An Ensemble Approach to Control Network Traffic on IoT

2021 ◽  
pp. 759-765
Author(s):  
K. Sree Lakshmi, K.V.V.Satyanarayana
Keyword(s):  
Network Traffic ◽  
Cyber Security ◽  
Window Size ◽  
Cyber Attacks ◽  
Control Network ◽  
Data Detection ◽  
Data Packets ◽  
Digital Services ◽  
User Data ◽  
Significant Model

Cyber security is most widely seen in many domains. From various domains these attacks plays the major role in damaging the servers and making websites unavailable. Many challenges are facing with the various cyber attacks.Internet of Things (IoT) is most widely used to define as a pervasive network of a (broad) range of connected smart nodes that offer diverse digital services, including the collection of environmental and user data. Detection of cyber attacks is difficult task and this may cause the loss of data packets and may interrupt the server. In this paper, the Enhancement is developed to handle the attack packets effectively. This is the window based application i,e based on the window size the data is processed. The Enhancement is called as an Amplified and Forward for Bi- Directional traffic from Attacks. This is very significant model to detect the several types of attacks that occur in IoT. Results show the performance of proposed system.

scholarly journals Improvement of Network Cyber Security Services using Security Operation Models

2020 ◽  
Vol 9 (1) ◽  
pp. 254-261
Keyword(s):  
Power System ◽  
Cyber Security ◽  
Transmission Rate ◽  
Traffic Analysis ◽  
Cyber Attacks ◽  
Data Link ◽  
Link Layer ◽  
Security Controls ◽  
Data Link Layer ◽  
User Data

Concerns for service computer networks’ security and reliability are growing rapidly due to increasing service devices with connections to external networks. This aggravates vulnerability of service networks to cyber attacks through external connections. Though encryption can provide security for user data transmissions, encryption itself could not provide protections against traffic analysis attacks. Techniques against traffic-analysis attacks through statistically controlling the transmission rate of padded and encrypted frames are unsuited for power system applications. This paper proposes three security operation modes for the newly developed security layer, located below DNP3 data-link layer, to strengthen encryption and authentication operations against the effectiveness of trafficanalysis and cryptanalysis attacks. The security models use padding to disguise the amount of user data transmitted and disguise the user data link layer frame amongst a group of manufactured frames similar to statistically controlling data transmission rate. The proposed security operations have been successfully applied to enhance power system security controls.

scholarly journals Design of a dynamic and self-adapting system, supported with artificial intelligence, machine learning and real-time intelligence for predictive cyber risk analytics in extreme environments – cyber risk in the colonisation of Mars

2021 ◽  
Author(s):  
Petar Radanliev ◽  
David De Roure ◽  
Kevin Page ◽  
Max Van Kleek ◽  
Omar Santos ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Real Time ◽  
Cyber Security ◽  
Extreme Environments ◽  
Learning Technologies ◽  
Cyber Attacks ◽  
Edge Computing ◽  
Mathematical Formulas ◽  
Cyber Risk

AbstractMultiple governmental agencies and private organisations have made commitments for the colonisation of Mars. Such colonisation requires complex systems and infrastructure that could be very costly to repair or replace in cases of cyber-attacks. This paper surveys deep learning algorithms, IoT cyber security and risk models, and established mathematical formulas to identify the best approach for developing a dynamic and self-adapting system for predictive cyber risk analytics supported with Artificial Intelligence and Machine Learning and real-time intelligence in edge computing. The paper presents a new mathematical approach for integrating concepts for cognition engine design, edge computing and Artificial Intelligence and Machine Learning to automate anomaly detection. This engine instigates a step change by applying Artificial Intelligence and Machine Learning embedded at the edge of IoT networks, to deliver safe and functional real-time intelligence for predictive cyber risk analytics. This will enhance capacities for risk analytics and assists in the creation of a comprehensive and systematic understanding of the opportunities and threats that arise when edge computing nodes are deployed, and when Artificial Intelligence and Machine Learning technologies are migrated to the periphery of the internet and into local IoT networks.

