Blockchain-Based Man-in-the-Middle (MITM) Attack Detection for Photovoltaic Systems

2021 ◽  
Author(s):  
Jinchun Choi ◽  
Bohyun Ahn ◽  
Gomanth Bere ◽  
Seerin Ahmad ◽  
Homer Alan Mantooth ◽  
...  
Keyword(s):  
Attack Detection ◽  
Photovoltaic Systems ◽  
Man In The Middle ◽  
Mitm Attack

Hybrid Routing for Man-in-the-Middle (MITM) Attack Detection in IoT Networks

2019 ◽  
Author(s):  
James Jin Kang ◽  
Kiran Fahd ◽  
Sitalakshmi Venkatraman ◽  
Rolando Trujillo-Rasua ◽  
Paul Haskell-Dowland
Keyword(s):  
Attack Detection ◽  
Hybrid Routing ◽  
Man In The Middle ◽  
Mitm Attack

A Procedure for Collecting and Labeling Man-in-the-Middle Attack Traffic

2017 ◽  
Vol 24 (01) ◽  
pp. 1750002 ◽  
Author(s):  
Chad Calvert ◽  
Taghi M. Khoshgoftaar ◽  
Maryam M. Najafabadi ◽  
Clifford Kemp
Keyword(s):  
Real World ◽  
Production Environment ◽  
Representative Data ◽  
Man In The Middle ◽  
Scale Network ◽  
The Impact ◽  
Traffic Behavior ◽  
Gain Access ◽  
Mitm Attack

In this work, we outline a procedure for collecting and labeling Man-in-the-Middle (MITM) attack traffic. Our capture procedure allows for the collection of real-world representative data using a full-scale network environment. MITM attacks are typically performed with the purpose of intercepting information amongst two networked machines. This enables the attacker to gain access to otherwise confidential communications and potentially alter said communications maliciously. MITM attacks are still a very common attack that can be implemented with relative ease across a variety of network environments. Our work establishes experimental procedures for enacting three prevalent MITM attack variants through penetration testing. The process for data collection is defined, along with our approach on gathering real-world, representative data. We also present a novel labeling procedure based on the inherent behaviors of each MITM attack variant. Our work aims to address the challenges associated with collecting such data within a live production environment, as well as identify the impact MITM attacks have on traffic behavior. We also present a case study to provide some quantitative analysis regarding the data collected.

scholarly journals Man in the Middle and Current Injection Attacks Against the KLJN Key Exchanger Compromised by DC Sources

2020 ◽  
pp. 2150011
Author(s):  
M. Y. Melhem ◽  
L. B. Kish
Keyword(s):  
Current Injection ◽  
Johnson Noise ◽  
Injection Attacks ◽  
Ideal Situation ◽  
Man In The Middle ◽  
Active Attacks ◽  
The Impact ◽  
Mitm Attack ◽  
The Ideal

This study addresses a new question regarding the security of the Kirchhoff-Law-Johnson-Noise (KLJN) scheme compromised by DC sources at Alice and Bob: What is the impact of these parasitic sources on active attacks, such as the man-in-the-middle (MITM) attack, or the current injection attack if Alice and Bod did not eliminate these sources? The surprising answer is that the parasitic DC sources actually increase the security of the system because, in the case of the MITM attack, they make easier to uncover the eavesdropping than the ideal situation. In some of the cases, Eve can fix this deficiency but then the problem gets reduced to the original MITM attack to which the KLJN scheme is immune, it is already proven earlier.

scholarly journals Defending Against Man-In-The-Middle Attack in Repeated Games

2017 ◽  
Author(s):  
Shuxin Li ◽  
Xiaohong Li ◽  
Jianye Hao ◽  
Bo An ◽  
Zhiyong Feng ◽  
...  
Keyword(s):  
Nash Equilibrium ◽  
Repeated Games ◽  
Information Leakage ◽  
Solution Concept ◽  
Equilibrium Strategy ◽  
Nash Equilibrium Strategy ◽  
Man In The Middle ◽  
Unique Nash Equilibrium ◽  
Simultaneous Move ◽  
Mitm Attack

The Man-in-the-Middle (MITM) attack has become widespread in networks nowadays. The MITM attack would cause serious information leakage and result in tremendous loss to users. Previous work applies game theory to analyze the MITM attack-defense problem and computes the optimal defense strategy to minimize the total loss. It assumes that all defenders are cooperative and the attacker know defenders' strategies beforehand. However, each individual defender is rational and may not have the incentive to cooperate. Furthermore, the attacker can hardly know defenders' strategies ahead of schedule in practice. To this end, we assume that all defenders are self-interested and model the MITM attack-defense scenario as a simultaneous-move game. Nash equilibrium is adopted as the solution concept which is proved to be always unique. Given the impracticability of computing Nash equilibrium directly, we propose practical adaptive algorithms for the defenders and the attacker to learn towards the unique Nash equilibrium through repeated interactions. Simulation results show that the algorithms are able to converge to Nash equilibrium strategy efficiently.

