Analysis of Key Generation Methods for Enable Secured Communication in the IoTs System

Zero conf protocols date from 1999. They provide plug and play mechanisms to set up networks without having to conFigure DNS or DHCP servers. Almost every device (PCs, printers, scanners, etc.) nowadays “speaks” one of these protocols, sometimes without its owner being even aware of it. The booming IoT ecosystem, in particular, relies heavily on them. Unfortunately, these protocols offer a number of different ways to run, so called, man in the middle attacks (MITM). Some previous publications have mentioned and have taken advantage of one or another of these design flaws. In this paper, we provide a deep dive into the various issues at hand and show the extent of the problem. We consider that the growing reliance of networks on these protocols represent an underestimated and ill covered threat. We have run a number of experiments (300) to test various implementations and discuss our results. We also propose means to detect these attacks thanks to Zeek (aka Bro). We make the attack code as well as the Zeek scripts available to the research community in a format that makes replication of our results possible by researchers while not easy to use by script kiddies.

Cyber security of distribution power systems is of an increasing and pressing importance due to the fast modernisation of current systems. Cyber attacks on distribution power systems may aim to operate the system inefficiently, steal private smart meter data or cause intentional false tripping of few or all feeders. In this paper, a Man in The Middle (MiTM) attack on a power factor correction unit is implemented and demonstrated to overload a distribution feeder and cause an intentional false tripping of the entire feeder causing regional blackout. Experimental implementation of the attack is carried out in a laboratory-scale setup using commercial power equipment under different loading conditions to demonstrate the effectiveness of this attack.

In this paper, we propose a new comprehensive realistic cyber security dataset of IoT and IIoT applications, called Edge-IIoTset, which can be used by machine learning-based intrusion detection systems in two different modes, namely, centralized and federated learning. Specifically, the dataset has been generated using a purpose-built IoT/IIoT testbed with a large representative set of devices, sensors, protocols and cloud/edge configurations. The IoT data are generated from various IoT devices (more than 10 types) such as Low-cost digital sensors for sensing temperature and humidity, Ultrasonic sensor, Water level detection sensor, pH Sensor Meter, Soil Moisture sensor, Heart Rate Sensor, Flame Sensor, etc.). Furthermore, we identify and analyze fourteen attacks related to IoT and IIoT connectivity protocols, which are categorized into five threats, including, DoS/DDoS attacks, Information gathering, Man in the middle attacks, Injection attacks, and Malware attacks. In addition, we extract features obtained from different sources, including alerts, system resources, logs, network traffic, and propose new 61 features with high correlations from 1176 found features. After processing and analyzing the proposed realistic cyber security dataset, we provide a primary exploratory data analysis and evaluate the performance of machine learning approaches (i.e., traditional machine learning as well as deep learning) in both centralized and federated learning modes. The Edge-IIoTset dataset can be publicly accessed from <uri xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">http://ieee-dataport.org/8939</uri> .

Information is gathered in smart agriculture from a variety of sources, such as IoT devices with There are many different kinds of sensors, such as weather sensor stations, soil moisture sensors, and sensors used by insects to check crop health. The satellites and drones are used to gather this sensor data. Farm management software tracks plant schedules, pest control methods, and irrigation techniques using the collected valuable data. Any unauthorized person manipulating agricultural data in this way leads to serious issues in the agricultural food supply chain and increases market demand for food. To avoid data manipulation in agricultural information, many strategies are utilized. This work discusses man in the middle attacks, man in the cloud attacks, SQL injection attacks, and cross-site scripting (XSS) attacks. Our strategy was to efficiently test the modified data using cyber integrated agriculture management (CIAM). This strategy focuses on tailored and effective techniques for treating plant soil health, analyzing nutrition levels and pH to guide fertilization, managing water levels, and detecting early signs of pests using image recognition and IoT data. AI-driven tools can detect anomalies and prevent attacks in real time, allowing different farming practices or weather conditions and their impacts on productivity for water usage, fertilizer application, and planting strategies to be detected and avoided with an impressive 98% accuracy, affecting both local and global food security.

In a present-day world there are different types of attacks being launched on computing devices. World is experiencing more and more cyber-attacks and types of attacks are also increasing. For example, an IoT device in a home network can act as a botnet attacking other devices or there could be man in the middle attack. As time goes by more and more devices are being connected within any given network. All these devices will be vulnerable to attacks if any one of the devices is compromised within the network. This complicates Intrusion Detection in any given network. Manual detection and intervention is nearly impossible. Hence it is quintessential to detect different types of attacks with more confidence with less computation complexity and time. A lot of research work has already been done in this area where the attacks have been studied separately. In this paper we focus on detecting intrusions including IoT botnet attacks and other types of network attacks. To achieve this, we build a multiclass classification using supervised learning models along with the dimensionality reduction technique. Numerous studies on ML-based IDS have been using KDD or the upgraded versions of KDD dataset. In this study we used a new dataset, IoT network Intrusion Detection dataset.