Cybersecurity Teamwork: A Review of Current Practices and Suggested Improvements

2020 ◽  
Vol 64 (1) ◽  
pp. 451-455
Author(s):  
Richard J. Simonson ◽  
Joseph R. Keebler ◽  
Mathew Lessmiller ◽  
Tyson Richards ◽  
John C. Lee
Keyword(s):  
Cyber Security ◽  
Cyber Attacks ◽  
Team Science ◽  
The Past ◽  
Insight Into ◽  
Current Practices

As cyber-attacks and their subsequent responses have become more frequent and complex over the past decade, research into the performance and effectiveness of cybersecurity teams has gained an immense amount of traction. However, investigation of teamwork in this domain is lacking due to the exclusion of known team competencies and a lack of reliance on team science. This paper serves to provide insight into the benefit that can be gained from utilizing the extant teamwork literature to improve teams’ research and applications in the domain of cyber-security.

scholarly journals Utilising Flow Aggregation to Classify Benign Imitating Attacks

Sensors ◽  
2021 ◽  
Vol 21 (5) ◽  
pp. 1761
Author(s):  
Hanan Hindy ◽  
Robert Atkinson ◽  
Christos Tachtatzis ◽  
Ethan Bayne ◽  
Miroslav Bures ◽  
...  
Keyword(s):  
Machine Learning ◽  
Feature Extraction ◽  
Network Traffic ◽  
Cyber Attacks ◽  
Detection Accuracy ◽  
Computational Power ◽  
Human Understanding ◽  
Flow Aggregation ◽  
Additional Level ◽  
Attack Surfaces

Cyber-attacks continue to grow, both in terms of volume and sophistication. This is aided by an increase in available computational power, expanding attack surfaces, and advancements in the human understanding of how to make attacks undetectable. Unsurprisingly, machine learning is utilised to defend against these attacks. In many applications, the choice of features is more important than the choice of model. A range of studies have, with varying degrees of success, attempted to discriminate between benign traffic and well-known cyber-attacks. The features used in these studies are broadly similar and have demonstrated their effectiveness in situations where cyber-attacks do not imitate benign behaviour. To overcome this barrier, in this manuscript, we introduce new features based on a higher level of abstraction of network traffic. Specifically, we perform flow aggregation by grouping flows with similarities. This additional level of feature abstraction benefits from cumulative information, thus qualifying the models to classify cyber-attacks that mimic benign traffic. The performance of the new features is evaluated using the benchmark CICIDS2017 dataset, and the results demonstrate their validity and effectiveness. This novel proposal will improve the detection accuracy of cyber-attacks and also build towards a new direction of feature extraction for complex ones.

An investigation into the effect of cybersecurity on attack prevention strategies

2020 ◽  
pp. 53-60
Author(s):  
Mohammed I. Alghamdi ◽  
Keyword(s):  
Information Technology ◽  
Computer Networks ◽  
Cyber Security ◽  
Information Technologies ◽  
Vital Role ◽  
Cyber Attacks ◽  
Security Threats ◽  
Prevention Strategies ◽  
Sufficient Knowledge ◽  
Simplified Solution

Our economy, infrastructure and societies rely to a large extent on information technology and computer networks solutions. Increasing dependency on information technologies has also multiplied the potential hazards of cyber-attacks. The prime goal of this study is to critically examine how the sufficient knowledge of cyber security threats plays a vital role in detection of any intrusion in simple networks and preventing the attacks. The study has evaluated various literatures and peer reviewed articles to examine the findings obtained by consolidating the outcomes of different studies and present the final findings into a simplified solution.

SARCP - Exploiting Cyber-Attack Prediction Through Socially-Aware Recommendation

2022 ◽  
Vol 14 (1) ◽  
pp. 0-0
Keyword(s):  
Social Network ◽  
Real World ◽  
Cyber Security ◽  
Betweenness Centrality ◽  
Cyber Attacks ◽  
Experimental Results ◽  
Cyber Attack ◽  
Defence Mechanisms ◽  
Network Measure ◽  
Recommender Algorithm

In the domain of cyber security, the defence mechanisms of networks has traditionally been placed in a reactionary role. Cyber security professionals are therefore disadvantaged in a cyber-attack situation due to the fact that it is vital that they maneuver such attacks before the network is totally compromised. In this paper, we utilize the Betweenness Centrality network measure (social property) to discover possible cyber-attack paths and then employ computation of similar personality of nodes/users to generate predictions about possible attacks within the network. Our method proposes a social recommender algorithm called socially-aware recommendation of cyber-attack paths (SARCP), as an attack predictor in the cyber security defence domain. In a social network, SARCP exploits and delivers all possible paths which can result in cyber-attacks. Using a real-world dataset and relevant evaluation metrics, experimental results in the paper show that our proposed method is favorable and effective.

