Investigation Approach for Network Attack Intention Recognition

2017 ◽  
Vol 9 (1) ◽  
pp. 17-38 ◽  
Author(s):  
Abdulghani Ali Ahmed
Keyword(s):  
Rapid Development ◽  
Sensitive Information ◽  
Effective Protection ◽  
Network Attacks ◽  
Similarity Metric ◽  
Network Attack ◽  
Network Information ◽  
Protection Systems ◽  
Network Technologies ◽  
Malicious Intent

Sensitive information has critical risks when transmitted through computer networks. Existing protection systems still have limitations with treating network information with sufficient confidentiality, integrity, and availability. The rapid development of network technologies helps increase network attacks and hides their malicious intentions. Attack intention is the ultimate attack goal that the attacker attempts to achieve by executing various intrusion methods or techniques. Recognizing attack intentions helps security administrator develop effective protection systems that can detect network attacks that have similar intentions. This paper analyses attack types and classifies them according to their malicious intent. An investigation approach based on similarity metric is proposed to recognize attacker plans and predict their intentions. The obtained results demonstrate that the proposed approach is capable of investigating similarity of attack signatures and recognizing the intentions of Network attack.

Investigation Approach for Network Attack Intention Recognition

2020 ◽  
pp. 185-208
Author(s):  
Abdulghani Ali Ahmed
Keyword(s):  
Rapid Development ◽  
Sensitive Information ◽  
Effective Protection ◽  
Network Attacks ◽  
Similarity Metric ◽  
Network Attack ◽  
Network Information ◽  
Protection Systems ◽  
Network Technologies ◽  
Malicious Intent

Sensitive information has critical risks when transmitted through computer networks. Existing protection systems still have limitations with treating network information with sufficient confidentiality, integrity, and availability. The rapid development of network technologies helps increase network attacks and hides their malicious intentions. Attack intention is the ultimate attack goal that the attacker attempts to achieve by executing various intrusion methods or techniques. Recognizing attack intentions helps security administrator develop effective protection systems that can detect network attacks that have similar intentions. This paper analyses attack types and classifies them according to their malicious intent. An investigation approach based on similarity metric is proposed to recognize attacker plans and predict their intentions. The obtained results demonstrate that the proposed approach is capable of investigating similarity of attack signatures and recognizing the intentions of Network attack.

scholarly journals Intelligent Techniques for Detecting Network Attacks: Review and Research Directions

Sensors ◽  
2021 ◽  
Vol 21 (21) ◽  
pp. 7070
Author(s):  
Malak Aljabri ◽  
Sumayh S. Aljameel ◽  
Rami Mustafa A. Mohammad ◽  
Sultan H. Almotiri ◽  
Samiha Mirza ◽  
...  
Keyword(s):  
Rapid Development ◽  
Attack Detection ◽  
Network Attacks ◽  
Research Directions ◽  
Network Attack ◽  
Detection Systems ◽  
Increased Risk ◽  
Use Of The Internet ◽  
Main Components ◽  
Network Technologies

The significant growth in the use of the Internet and the rapid development of network technologies are associated with an increased risk of network attacks. Network attacks refer to all types of unauthorized access to a network including any attempts to damage and disrupt the network, often leading to serious consequences. Network attack detection is an active area of research in the community of cybersecurity. In the literature, there are various descriptions of network attack detection systems involving various intelligent-based techniques including machine learning (ML) and deep learning (DL) models. However, although such techniques have proved useful within specific domains, no technique has proved useful in mitigating all kinds of network attacks. This is because some intelligent-based approaches lack essential capabilities that render them reliable systems that are able to confront different types of network attacks. This was the main motivation behind this research, which evaluates contemporary intelligent-based research directions to address the gap that still exists in the field. The main components of any intelligent-based system are the training datasets, the algorithms, and the evaluation metrics; these were the main benchmark criteria used to assess the intelligent-based systems included in this research article. This research provides a rich source of references for scholars seeking to determine their scope of research in this field. Furthermore, although the paper does present a set of suggestions about future inductive directions, it leaves the reader free to derive additional insights about how to develop intelligent-based systems to counter current and future network attacks.

A Review of Attacks and Countermeasures in Internet of Things and Cyber Physical Systems

2020 ◽  
pp. 1-24
Author(s):  
Vasaki Ponnusamy ◽  
Naveena Devi Regunathan ◽  
Pardeep Kumar ◽  
Robithoh Annur ◽  
Khalid Rafique
Keyword(s):  
Industrial Revolution ◽  
Denial Of Service ◽  
Internet Usage ◽  
Transport Layer ◽  
Distributed Denial Of Service ◽  
Sybil Attack ◽  
Network Attacks ◽  
Network Attack ◽  
Physical Layers ◽  
Network Information

The internet usage for commercial and public services has significantly increased over these decades to where security of information is becoming a more important issue to society. At the same time, the number of network attacks in IoT is increasing. These include distributed denial of service (DDOS) attack, phishing, trojan, and others that will cause the network information to not be secure. With the revolution in Industry 4.0 and IoT being the main asset in the Fourth Industrial Revolution, many companies spend thousands or millions to protect their networks and servers. Unfortunately, the success rate to prevent network attack is still not welcoming. The attacks on physical layers, such as jamming, node tampering; link layer, such as collision, unfairness, battery exhaustion; network layer, such as spoofing, hello flood, Sybil attack, wormhole, DOS, DDOS; transport layer, such as flooding, de-synchronization; application layer, such as flooding, are alarming. This chapter reviews attacks and countermeasures.

