Biblio

The paper proposes ways to solve the problem of secure remote access to telecommunications’ equipment. The purpose of the study is to develop a set of procedures to ensure secure interaction while working remotely with Cisco equipment using the SSH protocol. This set of measures is a complete list of measures which ensures security of remote connection to a corporate computer network using modern methods of cryptography and network administration technologies. It has been tested on the GNS3 software emulator and Cisco telecommunications equipment and provides a high level of confidentiality and integrity of remote connection to a corporate computer network. In addition, the study detects vulnerabilities in the IOS operating system while running SSH service and suggests methods for their elimination.

Generally, the defense measures taken against new cyber-attack methods are insufficient for cybersecurity risk management. Contrary to classical attack methods, the existence of undiscovered attack types called’ zero-day attacks’ can invalidate the actions taken. It is possible with honeypot systems to implement new security measures by recording the attacker’s behavior. The purpose of the honeypot is to learn about the methods and tools used by the attacker or malicious activity. In particular, it allows us to discover zero-day attack types and develop new defense methods for them. Attackers have made protocols such as SSH (Secure Shell) and Telnet, which are widely used for remote access to devices, primary targets. In this study, SSHTelnet honeypot was established using Cowrie software. Attackers attempted to connect, and attackers record their activity after providing access. These collected attacker log records and files uploaded to the system are published on Github to other researchers1. We shared the observations and analysis results of attacks on SSH and Telnet protocols with honeypot.

Generally, the defense measures taken against new cyber-attack methods are insufficient for cybersecurity risk management. Contrary to classical attack methods, the existence of undiscovered attack types called' zero-day attacks' can invalidate the actions taken. It is possible with honeypot systems to implement new security measures by recording the attacker's behavior. The purpose of the honeypot is to learn about the methods and tools used by the attacker or malicious activity. In particular, it allows us to discover zero-day attack types and develop new defense methods for them. Attackers have made protocols such as SSH (Secure Shell) and Telnet, which are widely used for remote access to devices, primary targets. In this study, SSHTelnet honeypot was established using Cowrie software. Attackers attempted to connect, and attackers record their activity after providing access. These collected attacker log records and files uploaded to the system are published on Github to other researchers1. We shared the observations and analysis results of attacks on SSH and Telnet protocols with honeypot.

Network traffic anomaly detection is of critical importance in cybersecurity due to the massive and rapid growth of sophisticated computer network attacks. Indeed, the more new Internet-related technologies are created, the more elaborate the attacks become. Among all the contemporary high-level attacks, dictionary-based brute-force attacks (BFA) present one of the most unsurmountable challenges. We need to develop effective methods to detect and mitigate such brute-force attacks in realtime. In this paper, we investigate SSH and FTP brute-force attack detection by using the Long Short-Term Memory (LSTM) deep learning approach. Additionally, we made use of machine learning (ML) classifiers: J48, naive Bayes (NB), decision table (DT), random forest (RF) and k-nearest-neighbor (k-NN), for additional detection purposes. We used the well-known labelled dataset CICIDS2017. We evaluated the effectiveness of the LSTM and ML algorithms, and compared their performance. Our results show that the LSTM model outperforms the ML algorithms, with an accuracy of 99.88%.

A honeypot provides information about the new attack and exploitation methods and allows analyzing the adversary's activities during or after exploitation. One way of an adversary to communicate with a server is via secure shell (SSH). SSH provides secure login, file transfer, X11 forwarding, and TCP/IP connections over untrusted networks. SSH is a preferred target for attacks, as it is frequently used with password-based authentication, and weak passwords are easily exploited using brute-force attacks. In this paper, we introduce a Virtual Machine Introspection based SSH honeypot. We discuss the design of the system and how to extract valuable information such as the credential used by the attacker and the entered commands. Our experiments show that the system is able to detect the adversary's activities during and after exploitation, and it has advantages compared to currently used SSH honeypot approaches.

