in Software-Defined Networks Using Data Mining Techniques

“…Security vulnerabilities, especially in the IoT context, arise due to exposure of the MCSoC infrastructure to DoS attacks by malicious users. An example of a low-cost mechanism for detecting the location of the attacker in the MCSoC and direction of the collision is presented by Chaves et al [ 43 ].…”