Diversity-aware, Cost-effective Network Security Hardening Using Attack Graph

2017 ◽  
pp. 1-15
Author(s):  
M. A. Jabbar ◽  
Ghanshyam S. Bopche ◽  
B. L. Deekshatulu ◽  
B. M. Mehtre
Keyword(s):  
Network Security ◽  
Cost Effective ◽  
Attack Graph ◽  
Security Hardening ◽  
Effective Network

On the design of a cost effective network security switch architecture

2005 ◽  
Author(s):  
Nen-Fu Huang ◽  
Chih-Hao Chen ◽  
Rong-Tai Liu ◽  
Chia-Nan Kao ◽  
Chih-Chiang Wu
Keyword(s):  
Network Security ◽  
Cost Effective ◽  
Switch Architecture ◽  
Effective Network

scholarly journals Implementasi Multiple Honeypot pada Raspberry Pi dan Visualisasi Log Honeypot Menggunakan ELK Stack

Repositor ◽  
2020 ◽  
Vol 2 (4) ◽  
pp. 475
Author(s):  
Ilfan Arif Romadhan ◽  
Syaifudin Syaifudin ◽  
Denar Regata Akbi
Keyword(s):  
Network Security ◽  
Cost Effective ◽  
Raspberry Pi ◽  
Log Analysis ◽  
Security Threats ◽  
Multiple Sources ◽  
Important Data ◽  
Desktop Computers ◽  
Monitoring Result

ABSTRAKPerlindungan terhadap keamanan jaringan merupakan hal yang sangat penting untuk dilakukan. Mengingat kemudahan dalam mengakses jaringan memungkinkan adanya gangguan dari pihak yang ingin menyerang, merusak, bahkan mengambil data penting. Honeypot memang tidak menyelesaikan masalah pada keamanan jaringan, namun honeypot membuat penelitian tentang serangan menjadi lebih sederhana dengan konsep yang mudah untuk dimengerti dan dimplementasikan. Penelitian ini menerapkan beberapa honeypot menggunakan Raspberry pi dan ELK stack untuk monitoring hasil yang didapatkan oleh honeypot. Tujuan dari penelitian ini untuk merancang sistem yang mampu mendeteksi serangan pada jaringan menggunakan honeypot. Raspberry pi digunakan sebagai sensor honeypot untuk pemantauan ancaman keamanan terbukti hemat biaya dan efektif menggantikan komputer desktop. ELK stack memudahkan pemusatan data dari berbagai sumber dan membuat analisis log yang awalnya rumit untuk dianalisis menjadi lebih menarik.ABSTRACTProtection of network security is very important to do. Given the ease in accessing the network allows for interference from parties who want to attack, destroy, and even retrieve important data. Honeypot does not solve the problem on network security, but the honeypot makes research about attacks become simpler with concepts that are easy to understand and implement. This research applies some honeypot using Raspberry pi and ELK stack for monitoring result obtained by honeypot. The purpose of this research is to design a system capable of detecting attacks on a network using a honeypot. Raspberry pi is used as a honeypot sensor for monitoring proven cost-effective and cost-effective security threats to replace desktop computers. The ELK stack facilitates the convergence of data from multiple sources and makes log analysis initially complex for analysis to be more interesting.

scholarly journals A Nodes-Based Non-Structural Model Considering a Series Structure for Heat Exchanger Network Synthesis

Processes ◽  
2020 ◽  
Vol 8 (6) ◽  
pp. 695
Author(s):  
Yue Xu ◽  
Heri Ambonisye Kayange ◽  
Guomin Cui
Keyword(s):  
Heat Exchanger ◽  
Heat Exchangers ◽  
Structural Model ◽  
Cost Effective ◽  
Maximum Energy ◽  
Network Synthesis ◽  
Heat Exchanger Network ◽  
Proposed Model ◽  
Effective Network ◽  
Heat Exchanger Network Synthesis

The aim of heat exchanger network synthesis is to design a cost-effective network configuration with the maximum energy recovery. Therefore, a nodes-based non-structural model considering a series structure (NNM) is proposed. The proposed model utilizes a simple principle based on setting the nodes on streams such that to achieve optimization of a heat exchanger network synthesis (HENS) problem. The proposed model uses several nodes to quantify the possible positions of heat exchangers so that the matching between hot and cold streams is random and free. Besides the stream splits, heat exchangers with series structures are introduced in the proposed model. The heuristic algorithm used to solve NNM model is a random walk algorithm with compulsive evolution. The proposed model is used to solve four scale cases of a HENS problem, the results show that the costs obtained by NNM model can be respectively lower 3226 $/a(Case 1), 11,056 $/a(Case 2), 2463 $/a(Case 3), 527 $/a(Case 4) than the best costs listed in literature.

scholarly journals DeepIDS: Deep Learning Approach for Intrusion Detection in Software Defined Networking

Electronics ◽  
2020 ◽  
Vol 9 (9) ◽  
pp. 1533 ◽  
Author(s):  
Tuan Anh Tang ◽  
Lotfi Mhamdi ◽  
Des McLernon ◽  
Syed Ali Raza Zaidi ◽  
Mounir Ghogho ◽  
...  
Keyword(s):  
Neural Network ◽  
Deep Learning ◽  
Intrusion Detection ◽  
Detection System ◽  
Software Defined Networking ◽  
Cost Effective ◽  
The Internet ◽  
Network Intrusion ◽  
Effective Network ◽  
Control Application

Software Defined Networking (SDN) is developing as a new solution for the development and innovation of the Internet. SDN is expected to be the ideal future for the Internet, since it can provide a controllable, dynamic, and cost-effective network. The emergence of SDN provides a unique opportunity to achieve network security in a more efficient and flexible manner. However, SDN also has original structural vulnerabilities, which are the centralized controller, the control-data interface and the control-application interface. These vulnerabilities can be exploited by intruders to conduct several types of attacks. In this paper, we propose a deep learning (DL) approach for a network intrusion detection system (DeepIDS) in the SDN architecture. Our models are trained and tested with the NSL-KDD dataset and achieved an accuracy of 80.7% and 90% for a Fully Connected Deep Neural Network (DNN) and a Gated Recurrent Neural Network (GRU-RNN), respectively. Through experiments, we confirm that the DL approach has the potential for flow-based anomaly detection in the SDN environment. We also evaluate the performance of our system in terms of throughput, latency, and resource utilization. Our test results show that DeepIDS does not affect the performance of the OpenFlow controller and so is a feasible approach.

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