scholarly journals Preventing Man-in-The-Middle (MiTM) Attack of GSM Calls

2021 ◽  
Vol 5 (4) ◽  
pp. 63-68
Author(s):  
B. I. Bakare ◽  
S. M. Ekolama
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Network Attack ◽  
Network Intrusion ◽  
Cellular Telephony ◽  
Depth Analysis ◽  
Man In The Middle ◽  
Internet Presence ◽  
Artificial Neural ◽  
Mitm Attack

Preventing man-in-the-middle (MiTM) attack using Artificial Neural Network refers to an in depth analysis of how calls are made vis-a-viz the structure of the inter-related operations that binds the respective subsystems within the GSM Architecture during calls. Calls in the GSM network is a request from aMobile Station (MS). This request has faced severe attacks due to the network’s access to Internet presence that has made its way into cellular telephony, creating a vulnerable and susceptible network attack such as Man-in-the-middle. This paper proffer solution to Man-in-the-middle attack during GSM calls by using Artificial Neural Network which can be embedded into the Protocol Stack to detect network intrusion and prevent Man-in-the-middle attack to obtain hitch-free local and international calls.

scholarly journals Detection and Prevention of Man-in-the-Middle Spoofing Attacks in MANETs Using Predictive Techniques in Artificial Neural Networks (ANN)

2019 ◽  
Vol 2019 ◽  
pp. 1-14 ◽  
Author(s):  
Robert A. Sowah ◽  
Kwadwo B. Ofori-Amanfo ◽  
Godfrey A. Mills ◽  
Koudjo M. Koumadi
Keyword(s):  
Intrusion Detection ◽  
Ad Hoc Network ◽  
Ad Hoc ◽  
Mobile Ad Hoc Network ◽  
Attack Detection ◽  
Mobility Patterns ◽  
Wired Networks ◽  
Man In The Middle ◽  
Mobile Ad Hoc ◽  
Ann Classification

A Mobile Ad-Hoc Network (MANET) is a convenient wireless infrastructure which presents many advantages in network settings. With Mobile Ad-Hoc Network, there are many challenges. These networks are more susceptible to attacks such as black hole and man-in-the-middle (MITM) than their corresponding wired networks. This is due to the decentralized nature of their overall architecture. In this paper, ANN classification methods in intrusion detection for MANETs were developed and used with NS2 simulation platform for attack detection, identification, blacklisting, and node reconfiguration for control of nodes attacked. The ANN classification algorithm for intrusion detection was evaluated using several metrics. The performance of the ANN as a predictive technique for attack detection, isolation, and reconfiguration was measured on a dataset with network-varied traffic conditions and mobility patterns for multiple attacks. With a final detection rate of 88.235%, this work not only offered a productive and less expensive way to perform MITM attacks on simulation platforms but also identified time as a crucial factor in determining such attacks as well as isolating nodes and reconfiguring the network under attack. This work is intended to be an opening for future malicious software time signature creation, identification, isolation, and reconfiguration to supplement existing Intrusion Detection Systems (IDSs).

scholarly journals Trusted Time-Based Verification Model for Automatic Man-in-the-Middle Attack Detection in Cybersecurity

Cryptography ◽  
2018 ◽  
Vol 2 (4) ◽  
pp. 38 ◽  
Author(s):  
James Jin Kang ◽  
Kiran Fahd ◽  
Sitalakshmi Venkatraman
Keyword(s):  
Attack Detection ◽  
Cyber Attacks ◽  
Transport Layer ◽  
Transmission Time ◽  
Network Resource ◽  
Robust Solution ◽  
Detection Systems ◽  
Proposed Model ◽  
Man In The Middle ◽  
Verification Model

Due to the prevalence and constantly increasing risk of cyber-attacks, new and evolving security mechanisms are required to protect information and networks and ensure the basic security principles of confidentiality, integrity, and availability—referred to as the CIA triad. While confidentiality and integrity can be achieved using Secure Sockets Layer (SSL)/Transport Layer Security (TLS) certificates, these depend on the correct authentication of servers, which could be compromised due to man-in-the-middle (MITM) attacks. Many existing solutions have practical limitations due to their operational complexity, deployment costs, as well as adversaries. We propose a novel scheme to detect MITM attacks with minimal intervention and workload to the network and systems. Our proposed model applies a novel inferencing scheme for detecting true anomalies in transmission time at a trusted time server (TTS) using time-based verification of sent and received messages. The key contribution of this paper is the ability to automatically detect MITM attacks with trusted verification of the transmission time using a learning-based inferencing algorithm. When used in conjunction with existing systems, such as intrusion detection systems (IDS), which require comprehensive configuration and network resource costs, it can provide a robust solution that addresses these practical limitations while saving costs by providing assurance.

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