The New Period Encryption Technology in the Application the Study of Network Security

2014 ◽  
Vol 685 ◽  
pp. 599-602
Author(s):  
Jing Lin
Keyword(s):  
Network Security ◽  
Information Transmission ◽  
Computer Network ◽  
Rapid Development ◽  
Network Attacks ◽  
Network Information ◽  
New Period ◽  
Computer Network Security ◽  
The New Period

with the rapid development of computer, network is also in constant development. A variety of network attacks and the corresponding means alsobreed, network security has become now the human network life about to ask.One of the most important methods to protect the network security is a dataencryption, its application in computer network security greatly improves thesecurity of network information transmission.

scholarly journals Towards Intrusion Detection Of Previously Unknown Network Attacks

2021 ◽  
Author(s):  
Saif Alzubi ◽  
Frederic T. Stahl ◽  
Mohamed M. Gaber
Keyword(s):  
Network Flow ◽  
Telecommunication Network ◽  
Ground Truth ◽  
Network Attacks ◽  
Network Attack ◽  
Detection Techniques ◽  
Free Data ◽  
Normal Network ◽  
Unsupervised Anomaly Detection ◽  
Network Technologies

Advances in telecommunication network technologies have led to an ever more interconnected world. Accordingly, the types of threats and attacks to intrude or disable such networks or portions of it are continuing to develop likewise. Thus, there is a need to detect previously unknown attack types. Supervised techniques are not suitable to detect previously not encountered attack types. This paper presents a new ensemble-based Unknown Network Attack Detector (UNAD) system. UNAD proposes a training workflow composed of heterogeneous and unsupervised anomaly detection techniques, trains on attack-free data and can distinguish normal network flow from (previously unknown) attacks. This scenario is more realistic for detecting previously unknown attacks than supervised approaches and is evaluated on telecommunication network data with known ground truth. Empirical results reveal that UNAD can detect attacks on which the workflows have not been trained on with a precision of 75% and a recall of 80%. The benefit of UNAD with existing network attack detectors is, that it can detect completely new attack types that have never been encountered before.

scholarly journals Image-Based Automatic Watermeter Reading under Challenging Environments

Sensors ◽  
2021 ◽  
Vol 21 (2) ◽  
pp. 434
Author(s):  
Qingqi Hong ◽  
Yiwei Ding ◽  
Jinpeng Lin ◽  
Meihong Wang ◽  
Qingyang Wei ◽  
...  
Keyword(s):  
Smart Cities ◽  
Rapid Development ◽  
Mobile Network ◽  
Spatial Layout ◽  
Single Image ◽  
Automatic Instrument ◽  
Intelligent Sensors ◽  
Fifth Generation ◽  
Instrument Reading ◽  
Network Technologies

With the rapid development of artificial intelligence and fifth-generation mobile network technologies, automatic instrument reading has become an increasingly important topic for intelligent sensors in smart cities. We propose a full pipeline to automatically read watermeters based on a single image, using deep learning methods to provide new technical support for an intelligent water meter reading. To handle the various challenging environments where watermeters reside, our pipeline disentangled the task into individual subtasks based on the structures of typical watermeters. These subtasks include component localization, orientation alignment, spatial layout guidance reading, and regression-based pointer reading. The devised algorithms for orientation alignment and spatial layout guidance are tailored to improve the robustness of our neural network. We also collect images of watermeters in real scenes and build a dataset for training and evaluation. Experimental results demonstrate the effectiveness of the proposed method even under challenging environments with varying lighting, occlusions, and different orientations. Thanks to the lightweight algorithms adopted in our pipeline, the system can be easily deployed and fully automated.

