Broken Authentication and Session Management Vulnerability: A Case Study of Web Application

Hassan, Mohamed H.; Nipa, Shamima Sultana; Akter, Marjan; Haque, Rafita; Deepa, Fabiha Nawar; Rahman, Mostafijur; Siddiqui, Md.; Sharif, Md. Hasan

doi:10.5013/ijssst.a.19.02.06

Cited by 21 publications

(13 citation statements)

References 20 publications

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“…Moreover, the PCS can expose different services such as web applications, Virtual Network Computing software, and so on. Several works broadly analyzed the vulnerabilities of web server and common attacks such as SQL injection [ 24 ], cross-site scripting [ 25 ], broken authentication and session management [ 26 ], and Denial of Services [ 27 ]. Furthermore, the patch management in ICS environment is more complicated than in the IT sector, so those vulnerabilities persist on industrial devices.…”

Section: Attack Surface Of Storage Systemsmentioning

confidence: 99%

Detecting Cyberattacks on Electrical Storage Systems through Neural Network Based Anomaly Detection Algorithm

Gaggero

Caviglia

Armellin

et al. 2022

Sensors

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Distributed Energy Resources (DERs) are growing in importance Power Systems. Battery Electrical Storage Systems (BESS) represent fundamental tools in order to balance the unpredictable power production of some Renewable Energy Sources (RES). Nevertheless, BESS are usually remotely controlled by SCADA systems, so they are prone to cyberattacks. This paper analyzes the vulnerabilities of BESS and proposes an anomaly detection algorithm that, by observing the physical behavior of the system, aims to promptly detect dangerous working conditions by exploiting the capabilities of a particular neural network architecture called the autoencoder. The results show the performance of the proposed approach with respect to the traditional One Class Support Vector Machine algorithm.

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Section: Attack Surface Of Storage Systemsmentioning

confidence: 99%

Detecting Cyberattacks on Electrical Storage Systems through Neural Network Based Anomaly Detection Algorithm

Gaggero

Caviglia

Armellin

et al. 2022

Sensors

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“…(i) Injections: manipulating the input to force a web application to execute arbitrary commands in the operating system and queries in databases [9], SQL injection is the most famous of injection attacks [10], and it allows the attacker to interact with the database by reading, writing, and modifying records. (ii) Broken authentication: exploiting logical and weakness points in the authentication mechanism to takeover and control accounts [11]. (iii) Sensitive data exposure: manipulating a web application to make it throw exceptions and expose sensitive data such as credentials of the database [12].…”

Section: Related Workmentioning

confidence: 99%

“…Input of data: d (dataset), a (algorithm), p1 (web server port), i1 (web server IP), p2 (WAF port), i2 (WAF IP). ( 1) Start (2) Connect to database to initialize Inputs (d, a, p1, i1, p2, i2) (3) Start WAF listener using Inputs (p1, i1, p2, i2) (4) Training WAF using Inputs (d, a) (5) While WAF listener is "ON": (6) If new request arrived R: (7) Parse R (8) Compute basic features vector B from parsed R (9) Compute V Final features vector from B (10) Compute C (class) of parsed request R by classify based on V (11) If C � "anomal" (12) Drop request (13) Redirect to custom page with message "Attack" (14) Else//C � 'normal' (15) pass request to web server (16) Store V and C in database ( 17) Endif ( 18) Endif ( 19) EndWhile (20) End ALGORITHM 1: Units of proposal WAF (detailed algorithm).…”

Section: Features Engineeringmentioning

confidence: 99%

Web Application Firewall Using Machine Learning and Features Engineering

Shaheed

Kurdy

2022

Security and Communication Networks

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Web application security has become a major requirement for any business, especially with the wide web attacks spreading despite the defensive measures and the continuous development of software frameworks and servers. In this study, we present a proposed model for a web application firewall that used machine learning and features engineering to detect common web attacks. Our proposed model analyses incoming requests to the webserver, parses these requests to extract four features that describe completely HTTP request parts (URL, payload, and headers), and classifies whether a request is normal or an anomaly. We took into consideration the limitation of previous works that use URL and payload only in classification and provided five features that describe and summarize all parts of the HTTP request using features engineering and previous experience in the field of the software security domain. Extracted features are length of request, percentage of characters allowed, percentage of special characters, and attack weight. These features were calculated for four different datasets CSIC 2010, HTTPParams 2015, Hybrid dataset (CSIC 2010 and HTTPParams), and real logs for the compromised web server. We evaluated our proposed model by using these updated datasets with four classification algorithms (Naive Bayes, logistic regression, decision tree, and support vector machine) with two methods (train test split and cross-validation) to negate the probability of overfitting and ensure that features are effective. Features values for a normal request are usually short request length, large allowed character ratio, small special character ratio, and zero attack weight or close to zero. Features values for anomaly requests are large request length, small allowed character percentage, large special character percentage, and very large numerically attack weight. Our proposed model achieved a classification accuracy of 99.6% with datasets used in research studies in this field and 98.8% with datasets of real web servers.

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“…Keempat, issue lainnya yang berhubungan contohnya password di dalam source code tidak boleh dalam bentuk hard-coded. Kelima, Session ID Protection hal ini digunakan biasanya untuk server mengidentifikasi user yang akan masuk ke dalam session menggunakan session ID (Hassan et al, 2018). Broken authentication memiliki fungsi untuk autentikasi dan manajemen session yang tidak dapat diterapkan dengan baik, memungkinkan penyerang menyusup untuk mendapatkan username dan password dan mengeksploitasi kelemahan implementasi untuk mengasumsikan identitas pengguna lain secara permanen atau sementara (OWASP, 2017).…”

Section: Pendahuluanunclassified

Optimasi Keamanan Web Server terhadap Serangan Broken Authentication Menggunakan Teknologi Blockchain

Riadi

Herman

Ifani

2021

JISKa

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The aspect of the internet that needs to be considered a security is the login system. The login system usually uses a username and password as an authentication method because it is easy to implement. However, data in the form of usernames and passwords are very vulnerable to theft, so it is necessary to increase the security of the login system. The purpose of this research is to investigate the security of the system. Whether the system is good at protecting user data or not, minimizing execution errors from the system and minimizing risk errors on the system so that the login system can be used safely. This research is conducted to test the system security with Burp Suite on the login system that has been built. Testing the security of this system by experimenting with POST data which is secured using blockchain technology makes the data sent in the form of hash blocks safer and more confidential so that the system is safer than before. Blockchain technology has successfully secured usernames and passwords from broken authentication attacks. By using the Burp Suite testing system, login is more specific in conducting security testing.

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Broken Authentication and Session Management Vulnerability: A Case Study of Web Application

Cited by 21 publications

References 20 publications

Detecting Cyberattacks on Electrical Storage Systems through Neural Network Based Anomaly Detection Algorithm

Detecting Cyberattacks on Electrical Storage Systems through Neural Network Based Anomaly Detection Algorithm

Web Application Firewall Using Machine Learning and Features Engineering

Optimasi Keamanan Web Server terhadap Serangan Broken Authentication Menggunakan Teknologi Blockchain

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