Human errors in performing security-critical tasks are typically blamed on the complexity of those tasks. However, such errors can also occur because of (possibly unexpected) sensory distractions. A sensory distraction that produces negative effects can be abused by the adversary that controls the environment. Meanwhile, a distraction with positive effects can be artificially introduced to improve user performance. The goal of this work is to explore the effects of visual stimuli on the performance of security-critical tasks. To this end, we experimented with a large number of subjects who were exposed to a range of unexpected visual stimuli while attempting to perform Bluetooth Pairing. Our results clearly demonstrate substantially increased task completion times and markedly lower task success rates. These negative effects are noteworthy, especially, when contrasted with prior results on audio distractions which had positive effects on performance of similar tasks. Experiments were conducted in a novel (fully automated and completely unattended) experimental environment. This yielded more uniform experiments, better scalability and significantly lower financial and logistical burdens. We discuss this experience, including benefits and limitations of the unattended automated experiment paradigm.
@cite_21 proposed an authentication protocol that used Mad-Lib" style SAS. Each device in this protocol creates a nonsensical phrase based on the protocol outcome, and the user then determine if the two phrases match. This approach was found to be easier for non-specialist users.
@cite_21
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Can we secure user authentication against eavesdropping adversaries, relying on human cognitive functions alone, unassisted by any external computational device? To accomplish this goal, we propose challenge response protocols that rely on a shared secret set of pictures. Under the considered brute-force attack the protocols are safe against eavesdropping, in that a modestly powered adversary who fully records a series of successful interactions cannot compute the user's secret. Moreover, the protocols can be tuned to any desired level of security against random guessing, where security can be traded-off with authentication time. The proposed protocols have two drawbacks: First, training is required to familiarize the user with the secret set of pictures. Second, depending on the level of security required, entry time can be significantly longer than with alternative methods. We describe user studies showing that people can use these protocols successfully, and quantify the time it takes for training and for successful authentication. We show evidence that the secret can be maintained for a long time (up to a year) with relatively low loss. We present attacks against two cognitive authentication schemes [3] recently proposed at the 2006 IEEE Symposium on Security and Privacy. These authentication schemes are designed to be secure against eavesdropping attacks while relying only on human cognitive skills. They achieve authentication via challenge response protocols based on a shared secret set of pictures. Our attacks use a SAT solver to recover a user’s key in a few seconds, after observing only a small number of successful logins. These attacks demonstrate that the authentication schemes of [3] are not secure against an eavesdropping adversary. Small, mobile devices without user interfaces, such as Bluetooth headsets, often need to communicate securely over wireless networks. Active attacks can only be prevented by authenticating wireless communication, which is problematic when devices do not have any a priori information about each other. We introduce a new method for device-to-device authentication by shaking devices together. This paper describes two protocols for combining cryptographic authentication techniques with known methods of accelerometer data analysis to the effect of generating authenticated, secret keys. The protocols differ in their design, one being more conservative from a security point of view, while the other allows more dynamic interactions. Three experiments are used to optimize and validate our proposed authentication method. Implicit authentication schemes are a secondary authentication mechanism that provides authentication by employing unique patterns of device use that are gathered from smartphone users without requiring deliberate actions. Contemporary implicit authentication schemes operate at the device level such that they neither discriminate between data from different applications nor make any assumption about the nature of the application that the user is currently using. In this paper, we challenge the device-centric approach to implicit authentication on smartphones. We argue that the conventional approach of misuse detection at the device level has inherent limitations for mobile platforms. To this end, we analyze and empirically evaluate the device-centric nature of implicit authentication schemes to show their limitations in terms of detection accuracy, authentication overhead, and fine grained authentication control. To mitigate these limitations and for effective and pragmatic implicit authentication on the mobile platform, we propose a novel application-centric implicit authentication approach. We observe that for implicit authentication, an application knows best on when to authenticate and how to authenticate. Therefore, we delegate the implicit authentication task to the application and let the application provider decide when and how to authenticate a user in order to protect the owner's personal information. Our proposed application-centric implicit authentication approach improves accuracy and provides fine grained authentication control with low authentication overhead. Future research in this domain will benefit from our findings to provide pragmatic implicit authentication solutions. This paper presents the results of a security and usability review of the authentication implementations used by more than 10 UK banks. Our focus is on their use