ABSTRAK Penelitian ini bertujuan untuk mengevaluasi tingkat keamanan jaringan WLAN yang telah diterapkan di SMK Kristen Getsemani Manado dengan menggunakan metode Penetration Testing. Dalam Analisa keamanan jaringan WLAN dilakukan dengan menggunakan metode Penetration Testing dengan mensimulasikan bentuk serangan terhadap jaringan menggunakan sistem operasi yang biasa digunakan dalam penetration yaitu Kali Linux. Berdasarkan hasil pengujian ditemukan bahwa jaringan WLAN di SMK Kristen Getsemani Manado masih memiliki kerentanan yang dapat dimanfaatkan oleh pihak yang tidak bertanggung jawab.Dua jenis serangan yang berhasil dilakukan dalam penelitian ini adalah Analisis Lalu lintas Jaringan(Traffic Network) dan Man In The Middle Attack. Dari temuan tersebut disimpulkan bahwa Jaringan WLAN di SMK Kristen Getsemani Manado belum memberikan perilndungan yang optimal bagi pengguna yang terhubung, sehingga masih memungkinkan terjadinya gangguan saat mengakses layanan internet. ABSTRACT This study aims to broadcast the level of WLAN network security that has been implemented at SMK Kristen Getsemani Manado using the Penetration Testing method. In the WLAN network security analysis is carried out using the Penetration Testing method with a copy of the form of attack on the network using the operating system commonly used in penetration, namely Kali Linux. Based on the test results, it was found that the WLAN network at SMK Kristen Getsemani Manado still has vulnerabilities that can be exploited by irresponsible parties. Two types of attacks that were successfully carried out in this study were Network Traffic Analysis and Man In The Middle Attack. From these findings, it is concluded that the WLAN Network at SMK Kristen Getsemani Manado has not provided optimal protection for connected users, so it is still possible for disruptions to occur when accessing internet services.

Secure authentication scheme to thwart RT MITM, CR MITM and malicious browser extension based phishing attacks

Evaluating the Impact of Cyberattacks on PLC Performance: A Systematic Implementation and Empirical Investigation

Short Messaging Service (SMS) has removed difference between near and far. Because of guaranteed delivery, people use it on daily basis for connectivity. Not only humans but Information Systems have also utilized it to connect, known as automated messaging. Although automated messaging holds prominent SMS market share but full potential was not reached because of the fact that SMS has no security at all. Any SMS sent or received can be intercepted and manipulated by Man In The Middle (MITM). To resist MITM in next generation smartphones we have proposed a new framework which can be used to secure both human and automated messaging. This automated messaging. This new framework use HTTPS for secure key exchange, ECC, RSA as encryption algorithm and GSM network to send and receive encrypted messages.

This article operationalizes a mathematical root of trust that can be scaled into protection for Internet of Things (IoT) devices. The initial discussion focuses on gated arrays and the generation of 4-way binary keys. Randomization is used in generation of input and sequence keys giving a unique secret key. The probability of successful attack depends on the number of devices and ordinary implementations are well into one in a billion or more. The paper uses the “epoch” concept; a time-dimensioned interval where more blocks are added to the blockchain. The epochs are selected at random and voting, duration, frequency and key roles are also randomized increasing resiliency. The model does not require constant update of IoT storage; only until such time as communication with others is initiated or a request is received. The substantial savings in processing requirements are significant in IoT. A detailed discussion of the management of the blockchain is provided as well as the necessary blocks enabling the approach. The paper includes a sample dialogue using standard TCP/IP communication structures with security protocols and closing remarks aim at extrapolation to cloud and quantum computing. Keywords: blockchain, key management and distribution, internet of things, root of trust, cyber-resiliency

Our modern technologies are increasingly moving towards cryptography to secure the data transmission via a wireless medium. This is because transmission via wireless media is convenient to the modern world, but there still exists a major drawback cryptography in the name of Security. The Vigenere cipher belongs to the family of ciphers in which the cipher text is the ‘sum’ of the plaintext and some keystream. The Vigenere cipher is the encryption technique used in most of the communications, particularly in SMS encryption and decryption. The Vigenere key stream is not random, and therefore the cipher is vulnerable to attack. The plaintext attack and dictionary attack are the most commonly occurring attack leading to man in the middle attack. To overcome these two common attacks in vigenere cipher, we propose a noble approach that uses numbers instead of English alphabets to generate the key.

