Biblio

User Authentication is a difficult problem yet to be addressed accurately. Little or no work is reported in literature dealing with clustering-based anomaly detection techniques for user authentication for keystroke data. Therefore, in this paper, Modified Differential Evolution (MDE) based subspace anomaly detection technique is proposed for user authentication in the context of behavioral biometrics using keystroke dynamics features. Thus, user authentication is posed as an anomaly detection problem. Anomalies in CMU's keystroke dynamics dataset are identified using subspace-based and distance-based techniques. It is observed that, among the proposed techniques, MDE based subspace anomaly detection technique yielded the highest Area Under ROC Curve (AUC) for user authentication problem. We also performed a Wilcoxon Signed Rank statistical test to corroborate our results statistically.

Keystroke Dynamics is the study of typing patterns and rhythm for personal identification and traits. Keystrokes may be analysed as fixed text such as passwords or as continuous typed text such as documents. This paper reviews different classification metrics for continuous text, such as the A and R metrics, Canberra, Manhattan and Euclidean and introduces a variant of the Minkowski distance. To test the metrics, we adopted a substantial dataset containing 239 thousand records acquired under real, harsh, and unidealised conditions. We propose a new parameter for the Minkowski metric, and we reinforce another for the A metric, as initially stated by its authors.

In the modern day and age, credential based authentication systems no longer provide the level of security that many organisations and their services require. The level of trust in passwords has plummeted in recent years, with waves of cyber attacks predicated on compromised and stolen credentials. This method of authentication is also heavily reliant on the individual user's choice of password. There is the potential to build levels of security on top of credential based authentication systems, using a risk based approach, which preserves the seamless authentication experience for the end user. One method of adding this security to a risk based authentication framework, is keystroke dynamics. Monitoring the behaviour of the users and how they type, produces a type of digital signature which is unique to that individual. Learning this behaviour allows dynamic flags to be applied to anomalous typing patterns that are produced by attackers using stolen credentials, as a potential risk of fraud. Methods from statistics and machine learning have been explored to try and implement such solutions. This paper will look at an Autoencoder model for learning the keystroke dynamics of specific users. The results from this paper show an improvement over the traditional tried and tested statistical approaches with an Equal Error Rate of 6.51%, with the additional benefits of relatively low training times and less reliance on feature engineering.

Recent years have seen an increased interest in digital wallets for a multitude of use cases including online banking, cryptocurrency, and digital identity management. Digital wallets play a pivotal role in the secure management of cryptographic keys and credentials, and for providing certain identity management services. In this paper, we examine a proof-of-concept digital wallet in the context of Self-Sovereign Identity and provide a practical decentralized key recovery solution using Shamir's secret sharing scheme and Hyperledger Indy distributed ledger technology.

Research on keystroke dynamics has the good potential to offer continuous authentication that complements conventional authentication methods in combating insider threats and identity theft before more harm can be done to the genuine users. Unfortunately, the large amount of data required by free-text keystroke authentication often contain personally identifiable information, or PII, and personally sensitive information, such as a user's first name and last name, username and password for an account, bank card numbers, and social security numbers. As a result, there are privacy risks associated with keystroke data that must be mitigated before they are shared with other researchers. We conduct a systematic study to remove PII's from a recent large keystroke dataset. We find substantial amounts of PII's from the dataset, including names, usernames and passwords, social security numbers, and bank card numbers, which, if leaked, may lead to various harms to the user, including personal embarrassment, blackmails, financial loss, and identity theft. We thoroughly evaluate the effectiveness of our detection program for each kind of PII. We demonstrate that our PII detection program can achieve near perfect recall at the expense of losing some useful information (lower precision). Finally, we demonstrate that the removal of PII's from the original dataset has only negligible impact on the detection error tradeoff of the free-text authentication algorithm by Gunetti and Picardi. We hope that this experience report will be useful in informing the design of privacy removal in future keystroke dynamics based user authentication systems.