of dual text credentials that combine two passwords, PINs, or challenge questions (and some “partial selection” variations). We model the authentication protocols based upon several deployment choices, such as the credential rules, and use the model to compare the security and usability properties of the implementations. Our results indicate some variation and inconsistency across the UK banking industry, from which we offer some suggestions for improved authentication protocol design. The authors specify authentication protocols as formal objects with precise syntax and semantics, and define a semantic model that characterizes protocol executions. They have identified two basic types of correctness properties, namely, correspondence and secrecy; that underlie the correctness concerns of authentication protocols. Assertions for specifying these properties, and a formal semantics for their satisfaction in the semantic model are defined. The Otway-Rees protocol is used to illustrate the semantic model and the basic correctness properties. > A challenge in facilitating spontaneous mobile interactions is to provide pairing methods that are both intuitive and secure. Simultaneous shaking is proposed as a novel and easy-to-use mechanism for pairing of small mobile devices. The underlying principle is to use common movement as a secret that the involved devices share for mutual authentication. We present two concrete methods, ShaVe and ShaCK, in which sensing and analysis of shaking movement is combined with cryptographic protocols for secure authentication. ShaVe is based on initial key exchange followed by exchange and comparison of sensor data for verification of key authenticity. ShaCK, in contrast, is based on matching features extracted from the sensor data to construct a cryptographic key. The classification algorithms used in our approach are shown to robustly separate simultaneous shaking of two devices from other concurrent movement of a pair of devices, with a false negative rate of under 12 percent. A user study confirms that the method is intuitive and easy to use, as users can shake devices in an arbitrary pattern. Traditional password based authentication scheme is vulnerable to shoulder surfing attack. So if an attacker sees a legitimate user to enter password then it is possible for the attacker to use that credentials later to illegally login into the system and may do some malicious activities. Many methodologies exist to prevent such attack. These methods are either partially observable or fully observable to the attacker. In this paper we have focused on detection of shoulder surfing attack rather than prevention. We have introduced the concept of tag digit to create a trap known as honeypot. Using the proposed methodology if the shoulder surfers try to login using others’ credentials then there is a high chance that they will be caught red handed. Comparative analysis shows that unlike the existing preventive schemes, the proposed methodology does not require much computation from users end. Thus from security and usability perspective the proposed scheme is quite robust and powerful. Touch input implicit authentication ( touch IA'') employs behavioural biometrics like touch location and pressure to continuously and transparently authenticate smartphone users. We provide the first ever evaluation of targeted mimicry attacks on touch IA and show that it fails against shoulder surfing and offline training attacks. Based on experiments with three diverse touch IA schemes and 256 unique attacker-victim pairs, we show that shoulder surfing attacks have a bypass success rate of 84 with the majority of successful attackers observing the victim's behaviour for less than two minutes. Therefore, the accepted assumption that shoulder surfing attacks on touch IA are infeasible due to the hidden nature of some features is incorrect. For offline training attacks, we created an open-source training app for attackers to train on their victims' touch data. With this training, attackers achieved bypass success rates of 86 , even with only partial knowledge of the underlying features used by the IA scheme. Previous work failed to find these severe vulnerabilities due to its focus on random, non-targeted attacks. Our work demonstrates the importance of considering targeted mimicry attacks to evaluate the security of an implicit authentication scheme. Based on our results, we conclude that touch IA is unsuitable from a security standpoint. Key agreement protocols are frequently based on the Diffie-Hellman protocol but require authenticating the protocol messages in two ways. This can be made by a cross-authentication protocol. Such protocols, based on the assumption that a channel which can authenticate short strings is available (SAS-based), have been proposed by Vaudenay. In this paper, we survey existing protocols and we propose a new one. Our proposed protocol requires three moves and a single SAS to be authenticated in two ways. It is provably secure in the random oracle model. We can further achieve security with a generic construction (e.g. in the standard model) at the price of an extra move. We discuss applications such as secure peer-to-peer VoIP. The single-writer multi-reader searchable encryption (SMSE) allows an arbitrary authorized user to submit a valid search token and get the corresponding encrypted identifiers. In order to achieve fine-grained access control, the identifiers are encrypted by the attribute-based encryption. In this case, the user can decrypt a ciphertext only when the access policy in it matches the user’s attribute set. However, the server unable to determine whether the user can decrypt a certain ciphertext without the knowledge of the user’s attribute set. As a result, all the ciphertexts based on a search token have to be returned to the user, which causes unnecessary communication and decryption costs. In this paper, we propose a new SMSE scheme, in which the server just needs to return the ones which can be decrypted by the user rather than the whole search results. In order to achieve this