scholarly journals Fuzzy-Based Symmetrical Multi-Criteria Decision-Making Procedure for Evaluating the Impact of Harmful Factors of Healthcare Information Security

Symmetry ◽  
2020 ◽  
Vol 12 (4) ◽  
pp. 664 ◽  
Author(s):  
Rajeev Kumar ◽  
Abhishek Kumar Pandey ◽  
Abdullah Baz ◽  
Hosam Alhakami ◽  
Wajdi Alhakami ◽  
...  
Keyword(s):  
Decision Making ◽  
Information Security ◽  
Information Management ◽  
Cyber Security ◽  
Cyber Attacks ◽  
Multi Criteria Decision Making ◽  
Local Hospital ◽  
Healthcare Information ◽  
Security Breaches ◽  
The Impact

Growing concern about healthcare information security in the wake of alarmingly rising cyber-attacks is being given symmetrical priority by current researchers and cyber security experts. Intruders are penetrating symmetrical mechanisms of healthcare information security continuously. In the same league, the paper presents an overview on the current situation of healthcare information and presents a layered model of healthcare information management in organizations. The paper also evaluates the various factors that have a key contribution in healthcare information security breaches through a hybrid fuzzy-based symmetrical methodology of AHP-TOPSIS. Furthermore, for assessing the effect of the calculated results, the authors have tested the results on local hospital software of Varanasi. Tested results of the factors are validated through the comparison and sensitivity analysis in this study. Tabulated results of the proposed study propose a symmetrical mechanism as the most conversant technique which can be employed by the experts and researchers for preparing security guidelines and strategies.

scholarly journals Cyber Attacks on Critical Infrastructure

2016 ◽  
pp. 448-465
Author(s):  
Ana Kovacevic ◽  
Dragana Nikolic
Keyword(s):  
Control Systems ◽  
Cyber Security ◽  
Critical Infrastructure ◽  
Cyber Attacks ◽  
Cyber Attack ◽  
Future Directions ◽  
Infrastructure Systems ◽  
Cyber Threats ◽  
Scada Systems ◽  
Insight Into

We are facing the expansion of cyber incidents, and they are becoming more severe. This results in the necessity to improve security, especially in the vulnerable field of critical infrastructure. One of the problems in the security of critical infrastructures is the level of awareness related to the effect of cyberattacks. The threat to critical infrastructure is real, so it is necessary to be aware of it and anticipate, predict, and prepare against a cyber attack. The main reason for the escalation of cyberattacks in the field of Critical Infrastructure (CI) may be that most control systems used for CI do not utilise propriety protocols and software anymore; they instead utilise standard solutions. As a result, critical infrastructure systems are more than ever before becoming vulnerable and exposed to cyber threats. It is important to get an insight into what attack types occur, as this may help direct cyber security efforts. In this chapter, the authors present vulnerabilities of SCADA systems against cyber attack, analyse and classify existing cyber attacks, and give future directions to achieve better security of SCADA systems.

scholarly journals Revealing and Sharing Malware Profile Using Malware Threat Intelligence Platform

2021 ◽  
Vol 6 (1) ◽  
pp. 72-82
Author(s):  
Faiz Iman Djufri ◽  
Charles Lim
Keyword(s):  
Cyber Security ◽  
Security Threats ◽  
Cyber Intelligence ◽  
Intelligence Sharing ◽  
Signature Detection ◽  
Threat Intelligence ◽  
User Data ◽  
Self Discovery ◽  
New Generation ◽  
Security Incidents

Cyber Security is an interchange between attackers and defenders, a non-static balancing force. The increasing trend of novel security threats and security incidents, which does not seem to be stopping, prompts the need to add another line of security defences. This is because the risk management and risk detection has become virtually impossible due to the limited access towards user data and the variations of modern threat taxonomies. The traditional strategy of self-discovery and signature detection which has a static nature is now obsolete in facing threats of the new generation with a dynamic nature; threats which are resilient, complex, and evasive. Therefore, this thesis discusses the use of MISP and The Triad Investigation approach to share the Indicator of Compromise on Cyber Intelligence Sharing Platform to be able to address the newt threats.

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