A number of solutions have been proposed to tackle the user privacy-preserving issue. Most of existing schemes, however, focus on methodology and techniques from the perspective of data processing. In this paper, we propose a lightweight privacy-preserving scheme for user identity from the perspective of data user and applied cryptography. The basic idea is to break the association relationships between User identity and his behaviors and ensure that User can access data or services as usual while the real identity will not be revealed. To this end, an interactive zero-knowledge proof protocol of identity is executed between CSP and User. Besides, a trusted third-party is introduced to manage user information, help CSP to validate User identity and establish secure channel between CSP and User via random shared key. After passing identity validation, User can log into cloud platform as usual without changing existing business process using random temporary account and password generated by CSP and sent to User by the secure channel which can further obscure the association relationships between identity and behaviors. Formal security analysis and theoretic and experimental evaluations are conducted, showing that the proposal is efficient and practical.

It is standard practice that the secret key derived from an execution of a Password Authenticated Key Exchange (PAKE) protocol is used to authenticate and encrypt some data payload using a Symmetric Key Protocol (SKP). Unfortunately, most PAKEs of practical interest are studied using so-called game-based models, which – unlike simulation models – do not guarantee secure composition per se. However, Brzuska et al. (CCS 2011) have shown that a middle ground is possible in the case of authenticated key exchange that relies on Public-Key Infrastructure (PKI): the game-based models do provide secure composition guarantees when the class of higher-level applications is restricted to SKPs. The question that we pose in this paper is whether or not a similar result can be exhibited for PAKE. Our work answers this question positively. More specifically, we show that PAKE protocols secure according to the game-based Real-or-Random (RoR) definition with the weak forward secrecy of Abdalla et al. (S&P 2015) allow for safe composition with arbitrary, higher-level SKPs. Since there is evidence that most PAKEs secure in the Find-then-Guess (FtG) model are in fact secure according to RoR definition, we can conclude that nearly all provably secure PAKEs enjoy a certain degree of composition, one that at least covers the case of implementing secure channels.

This paper presents a possible implementation of progressive authentication using the Android pattern lock. Our key idea is to use one pattern for two access levels to the device; an abridged pattern is used to access generic applications and a second, extended and higher-complexity pattern is used less frequently to access more sensitive applications. We conducted a user study of 89 participants and a consecutive user survey on those participants to investigate the usability of such a pattern scheme. Data from our prototype showed that for unlocking lowsecurity applications the median unlock times for users of the multiple pattern scheme and conventional pattern scheme were 2824 ms and 5589 ms respectively, and the distributions in the two groups differed significantly (Mann-Whitney U test, p-value less than 0.05, two-tailed). From our user survey, we did not find statistically significant differences between the two groups for their qualitative responses regarding usability and security (t-test, p-value greater than 0.05, two-tailed), but the groups did not differ by more than one satisfaction rating at 90% confidence.

User authentication in wireless sensor networks is more complex than normal networks due to sensor network characteristics such as unmanned operation, limited resources, and unreliable communication. For this reason, various authentication protocols have been presented to provide secure and efficient communication. In 2017, Wu et al. presented a provable and privacy-preserving user authentication protocol for wireless sensor networks. Unfortunately, we found that Wu et al.'s protocol was still vulnerable against user impersonation attack, and had a problem in the password change phase. We show how an attacker can impersonate an other user and why the password change phase is ineffective.

Problem: Today, many methods of influencing on personnel in the communication process are available to social engineers and information security specialists, but in practice it is difficult to say which method and why it is appropriate to use one. Criteria and indicators of effective communication are not formalized. Purpose: to formalize the concept of effective communication, to offer a tool for combining existing methods and means of communication, to formalize the purpose of communication. Methods: Use of the terminal model of a control system for a non-stochastic communication object. Results. Two examples demonstrating the possibility of using the terminal model of the communication control system, which allows you to connect tools and methods of communication, justify the requirements for the structure and feedback of communication, select the necessary communication algorithms depending on the observed response of the communication object. Practical significance: the results of the research can be used in planning and conducting effective communication in the process of information protection, in business, in private relationships and in other areas of human activity.

