CIoTAS protocol: CloudIoT available services protocol through autonomic computing against distributed denial of services attacks

Maati, Bouchera; Saïdouni, Djamel Eddine

doi:10.1007/s12652-020-02556-0

Cited by 12 publications

(6 citation statements)

References 46 publications

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“…All the other previous works tackle simpler search problems by only focusing on a single mitigation class (Marsa-Maestre et al [21]), a one-to-one mapping from attack action classes to mitigation action classes (Sandor et al [28]) or a one-to-many mapping from the former to the latter (Lysenko et al [19], Huertas-Celdran et al [5], [20]). While Gonzales-Granadillo et al [12], Kanoun et al [16], Javornik et, al.…”

Section: Related Workmentioning

confidence: 99%

Intelligent Decision Support for Cybersecurity Incident Response Teams: Autonomic Architecture and Mitigation Search

Correa

Robin

Mazo

et al. 2022

Lecture Notes in Computer Science

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Critical infrastructures must be able to mitigate, at runtime, suspected ongoing cyberattacks that have eluded preventive security measures. To tackle this issue, we first propose an autonomic computing architecture for a Cyber-Security Incident Response Team Intelligent Decision Support System (CSIRT-IDSS) with a precise set of technologies for each of its components. We then zoom in on the component responsible for proposing to the CSIRT, automatically ranked sets of runtime actions to mitigate suspected ongoing cyber-attacks. We formalize its task as a Constraint Optimization Problem (COP). We then propose to implement it by a Constraint Object-Oriented Logic Program (COOLP) deployed as a containerized web service through the integration of three orthogonal extensions of Logic Programming (LP): Web Service Oriented LP (WSOLP) [34] Constraint LP (CLP) [10] and Object-Oriented LP (OOLP) [23]. This integration supports seamlessly reusing platform and task independent cybersecurity ontological knowledge to dynamically build a mitigation action search COP that is customized to an input suspected cyberattack action set. This customization then allows the COP, to be solved by a generic CLP engine efficiently enough to propose mitigation actions to the CSIRT team while they can still be effective. To validate this approach, we implemented a prototype called CARMAS (Cyber Attack Runtime Mitigation Action Search) and ran scalability tests on simulated attacks with various COP construction strategies.

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Section: Related Workmentioning

confidence: 99%

Intelligent Decision Support for Cybersecurity Incident Response Teams: Autonomic Architecture and Mitigation Search

Correa

Robin

Mazo

et al. 2022

Lecture Notes in Computer Science

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“…As a result of these assessments, we've structured the following categories or branches based on the above-mentioned identified weak areas in our growing architecture. They are organized into six groups: Malicious Applications, Misconfigurations, Data Alterations, Denial of Service (DoS) attacks and Distributed Denial of Services (DDoS) attacks, Data Outflow and Access Problems [14].…”

Section: Perspective Of Security Behavior and Lapsesmentioning

confidence: 99%

An Design of Software Defined Networks and Possibilities of Network Attacks

Haldorai¹,

Anandakumar²

2022

JCNS

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This article focusses on a rapidly evolving networking architecture known as Software Defined Networking (SDN) and the possibilities of hazards in the network. This architecture introduces decoupled infrastructure, which establishes customization in the networking system hence making it easy to manage, troubleshoot and configure. This paper focusses on the different aspects of the architecture leaving it an intermediate working in between scholarly application, adding on the elements such as security lapses, security behaviors, general security, programmability and design. In this paper, different points of weakness of the architecture have been evaluates, including the attack vector in every plane. This paper ends with a presentation for futuristic studies on the implications of attacks and potential solutions.

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“…In this step, Clients may need to come back to the previous step, if an empty list is returned, that is, they must change their combinations of functional and non-functional requirements. Otherwise (a non empty list is returned), the non-functional requirements (such as price, response time and reliability) are used to select the most adequate service [2]- [4]. The last step is the invocation of the selected service.…”

Section: Introductionmentioning

confidence: 99%

“…Consequently, the process of service requesting has to be monitored by service managers to detect any unexpected problem and apply corrective strategies when necessary. Many related works [2]- [12] emphasize the importance of monitoring service requests and their QoS. In general, the approaches proposed [13]- [15] offer a high level of abstraction to monitor service and do not consider the granularity of service requests.…”

Section: Introductionmentioning

confidence: 99%

Service request monitoring using Petri nets and model at runtime

Bouhamed

Kamel

D́ıaz

et al. 2022

Preprint

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The service computing paradigm has been widely adopted in various domains, such as in Web applications, Cloud computing and Internet of Things (IoT). Service providers offer services to their clients depending on their functional and non-functional requirements. Generally, the process of using a service consists of three steps discovery, selection, and invocation. This process is subject to many variables. For instance, no service with the required properties was found implying a requirement update, or just the invocation does not work. Therefore, the service monitoring is a necessary feature to be included by service providers. In this paper, we propose a model at-runtime approach to monitor this three-steps-process. We specify the proposed model using the Petri net formalism and the Flexible framework. Our approach allows service managers to monitor the three steps, change requirements when no service can satisfy the current requirements, and select other services when invocations fail. The monitoring system notifies service managers about the request state, the requirement changes required, and the invocation failures based on the Petri net marking. In addition, Python expressions can be used at runtime. Finally, a case study illustrates the approach by the implementation of a compression service.

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CIoTAS protocol: CloudIoT available services protocol through autonomic computing against distributed denial of services attacks

Cited by 12 publications

References 46 publications

Intelligent Decision Support for Cybersecurity Incident Response Teams: Autonomic Architecture and Mitigation Search

Intelligent Decision Support for Cybersecurity Incident Response Teams: Autonomic Architecture and Mitigation Search

An Design of Software Defined Networks and Possibilities of Network Attacks

Service request monitoring using Petri nets and model at runtime

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