scholarly journals Towards a Lightweight Intrusion Detection Framework for In-Vehicle Networks

2022 ◽  
Vol 11 (1) ◽  
pp. 6
Author(s):  
Dheeraj Basavaraj ◽  
Shahab Tayeb
Keyword(s):  
Intrusion Detection ◽  
Performance Metrics ◽  
Detection System ◽  
Electronic Control Unit ◽  
Denial Of Service ◽  
Control Unit ◽  
Control Area ◽  
The Internet ◽  
Area Network ◽  
Classification Models

With the emergence of networked devices, from the Internet of Things (IoT) nodes and cellular phones to vehicles connected to the Internet, there has been an ever-growing expansion of attack surfaces in the Internet of Vehicles (IoV). In the past decade, there has been a rapid growth in the automotive industry as network-enabled and electronic devices are now integral parts of vehicular ecosystems. These include the development of automobile technologies, namely, Connected and Autonomous Vehicles (CAV) and electric vehicles. Attacks on IoV may lead to malfunctioning of Electronic Control Unit (ECU), brakes, control steering issues, and door lock issues that can be fatal in CAV. To mitigate these risks, there is need for a lightweight model to identify attacks on vehicular systems. In this article, an efficient model of an Intrusion Detection System (IDS) is developed to detect anomalies in the vehicular system. The dataset used in this study is an In-Vehicle Network (IVN) communication protocol, i.e., Control Area Network (CAN) dataset generated in a real-time environment. The model classifies different types of attacks on vehicles into reconnaissance, Denial of Service (DoS), and fuzzing attacks. Experimentation with performance metrics of accuracy, precision, recall, and F-1 score are compared across a variety of classification models. The results demonstrate that the proposed model outperforms other classification models.

scholarly journals Design Of Intrusion Detection System For Dos Attack In 6lowpan And RPL Based IoT Network

2019 ◽  
Vol 8 (11) ◽  
pp. 3840-3844
Keyword(s):  
Intrusion Detection ◽  
Low Power ◽  
Intrusion Detection System ◽  
Detection System ◽  
Denial Of Service ◽  
Attack Detection ◽  
Area Network ◽  
Dos Attack ◽  
Resource Constrained ◽  
Ipv6 Protocol

Internet of Things (IoT) is a network spread globally and accommodates maximum things under it. All these things are connected globally using IPv6 protocol which satisfies the need of connecting maximum devices by supporting 2^128 addresses. Because of heavy-weight nature of IPv6 protocol, a compressed version of it known as IPv6 Low Power Personal Area Network (6LoWPAN) protocol is used for a resource-constrained network that communicates over low power and lossy links. In IoT, devices are resource-constrained in terms of low battery power, less processing power, less transceiver power, etc. Also these devices are directly connected to insecure internet hence it is very challenging to maintain security in IoT network. In this paper, we have discussed various attacks on 6LoWPAN and RPL network along with countermeasures to reduce the attacks. DoS attack is one of the severe attacks in IoT which has various patterns of execution. Out of various attacks we have designed Intrusion Detection System (IDS) for Denial of Service (DOS) attack detection using Contiki OS and Cooja simulator.

scholarly journals Towards Improved Random Forest based Feature Selection for Intrusion Detection in Smart IOT Environment

2019 ◽  
Vol 8 (11) ◽  
pp. 749-757
Keyword(s):  
Feature Selection ◽  
Random Forest ◽  
Intrusion Detection ◽  
Performance Metrics ◽  
Detection System ◽  
Denial Of Service ◽  
Learning Approaches ◽  
Iot Devices ◽  
Sensitivity Specificity ◽  
Research Challenge

Internet of Things (IoT) is raised as most adaptive technologies for the end users in past few years. Indeed of being popular, security in IoT turned out to be a crucial research challenge and a sensible topic which is discussed very often. Denial of Service (DoS) attack is encountered in IoT sensor networks by perpetrators with numerous compromised nodes to flood certain targeted IoT device and thus resulting in vulnerability or service unavailability. Features that are encountered from the malicious node can be utilized effectually to recognize recurring patterns or attack signature of network based or host based attacks. Henceforth, feature extraction using machine learning approaches for modelling of Intrusion detection system (IDS) have been cast off for identification of threats in IoT devices. In this investigation, Kaggle dataset is measured as benchmark dataset for detecting intrusion is considered initially. These dataset includes 41 essential attributes for intrusion identification. Next, selection of features for classifiers is done with an improved Weighted Random Forest Information extraction (IW-RFI). This proposed WRFI approach evaluates the mutual information amongst the attributes of features and select the optimal features for further computation. This work primarily concentrates on feature selection as effectual feature selection leads to effectual classification. Finally, performance metrics like accuracy, sensitivity, specificity is computed for determining enhanced feature selection. The anticipated model is simulated in MATLAB environment, which outperforms than the existing approaches. This model shows better trade off in contrary to prevailing approaches in terms of accurate detection of threats in IoT devices and offers better transmission over those networks.

scholarly journals Implementasi Intrusion Detection System (IDS) Pada Keamanan PC Server Terhadap Serangan Flooding Data

2018 ◽  
Vol 28 (1) ◽  
Author(s):  
Achmad Hambali Hambali ◽  
Siti Nurmiati
Keyword(s):  
Intrusion Detection ◽  
Intrusion Detection System ◽  
Local Area Network ◽  
Detection System ◽  
Denial Of Service ◽  
Local Area ◽  
Area Network