Kerberos is a third party and widely used authentication protocol, in which it enables computers to connect securely using a single sign-on over an insecure channel. It proves the identity of clients and encrypts all the communications between them to ensure data privacy and integrity. Typically, Kerberos composes of three communication phases to establish a secure session between any two clients. The authentication is based on a password-based scheme, in which it is a secret long-term key shared between the client and the Kerberos. Therefore, Kerberos suffers from a password-guessing attack, the main drawback of Kerberos. In this paper, we overcome this limitation by modifying the first initial phase using the virtual password and biometric data. In addition, the proposed protocol provides a strong authentication scenario against multiple types of attacks.

In order to solve the problem of vulnerable password guessing attacks caused by dictionary attacks, replay attacks in the authentication process, and man-in-the-middle attacks in the existing wireless local area network in terms of security authentication, we make some improvements to the 802.1X / EAP authentication protocol based on the study of the current IEEE802.11i security protocol with high security. After introducing the idea of Kerberos protocol authentication and applying the idea in the authentication process of 802.1X / EAP, a new protocol of Kerberos extensible authentication protocol (KEAP) is proposed. Firstly, the protocol introduces an asymmetric key encryption method, uses public key encryption during data transmission, and the receiver uses the corresponding private key for decryption. With unidirectional characteristics and high security, the encryption can avoid password guessing attacks caused by dictionary attacks as much as possible. Secondly, aiming at the problem that the request message sent from the client to the authentication server is vulnerable to replay attacks, the protocol uses a combination of the message sequence number and the random number, and the message serial number is added to the request message sent from the client to the authentication server. And establish a list database for storing message serial number and random number in the authentication server. After receiving a transfer message, the serial number and the random number are extracted and compared with the values in the list database to distinguish whether it is a retransmission message. Finally, the protocol introduces a keychain mechanism and uses an irreversible Hash function to encrypt the final authentication result, thereby effectively solving the man-in-the-middle attack by the pretender. The experiment uses the OPNET 14.5 simulation platform to model the KEAP protocol and simulate simulation attacks, and compares it with the current more common EAP-TLS authentication protocol. Experimental results show that the average traffic of the KEAP protocol is at least 14.74% higher than the EAP-TLS authentication protocol, and the average bit error rate is reduced by at least 24.00%.

Password auditing can enhance the cyber situational awareness of defenders, e.g. cyber security/IT professionals, with regards to the strength of text-based authentication mechanisms utilized in an organization. Auditing results can proactively indicate if weak passwords exist in an organization, decreasing the risks of compromisation. Password cracking is a typical and time-consuming way to perform password auditing. Given that defenders perform password auditing within a specific evaluation timeframe, the cracking process needs to be optimized to yield useful results. Existing password cracking tools do not provide holistic features to optimize the process. Therefore, the need arises to build new password auditing toolkits to assist defenders to achieve their task in an effective and efficient way. Moreover, to maximize the benefits of password auditing, a security policy should be utilized. Currently the efforts focus on the specification of password security policies, providing rules on how to construct passwords. This work proposes the functionality that should be supported by next-generation password auditing toolkits and provides guidelines to drive the specification of a relevant password auditing policy.

An important principle in computational security is to reduce the attack surface, by maintaining the Trusted Computing Base (TCB) small. Even so, no security technique ensures full protection against any adversary. Thus, sensitive applications should be designed with several layers of protection so that, even if a layer might be violated, sensitive content will not be compromised. In 2015, Intel released the Software Guard Extensions (SGX) technology in its processors. This mechanism allows applications to allocate enclaves, which are private memory regions that can hold code and data. Other applications and even privileged code, like the OS kernel and the BIOS, are not able to access enclaves' contents. This paper presents a novel password file protection scheme, which uses Intel SGX to protect authentication credentials in the PAM authentication framework, commonly used in UNIX systems. We defined and implemented an SGX-enabled version of the pam\_unix.so authentication module, called UniSGX. This module uses an SGX enclave to handle the credentials informed by the user and to check them against the password file. To add an extra security layer, the password file is stored using SGX sealing. A threat model was proposed to assess the security of the proposed solution. The obtained results show that the proposed solution is secure against the threat model considered, and that its performance overhead is acceptable from the user point of view. The scheme presented here is also suitable to other authentication frameworks.