This work presents a systematic analysis of symmetric encryption modes for SSH that are in use on the Internet, providing deployment statistics, new attacks, and security proofs for widely used modes. We report deployment statistics based on two Internet-wide scans of SSH servers conducted in late 2015 and early 2016. Dropbear and OpenSSH implementations dominate in our scans. From our first scan, we found 130,980 OpenSSH servers that are still vulnerable to the CBC-mode-specific attack of Albrecht et al. (IEEE S&P 2009), while we found a further 20,000 OpenSSH servers that are vulnerable to a new attack on CBC-mode that bypasses the counter-measures introduced in OpenSSH 5.2 to defeat the attack of Albrecht et al. At the same time, 886,449 Dropbear servers in our first scan are vulnerable to a variant of the original CBC-mode attack. On the positive side, we provide formal security analyses for other popular SSH encryption modes, namely ChaCha20-Poly1305, generic Encrypt-then-MAC, and AES-GCM. Our proofs hold for detailed pseudo-code descriptions of these algorithms as implemented in OpenSSH. Our proofs use a corrected and extended version of the "fragmented decryption" security model that was specifically developed for the SSH setting by Boldyreva et al. (Eurocrypt 2012). These proofs provide strong confidentiality and integrity guarantees for these alternatives to CBC-mode encryption in SSH. However, we also show that these alternatives do not meet additional, desirable notions of security (boundary-hiding under passive and active attacks, and denial-of-service resistance) that were formalised by Boldyreva et al.

This work presents a systematic analysis of symmetric encryption modes for SSH that are in use on the Internet, providing deployment statistics, new attacks, and security proofs for widely used modes. We report deployment statistics based on two Internet-wide scans of SSH servers conducted in late 2015 and early 2016. Dropbear and OpenSSH implementations dominate in our scans. From our first scan, we found 130,980 OpenSSH servers that are still vulnerable to the CBC-mode-specific attack of Albrecht et al. (IEEE S&P 2009), while we found a further 20,000 OpenSSH servers that are vulnerable to a new attack on CBC-mode that bypasses the counter-measures introduced in OpenSSH 5.2 to defeat the attack of Albrecht et al. At the same time, 886,449 Dropbear servers in our first scan are vulnerable to a variant of the original CBC-mode attack. On the positive side, we provide formal security analyses for other popular SSH encryption modes, namely ChaCha20-Poly1305, generic Encrypt-then-MAC, and AES-GCM. Our proofs hold for detailed pseudo-code descriptions of these algorithms as implemented in OpenSSH. Our proofs use a corrected and extended version of the "fragmented decryption" security model that was specifically developed for the SSH setting by Boldyreva et al. (Eurocrypt 2012). These proofs provide strong confidentiality and integrity guarantees for these alternatives to CBC-mode encryption in SSH. However, we also show that these alternatives do not meet additional, desirable notions of security (boundary-hiding under passive and active attacks, and denial-of-service resistance) that were formalised by Boldyreva et al.

We consider the setting of HTTP traffic over encrypted tunnels, as used to conceal the identity of websites visited by a user. It is well known that traffic analysis (TA) attacks can accurately identify the website a user visits despite the use of encryption, and previous work has looked at specific attack/countermeasure pairings. We provide the first comprehensive analysis of general-purpose TA countermeasures. We show that nine known countermeasures are vulnerable to simple attacks that exploit coarse features of traffic (e.g., total time and bandwidth). The considered countermeasures include ones like those standardized by TLS, SSH, and IPsec, and even more complex ones like the traffic morphing scheme of Wright et al. As just one of our results, we show that despite the use of traffic morphing, one can use only total upstream and downstream bandwidth to identify – with 98% accuracy - which of two websites was visited. One implication of what we find is that, in the context of website identification, it is unlikely that bandwidth-efficient, general-purpose TA countermeasures can ever provide the type of security targeted in prior work.