Technology of animation in multimedia courseware of mechanical drawing

2021 ◽  
pp. 002072092098608
Author(s):  
Yucheng Shen ◽  
Wei Lu
Keyword(s):  
Divergent Thinking ◽  
Rapid Development ◽  
Development Trend ◽  
Internet Technology ◽  
Size Principle ◽  
Network Information ◽  
Teaching Platform ◽  
Multimedia Teaching ◽  
Multimedia Environment ◽  
Use Of Internet

With the rapid development of Internet technology in China, mechanical drawing plays a more and more important role in social development and practice. The main purpose is to use the course of mechanical drawing to accurately represent the appearance, size, principle and technology of the machine. It is often called the language of communication in the industry. In order to make mechanical drawing better applied and practiced, and to make maximum use of Internet technical resources, the establishment of multimedia courseware teaching mechanism is the development trend of mechanical drawing.In order to adapt to the trend of network information, based on the multimedia environment, this paper studies the application of animation technology in mechanical drawing teaching, and constructs a small multimedia teaching platform. Through the explanation of animation courseware, students can better understand the making and principle of mechanical drawing, and cultivate students' divergent thinking. The teaching platform combines teaching material knowledge with practice to deepen students' understanding of the basic content of mechanical drawing. Finally, the rationality and practicability of the system are analyzed by investigating the platform users. The results show that the application of animation technology in mechanical drawing teaching is reasonable and practical.

Deep learning for detecting logic-flaw-exploiting network attacks: An end-to-end approach

2021 ◽  
pp. 1-30
Author(s):  
Qingtian Zou ◽  
Anoop Singhal ◽  
Xiaoyan Sun ◽  
Peng Liu
Keyword(s):  
Deep Learning ◽  
Attack Detection ◽  
Network Data ◽  
Learning Models ◽  
Real World Data ◽  
Network Attacks ◽  
Network Attack ◽  
Public Network ◽  
Network Intrusion ◽  
End To End

Network attacks have become a major security concern for organizations worldwide. A category of network attacks that exploit the logic (security) flaws of a few widely-deployed authentication protocols has been commonly observed in recent years. Such logic-flaw-exploiting network attacks often do not have distinguishing signatures, and can thus easily evade the typical signature-based network intrusion detection systems. Recently, researchers have applied neural networks to detect network attacks with network logs. However, public network data sets have major drawbacks such as limited data sample variations and unbalanced data with respect to malicious and benign samples. In this paper, we present a new end-to-end approach based on protocol fuzzing to automatically generate high-quality network data, on which deep learning models can be trained for network attack detection. Our findings show that protocol fuzzing can generate data samples that cover real-world data, and deep learning models trained with fuzzed data can successfully detect the logic-flaw-exploiting network attacks.

scholarly journals AODV-MSA: A Security Routing Protocol on Mobile Ad Hoc Network

2021 ◽  
pp. 143-149
Author(s):  
Le Quang Minh ◽  
Keyword(s):  
Routing Protocol ◽  
Ad Hoc Network ◽  
Network Performance ◽  
Ad Hoc ◽  
Mobile Ad Hoc Network ◽  
Network Attacks ◽  
Network Attack ◽  
Asymmetric Encryption ◽  
Mobile Ad Hoc ◽  
Security Routing Protocol

Network security is an important problem, which attracts more attention because recent network attacks caused huge consequences such as data lose, reduce network performance and increase routing load. In this article, we show network attack forms in MANET and propose Multiple Signature Authenticate (MSA) mechanism using digital signature based on asymmetric encryption RSA. Moreover, we describe a new security routing protocol named AODV-MSA by integrating MSA into AODV. Using NS2 simulator system, we implement and examine the efficiency of the AODV-MSA protocol with the 32-bit keys.

scholarly journals A Survey on True Random Number Generators Based on Chaos

2019 ◽  
Vol 2019 ◽  
pp. 1-10 ◽  
Author(s):  
Fei Yu ◽  
Lixiang Li ◽  
Qiang Tang ◽  
Shuo Cai ◽  
Yun Song ◽  
...  
Keyword(s):  
Chaotic System ◽  
Key Management ◽  
Random Number ◽  
Initial Conditions ◽  
Rapid Development ◽  
Current Mode ◽  
Random Numbers ◽  
Random Number Generators ◽  
Network Information ◽  
Survey Paper

With the rapid development of communication technology and the popularization of network, information security has been highly valued by all walks of life. Random numbers are used in many cryptographic protocols, key management, identity authentication, image encryption, and so on. True random numbers (TRNs) have better randomness and unpredictability in encryption and key than pseudorandom numbers (PRNs). Chaos has good features of sensitive dependence on initial conditions, randomness, periodicity, and reproduction. These demands coincide with the rise of TRNs generating approaches in chaos field. This survey paper intends to provide a systematic review of true random number generators (TRNGs) based on chaos. Firstly, the two kinds of popular chaotic systems for generating TRNs based on chaos, including continuous time chaotic system and discrete time chaotic system are introduced. The main approaches and challenges are exposed to help researchers decide which are the ones that best suit their needs and goals. Then, existing methods are reviewed, highlighting their contributions and their significance in the field. We also devote a part of the paper to review TRNGs based on current-mode chaos for this problem. Finally, quantitative results are given for the described methods in which they were evaluated, following up with a discussion of the results. At last, we point out a set of promising future works and draw our own conclusions about the state of the art of TRNGs based on chaos.

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