Secret passwords are very widely used for user authentication to websites, despite their known shortcomings. Most websites using passwords also implement password recovery to allow users to re-establish a shared secret if the existing value is forgotten; many such systems involve sending a password recovery email to the user, e.g. containing a secret link. The security of password recovery, and hence the entire user-website relationship, depends on the email being acted upon correctly; unfortunately, as we show, such emails are not always designed to maximise security and can introduce vulnerabilities into recovery. To understand better this serious practical security problem, we surveyed password recovery emails for 50 of the top English language websites. We investigated a range of security and usability issues for such emails, covering their design, structure and content (including the nature of the user instructions), the techniques used to recover the password, and variations in email content from one web service to another. Many well-known web services, including Facebook, Dropbox, and Microsoft, suffer from recovery email design, structure and content issues. This is, to our knowledge, the first study of its type reported in the literature. This study has enabled us to formulate a set of recommendations for the design of such emails.

The current paper is a continuation of a published article and is about the results of implementing a Honeypot in the Cloud. A five years period of raw data is analyzed and explained in the current Cyber Security state and landscape.

In 2017, Gelernter et al. identified the ``password-reset man-in-the-middle'' attack, which can take over a user's account during two-factor authentication. In this attack, a password reset request is sent via an SMS message instead of an expected authentication request, and the user enters a reset code at the malicious man-in-the-middle website without recognizing that the code resets the password. Following this publication, most vulnerable websites attempted to remove the vulnerability. However, it is still not clear whether these attempts were sufficient to prevent careless users from being attacked. In this paper, we describe the results of an investigation involving domestic major websites that were vulnerable to this type of attack. To clarify the causes of vulnerability, we conducted experiments with 180 subjects. The SMS-message parameters were ``with/without warning'', ``numeric/alphanumeric code'', and ``one/two messages'', and subjects were tested to see if they input the reset code into the fake website. According to the result of the experiment, we found that the PRMitM risk odds were increased 4.6, 1.86, and 11.59 times higher in a no-warning case, a numeric-only reset code, and a behavior that change passwords very frequently, respectively.

Two-factor authentication (2FA) popularly works by verifying something the user knows (a password) and something she possesses (a token, popularly instantiated with a smart phone). Conventional 2FA systems require extra interaction like typing a verification code, which is not very user-friendly. For improved user experience, recent work aims at zero-effort 2FA, in which a smart phone placed close to a computer (where the user enters her username/password into a browser to log into a server) automatically assists with the authentication. To prove her possession of the smart phone, the user needs to prove the phone is on the login spot, which reduces zero-effort 2FA to co-presence detection. In this paper, we propose SoundAuth, a secure zero-effort 2FA mechanism based on (two kinds of) ambient audio signals. SoundAuth looks for signs of proximity by having the browser and the smart phone compare both their surrounding sounds and certain unpredictable near-ultrasounds; if significant distinguishability is found, SoundAuth rejects the login request. For the ambient signals comparison, we regard it as a classification problem and employ a machine learning technique to analyze the audio signals. Experiments with real login attempts show that SoundAuth not only is comparable to existent schemes concerning utility, but also outperforms them in terms of resilience to attacks. SoundAuth can be easily deployed as it is readily supported by most smart phones and major browsers.

With the recent advances in information and communication technology, Web and Mobile Internet applications have become a part of our daily lives. These developments have also emerged Information Security concept due to the necessity of protecting information of institutions from Internet attackers. There are many security approaches to provide information security in Enterprise applications. However, using only one of these approaches may not be efficient enough to obtain security. This paper describes a Multi-Layered Framework of implementing two-factor and single sign-on authentication together. The proposed framework generates unique one-time passwords (OTP), which are used to authenticate application data. Nevertheless, using only OTP mechanism does not meet security requirements. Therefore, implementing a separate authentication application which has single sign-on capability is necessary.