Flooding Data adalah jenis serangan Denial of Service (DOS) di mana data flooding menyerangkomputer atau server di jaringan lokal atau internet dengan menghabiskan sumber daya yang dimiliki olehkomputer hingga komputer tidak dapat menjalankan fungsinya dengan baik sehingga tidak secara langsungmencegah pengguna lain dari mendapatkan akses ke layanan dari komputer yang diserang. Penelitian ini untukmenganalisis indikasi serangan dan menjaga keamanan sistem dari ancaman banjir data. Untuk itu kitamembutuhkan alat deteksi yang dapat mengenali keberadaan serangan flooding data dengan mengetuk paketdata dan kemudian membandingkannya dengan aturan basis data IDS (berisi paket serangan tanda tangan).Mesin IDS akan membaca peringatan dari IDS (seperti jenis serangan dan penyadap alamat IP) untukmeminimalkan data serangan flooding terhadap LAN (Local Area Network) dan server. Metode pengujian dataserangan banjir dengan menggunakan metode pengujian penetrasi. Tiga sampel uji adalah serangan floodingdata terhadap ICMP, UDP dan protokol TCP menggunakan aplikasi Flooding data. Hasil yang diperolehketika menguji data serangan flooding di mana sensor sensor deteksi dapat mendeteksi semua serangan dansemua sampel serangan dapat dicegah atau disaring menggunakan sistem keamanan jaringan berbasisfirewall.

scholarly journals A Novel Message-Preserving Scheme with Format-Preserving Encryption for Connected Cars in Multi-Access Edge Computing

Sensors ◽  
2019 ◽  
Vol 19 (18) ◽  
pp. 3869 ◽  
Author(s):  
Insu Oh ◽  
Taeeun Kim ◽  
Kangbin Yim ◽  
Sun-Young Lee
Keyword(s):  
Electronic Control Unit ◽  
Denial Of Service ◽  
Control Unit ◽  
Real Data ◽  
Edge Computing ◽  
Denial Of Service Attacks ◽  
Area Network ◽  
Message Structure ◽  
Connected Cars ◽  
Multi Access

In connected cars with various electronic control unit (ECU) modules, Ethernet is used to communicate data received by the sensor in real time, but it is partially used alongside a controller area network (CAN) due to the cost. There are security threats in the CAN, such as replay attacks and denial-of-service attacks, which can disrupt the driver or cause serious damage, such as a car accident through malicious manipulation. Although several secure protocols for protecting CAN messages have been proposed, they carry limitations, such as combining additional elements for security or modifying CAN messages with a limited length. Therefore, in this paper, we propose a method for encrypting the data frame, including real data in the CAN message structure, using format-preserving encryption (FPE), which ensures that the plaintext and ciphertext have the same format and length. In this way, block ciphers such as AES-128 must be divided into two or three blocks, but FPE can be processed simultaneously by encrypting them according to the CAN message format, thus providing better security against denial-of-service attacks. Based on the 150 ms CAN message, a normal message was received from a malicious message injection of 180 ms or more for AES-128 and a malicious message injection of 100 ms or more for FPE. Finally, based on the proposed scheme, a CAN transmission environment is constructed for analyzing the encryption/decryption rate and the process of transmitting and processing the encrypted message for connected cars in multi-access edge computing (MEC). This scheme is compared with other algorithms to verify that it can be used in a real environment.

A Novel Intrusion Detection System for Internet of Things Network Security

2021 ◽  
Vol 14 (3) ◽  
pp. 20-37
Author(s):  
Arun Kumar Bediya ◽  
Rajendra Kumar
Keyword(s):  
Internet Of Things ◽  
Intrusion Detection ◽  
Assisted Living ◽  
Intrusion Detection System ◽  
Detection System ◽  
Smart Cities ◽  
Denial Of Service ◽  
The Internet ◽  
Smart Vehicles ◽  
The Internet Of Things

Internet of things (IoT) comprises a developing ecosystem of responsive and interconnected devices, sensors, networks, and software. The internet of things keeps on extending with the number of its different equipment segments for smart cities, healthcare, smart homes, assisted living, smart vehicles, transportation, framework, and many more are the areas where the internet of things benefits human lives. IoT networks are meant to be monitored on real-time events, and if these devices get attacked, it can have an unfavorable effect on the system. This paper discussed many possible attacks at IoT networks and distributed denial of service (DDoS) attack is one of the most dangerous among them. Blockchain technology can be utilized to develop a framework to protect IoT systems; blockchain is a new technology used for cryptocurrency transactions. This paper proposed BIoTIDS an intrusion detection system for the IoT network using blockchain. BIoTIDS is able to detect an intruder in the IoT network and also able to identify DDoS attacks in IoT networks.

scholarly journals An Intrusion Detection System for Smart Grid Neighborhood Area Network

2021 ◽  
Author(s):  
Nasim Beigi Mohammadi
Keyword(s):  
Intrusion Detection ◽  
Smart Grid ◽  
Intrusion Detection System ◽  
Detection System ◽  
Area Network ◽  
Wormhole Attack ◽  
Detection Systems ◽  
Wireless Mesh ◽  
First Time ◽  
Neighborhood Area Network

Smart grid is expected to improve the efficiency, reliability and economics of current energy systems. Using two-way flow of electricity and information, smart grid builds an automated, highly distributed energy delivery network. In this thesis, we present the requirements for intrusion detection systems in smart grid, neighborhood area network (NAN) in particular. We propose an intrusion detection system (IDS) that considers the constraints and requirements of the NAN. It captures the communication and computation overhead constraints as well as the lack of a central point to install the IDS. The IDS is distributed on some nodes which are powerful in terms of memory, computation and the degree of connectivity. Our IDS uses an analytical approach for detecting Wormhole attack. We simulate wireless mesh NANs in OPNET Modeler and for the first time, we integrate our analytical model in Maple from MapleSoft with our OPNET simulation model.

Sign in / Sign up

Export Citation Format

Share Document