Over the past decade, the frequency of cyber attacks against power grids has steadily increased, requiring researchers to find and patch vulnerabilities before they can be exploited. Our research introduces the prototype of a man-in-the-middle attack to be implemented on a microgrid emulator of a smart grid. We present a method of violating the integrity and authentication of packets that are using the IEEE Synchrophasor Protocol in a controlled environment, but this same approach could be used on any other protocol that lacks the proper overhead to ensure the integrity and authenticity of packets. In future research, we plan to implement and test the attack on the previously mentioned smart grid testbed in order to assess the attacks feasibility and tangible effects on Wide Area Monitoring and Control applications, as well as propose possible countermeasures. For this paper, we developed a working simulation of our intended attack using the software ModelSim 10.4. The attack will modify network packet data coming from a Schweitzer Engineering Labs (SEL) Phasor Measurement Unit (PMU) hardware sensor, which provides a stream of precise timing values associated with current and voltage values, as these measured values are en route to the Open Phasor Data Concentrator (OpenPDC) application running on a Windows server. Our simulation provides and validates all of the necessary code in order to program a Field Programmable Gate Array and execute our attack on the testbed in future research.

Secure end-to-end information exchange is a constant challenge in electronic communications. Novel security architectures and approaches are proposed constantly, to be followed by announcements of sophisticated attack methods that compromise them, while people suspect others, even more sophisticated attack methods never see the daylight. In the present work we propose a novel method for secure end-to-end communication based on biometric evidence to ensure security and integrity of the information exchanged. The traditional approach for securing the communication between two peers is through the use of secret key encryption combined with a public key approach for exchanging the common secret key to be used by the end peers. The public key part of the communication is based on a trusted authority for providing the public keys, a service provided through a Public Key Infrastructure (PKI). Public key infrastructures are vulnerable to man in the middle attacks, among other approaches that compromise their integrity. There has been a lot of work for providing robust PKI infrastructures, the proposed solutions are fairly demanding on network resources, hence public key solutions are not the security approach of choice in several applications that require light weight solutions. Here we propose an approach for providing secure end-to-end communications in environments where it is possible to have biometric based authentication, exploiting the nature of the application; voice communication being the typical example that we use as our paradigm for describing the method. During the establishment of the communication session, the end-peers exchange a challenge/signature token, the integrity of which is confirmed vocally when the voice communication initiates. The security of the method relies on the inability to mechanically impersonate an individual both because of the biometric user specific attributes of the human voice and video as well as the user customized profile of the exchanged information. The method is appropriate for ensuring the security of an encrypted phone conversation, guaranteeing the integrity of the session key exchanged in the beginning of the conversation. It requires minimal resources from the user handsets and no additional support from the network, so it is inherently scalable and readily deployable as it only needs an appropriately enhanced secure handset. ©2006 IEEE.

Federated Learning (FL) enables cooperative model training across dispersed edge devices while protecting data privacy and providing localized insights without the need for centralized data aggregation. In the Internet of Things (IoT), federated learning enables cooperative model training among dispersed edge devices while protecting data privacy and providing localized insights without the need for centralized data aggregation. Nevertheless, Federated Learning&rsquo;s local model sharing approach makes it susceptible to Man-in-the-Middle (MITM) attacks. In FL, attackers have the ability to manipulate local models. As a result, a global model produced from the altered local models may be inaccurate. In this paper, we suggest a blockchain-based FL architecture to prevent intermediaries from readily altering the FL parameters throughout the transmission process. All of the clients&#039; parameters are combined by a cloud server, which is acting as the federated parameter server. By integrating blockchain technology into the overall architecture, we link all cloud and edge servers. This paper uses a PoC algorithm based on the SHA-256 hashing function in order to validate the data. The results and comparison analysis show that the suggested framework has a low false-positive rate and a high accuracy in detecting MITM attacks in their early stages, with a detection rate ranging from 98 to 100%.

Most of the various sectors in today’s life such as bank, transport, voting, health, electricity, etc., are currently digitalized. In our research paper, we have surveyed the voting system and explored the existing drawbacks of the voting system concerning security and malfunction. The demerits in the existing schemes include less data security, vote modification, man in the middle attack, masquerade attack, denial of service attack, impersonation attack, etc. Such attacks can compromise security and allows attackers to modify the results. To resolve the above-mentioned issues as well as the attacks, this research paper proposes a protocol to overcome security-based issues. In the proposed system, a secure online e-voting system is developed for end-to-end users to avoid misappropriation on the vote during the result publication in India or any other country. The proposed E-Voting Cloud System (ECS) system has three phases: The first phase is the registration phase, the second phase is vote polling, and the third phase is result announcements. In the proposed system, the election commission of India can search and verify the vote data through cloud computing. For a detailed description of our proposed protocol, a cube data storage structure and user differentiated system are first implemented. Based on the cube data structure and user differentiated system model, the proposed protocol helps to store voter data in the cloud with the encrypted model and ECS. Finally, the candidate can decrypt the data using their key. The people can verify the result announced by the ECS. The performance analysis clearly shows that our proposed system is highly secure when compared to the existing system. Using the proposed work, secure data transfer can be performed in an efficient way for online e-voting applications.