scholarly journals CoLL-IoT: A Collaborative Intruder Detection System for Internet of Things Devices

Electronics ◽  
2021 ◽  
Vol 10 (7) ◽  
pp. 848
Author(s):  
Hani Mohammed Alshahrani
Keyword(s):  
Internet Of Things ◽  
Detection System ◽  
Fog Computing ◽  
Denial Of Service ◽  
Sybil Attack ◽  
Replay Attack ◽  
Denial Of Service Attack ◽  
Intruder Detection ◽  
Service Attack ◽  
Iot Devices

The Internet of Things (IoT) and its applications are becoming popular among many users nowadays, as it makes their life easier. Because of its popularity, attacks that target these devices have increased dramatically, which might cause the entire system to be unavailable. Some of these attacks are denial of service attack, sybil attack, man in the middle attack, and replay attack. Therefore, as the attacks have increased, the detection solutions to detect malware in the IoT have also increased. Most of the current solutions often have very serious limitations, and malware is becoming more apt in taking advantage of them. Therefore, it is important to develop a tool to overcome the existing limitations of current detection systems. This paper presents CoLL-IoT, a CoLLaborative intruder detection system that detects malicious activities in IoT devices. CoLL-IoT consists of the following four main layers: IoT layer, network layer, fog layer, and cloud layer. All of the layers work collaboratively by monitoring and analyzing all of the network traffic generated and received by IoT devices. CoLL-IoT brings the detection system close to the IoT devices by taking the advantage of edge computing and fog computing paradigms. The proposed system was evaluated on the UNSW-NB15 dataset that has more than 175,000 records and achieved an accuracy of up to 98% with low type II error rate of 0.01. The evaluation results showed that CoLL-IoT outperformed the other existing tools, such as Dendron, which was also evaluated on the UNSW-NB15 dataset.

scholarly journals Mathematical model on distributed denial of service attack through Internet of things in a network

2019 ◽  
Vol 8 (1) ◽  
pp. 486-495 ◽  
Author(s):  
Bimal Kumar Mishra ◽  
Ajit Kumar Keshri ◽  
Dheeresh Kumar Mallick ◽  
Binay Kumar Mishra
Keyword(s):  
Mathematical Model ◽  
Internet Of Things ◽  
Equilibrium Points ◽  
Denial Of Service ◽  
Distributed Denial Of Service ◽  
Ddos Attacks ◽  
Denial Of Service Attack ◽  
Different Types ◽  
Service Attack ◽  
Iot Devices

Abstract Internet of Things (IoT) opens up the possibility of agglomerations of different types of devices, Internet and human elements to provide extreme interconnectivity among them towards achieving a completely connected world of things. The mainstream adaptation of IoT technology and its widespread use has also opened up a whole new platform for cyber perpetrators mostly used for distributed denial of service (DDoS) attacks. In this paper, under the influence of internal and external nodes, a two - fold epidemic model is developed where attack on IoT devices is first achieved and then IoT based distributed attack of malicious objects on targeted resources in a network has been established. This model is mainly based on Mirai botnet made of IoT devices which came into the limelight with three major DDoS attacks in 2016. The model is analyzed at equilibrium points to find the conditions for their local and global stability. Impact of external nodes on the over-all model is critically analyzed. Numerical simulations are performed to validate the vitality of the model developed.

scholarly journals SlowITe, a Novel Denial of Service Attack Affecting MQTT

Sensors ◽  
2020 ◽  
Vol 20 (10) ◽  
pp. 2932
Author(s):  
Ivan Vaccari ◽  
Maurizio Aiello ◽  
Enrico Cambiaso
Keyword(s):  
Internet Of Things ◽  
Denial Of Service ◽  
The Internet ◽  
Message Queue ◽  
Plain Text ◽  
Denial Of Service Attack ◽  
Service Attack ◽  
Iot Devices ◽  
The Internet Of Things ◽  
Low Rate

Security of the Internet of Things is a crucial topic, due to the criticality of the networks and the sensitivity of exchanged data. In this paper, we target the Message Queue Telemetry Transport (MQTT) protocol used in IoT environments for communication between IoT devices. We exploit a specific weakness of MQTT which was identified during our research, allowing the client to configure the behavior of the server. In order to validate the possibility to exploit such vulnerability, we propose SlowITe, a novel low-rate denial of service attack aimed to target MQTT through low-rate techniques. We validate SlowITe against real MQTT services, considering both plain text and encrypted communications and comparing the effects of the threat when targeting different daemons. Results show that the attack is successful and it is able to exploit the identified vulnerability to lead a DoS on the victim with limited attack resources.

scholarly journals SlowTT: A Slow Denial of Service against IoT Networks

Information ◽  
2020 ◽  
Vol 11 (9) ◽  
pp. 452
Author(s):  
Ivan Vaccari ◽  
Maurizio Aiello ◽  
Enrico Cambiaso
Keyword(s):  
Internet Of Things ◽  
Denial Of Service ◽  
Computational Power ◽  
Message Queue ◽  
Denial Of Service Attack ◽  
Research Activities ◽  
Cyber Threat ◽  
Service Attack ◽  
Long Time ◽  
Low Rate