In this paper, we propose a new authentication method to prevent authentication vulnerability of Claim Token method of Membership Service provide in Private BlockChain. We chose Hyperledger Fabric v1.0 using JWT authentication method of membership service. TOTP, which generate OTP tokens and user authentication codes that generate additional time-based password on existing authentication servers, has been applied to enforce security and two-factor authentication method to provide more secure services.

Ubiquitous Healthcare System (U-Healthcare) is a well-known application of wireless sensor networking (WSN). In this system, the sensors take less power for operating the function. As the data transfers between sensor and other stations is sensitive so there needs to provide a security scheme. Due to the low life of sensor nodes in Wireless Sensor Networks (WSN), asymmetric key based security (AKS) architecture is always considered as unsuitable for these types of networks. Several papers have been published in recent past years regarding how to incorporate AKS in WSN, Haque et al's Asymmetric key based Architecture (AKA) is one of them. But later it is found that this system has authentication problem and therefore prone to man-in-the-middle (MITM) attack, furthermore it is not a truly asymmetric based scheme. We address these issues in this paper and proposed a complete asymmetric approach using PEKS-PM (proposed by Pham in [8]) to remove impersonation attack. We also found some other vulnerabilities in the original AKA system and proposed solutions, therefore making it a better and enhanced asymmetric key based architecture.

We introduce MobiCeal, the first practical Plausibly Deniable Encryption (PDE) system for mobile devices that can defend against strong coercive multi-snapshot adversaries, who may examine the storage medium of a user's mobile device at different points of time and force the user to decrypt data. MobiCeal relies on "dummy write" to obfuscate the differences between multiple snapshots of storage medium due to existence of hidden data. By incorporating PDE in block layer, MobiCeal supports a broad deployment of any block-based file systems on mobile devices. More importantly, MobiCeal is secure against side channel attacks which pose a serious threat to existing PDE schemes. A proof of concept implementation of MobiCeal is provided on an LG Nexus 4 Android phone using Android 4.2.2. It is shown that the performance of MobiCeal is significantly better than prior PDE systems against multi-snapshot adversaries.

Most mobile applications generate local data on internal memory with SharedPreference interface of an Android operating system. Therefore, many possible loopholes can access the confidential information such as passwords. We propose a hybrid encryption approach for SharedPreferences to protect the leaking confidential information through the source code. We develop an Android application and store some data using SharedPreference. We produce different experiments with which this data could be accessed. We apply Hybrid encryption approach combining encryption approach with Android Keystore system, for providing better encryption algorithm to hide sensitive data.

SQL Injection is one of the most critical security vulnerability in web applications. Most web applications use SQL as web applications. SQL injection mainly affects these websites and web applications. An attacker can easily bypass a web applications authentication and authorization and get access to the contents they want by SQL injection. This unauthorised access helps the attacker to retrieve confidential data's, trade secrets and can even delete or modify valuable documents. Even though, to an extend many preventive measures are found, till now there are no complete solution for this problem. Hence, from the surveys and analyses done, an enhanced methodology is proposed against SQL injection disclosure and deterrence by ensuring proper authentication using Heisenberg analysis and password security using Honey pot mechanism.

Web-Based applications are becoming more increasingly technically complex and sophisticated. The very nature of their feature-rich design and their capability to collate, process, and disseminate information over the Internet or from within an intranet makes them a popular target for attack. According to Open Web Application Security Project (OWASP) Top Ten Cheat sheet-2017, SQL Injection Attack is at peak among online attacks. This can be attributed primarily to lack of awareness on software security. Developing effective SQL injection detection approaches has been a challenge in spite of extensive research in this area. In this paper, we propose a signature based SQL injection attack detection framework by integrating fingerprinting method and Pattern Matching to distinguish genuine SQL queries from malicious queries. Our framework monitors SQL queries to the database and compares them against a dataset of signatures from known SQL injection attacks. If the fingerprint method cannot determine the legitimacy of query alone, then the Aho Corasick algorithm is invoked to ascertain whether attack signatures appear in the queries. The initial experimental results of our framework indicate the approach can identify wide variety of SQL injection attacks with negligible impact on performance.