The security of Internet of Things environments is a critical and trending topic, due to the nature of the networks and the sensitivity of the exchanged information. In this paper, we investigate the security of the Message Queue Telemetry Transport (MQTT) protocol, widely adopted in IoT infrastructures. We exploit two specific weaknesses of MQTT, identified during our research activities, allowing the client to configure the KeepAlive parameter and MQTT packets to execute an innovative cyber threat against the MQTT broker. In order to validate the exploitation of such vulnerabilities, we propose SlowTT, a novel “Slow” denial of service attack aimed at targeting MQTT through low-rate techniques, characterized by minimum attack bandwidth and computational power requirements. We validate SlowTT against real MQTT services, by considering both plaintext and encrypted communications and by comparing the effects of the attack when targeting different application daemons and protocol versions. Results show that SlowTT is extremely successful, and it can exploit the identified vulnerability to execute a denial of service against the IoT network by keeping the connection alive for a long time.

scholarly journals دراسة استقصائية حول الآليات الآمنة للتحقق من الهوية في تطبيقات إنترنت الأشياء القائمة على الحوسبة الضبابية

2020 ◽  
Vol 9 (1) ◽  
pp. 17-27
Author(s):  
أروى باشنفر أروى باشنفر
Keyword(s):  
Denial Of Service ◽  
Sybil Attack ◽  
Denial Of Service Attack ◽  
Service Attack

زوَّدت الحوسبة الضبابية انترنت الأشياء بعدة مميزات، من أهمها: القابلية للتوسع والمرونة، وذلك عن طريق تقليل ازدحام شبكة الاتصالات وتحسين وقت الاستجابة بين الأجهزة المتصلة والخدمة السحابية. من جهة أخرى، فإن حوسبة الضبابية قد ورثت نقاط ضعف للعديد من الهجمات، بما في ذلك هجمات سايبل (Sybil Attack)، وانتحال الهوية (Impersonating attacks)، وحتى هجمات الحرمان من الخدمة (Denial of Service Attack). ولهذا السبب؛ فإنه من الضروري إضافة خاصية الأمان إلى طبقة الحوسبة الضبابية عن طريق تأمين خاصية التحقق من الهوية، والتي تعتبر خط الدفاع الأول المهم في أي نظام. في هذه الدراسة الاستقصائية، نقوم بمراجعة بعض الآليات الحديثة التي تم تطويرها كآليات آمنة للتحقق من الهوية في الحوسبة الضبابية، وعلى إثر هذه المراجعة نقدم مقارنة بين هذه الأليات بناءً على معايير محددة كالطريقة المتبعة لتعريف المستخدمين، خوارزمية التشفير المستخدمة، ودعم التنقل السلس للأجهزة.

scholarly journals Shield Advanced Mitigation System of Distributed Denial of Service Attack in Integration of Internet of Things and Cloud Computing Environment

2019 ◽  
Vol 9 (2) ◽  
pp. 1300-1306
Keyword(s):  
Cloud Computing ◽  
Internet Of Things ◽  
Denial Of Service ◽  
Cloud Services ◽  
Distributed Denial Of Service ◽  
Ddos Attacks ◽  
Denial Of Service Attack ◽  
Ddos Attack ◽  
Service Attack ◽  
Verification Process

Cloud services among public and business companies have become popular in recent years. For production activities, many companies rely on cloud technology. Distributed Denial of Services (DDoS) attack is an extremely damaging general and critical type of cloud attacks. Several efforts have been made in recent years to identify numerous types of DDoS attacks. This paper discusses the different types of DDoS attacks and their cloud computing consequences. Distributed Denial of Service attack (DDoS) is a malicious attempt to disrupt the normal movement of a targeted server, service or network through influx of internet traffic overwhelming the target or its infrastructure. The use of multiple affected computer systems as a source of attacks makes DDoS attacks effective. Computers and other networked tools, including IoT phones, may be included on exploited machines. A DDoS attack from a high level resembles a traffic jam that is caused by roads that prevents normal travel at their desired destination. So DDoS Attack is a major challenging problem in integrated Cloud and IoT. Hence, this paper proposes Shield Advanced Mitigation System of Distributed Denial of Service Attack in the integration of Internet of Things and Cloud Computing Environment. This secure architecture use two verification process to identify whether user is legitimate or malicious. Dynamic Captcha Testing with Equal Probability test for first verification process, moreover Zigsaw Image Puzzle Test is used for second verification process, and Intrusion Detection Prevention System is used to identify and prevent malicious user, moreover reverse proxy is used to hide server location. These functional components and flow could strengthen security in Client side network to provide cloud services furthermore to overcome distributed denial of service attack in the integration of Internet of Things and Cloud Environment.

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