goal, we present a server-side match technique with which the server can test whether the user can decrypt a ciphertext without knowing the user’s attribute set. Furthermore, the decryption computation is very efficient, irrespective of the structure of access policy. Therefore, both the communication and decryption overheads are dramatically reduced in our scheme. Authentication methods can be improved by considering implicit, individual behavioural cues. In particular, verifying users based on typing behaviour has been widely studied with physical keyboards. On mobile touchscreens, the same concepts have been applied with little adaptations so far. This paper presents the first reported study on mobile keystroke biometrics which compares touch-specific features between three different hand postures and evaluation schemes. Based on 20.160 password entries from a study with 28 participants over two weeks, we show that including spatial touch features reduces implicit authentication equal error rates (EER) by 26.4 - 36.8 relative to the previously used temporal features. We also show that authentication works better for some hand postures than others. To improve applicability and usability, we further quantify the influence of common evaluation assumptions: known attacker data, training and testing on data from a single typing session, and fixed hand postures. We show that these practices can lead to overly optimistic evaluations. In consequence, we describe evaluation recommendations, a probabilistic framework to handle unknown hand postures, and ideas for further improvements. Knowledge-based authentication systems generally rely upon users' explicit recollection of passwords, facts, or personal preferences. These systems impose a cognitive burden that often results in forgotten secrets or secrets with poor entropy. We propose an authentication system that instead draws on implicit memory - that is, the unconscious encoding and usage of information. In such a system, a user is initially presented with images of common objects in a casual familiarization task. When the user later authenticates, she is asked to perform a task involving a set of degraded images, some of which are based upon the images in the familiarization task. The prior exposure to those images influences the user's responses in the task, thereby eliciting authentication information. We ran a user study to investigate the plausibility of our system design. Our results suggest that implicit memory has potential as a basis for low-cognitive-overhead, high-stability, knowledge-based authentication. We study the question of basing symmetric key cryptography on weak secrets. In this setting, Alice and Bob share an n-bit secret W, which might not be uniformly random, but the adversary has at least k bits of uncertainty about it (formalized using conditional min-entropy). Since standard symmetric-key primitives require uniformly random secret keys, we would like to construct an authenticated key agreement protocol in which Alice and Bob use W to agree on a nearly uniform key R, by communicating over a public channel controlled by an active adversary Eve. We study this question in the information theoretic setting where the attacker is computationally unbounded. We show that single-round (i.e. one message) protocols do not work when k ≤ n 2, and require poor parameters even when n 2 On the other hand, for arbitrary values of k, we design a communication efficient two-round (challenge-response) protocol extracting nearly k random bits. This dramatically improves the previous construction of Renner and Wolf [32], which requires Θ(λ + log(n)) rounds where λ is the security parameter. Our solution takes a new approach by studying and constructing "non-malleable" seeded randomness extractors -- if an attacker sees a random seed X and comes up with an arbitrarily related seed X', then we bound the relationship between R= Ext(W;X) and R' = Ext(W;X'). We also extend our two-round key agreement protocol to the "fuzzy" setting, where Alice and Bob share "close" (but not equal) secrets WA and WB, and to the Bounded Retrieval Model (BRM) where the size of the secret W is huge. This paper describes an experiment to investigate user perceptions of the usability and security of single-factor and two-factor authentication methods in automated telephone banking. In a controlled experiment with 62 banking customers a knowledge-based, single-factor authentication procedure, based on those commonly used in the financial services industry, was compared with a two-factor approach where in addition to the knowledge-based step, a one-time passcode was generated using a hardware security token. Results were gathered on the usability and perceived security of the two methods described, together with call completion rates and call durations for the two methods. Significant differences were found between the two methods, with the two-factor version being perceived as offering higher levels of security than the single-factor authentication version; however, this gain was offset by significantly lower perceptions of usability, and lower ratings for convenience and ease of use for the two-factor version. In addition, the two-factor authentication version took longer for participants to complete. This research provides valuable empirical evidence of the trade-off between security and usability in automated systems. We propose to establish a secure communication channel among devices based on similar audio patterns. Features from ambient audio are used to generate a shared cryptographic key between devices without exchanging information about the ambient audio itself or the features utilized for the key generation process. We explore a common audio-fingerprinting approach and account for the noise in the derived fingerprints by employing error correcting codes. This fuzzy-cryptography scheme enables the adaptation of a specific value for the tolerated noise among fingerprints based on environmental conditions by altering the parameters of the error correction and the length of the audio samples utilized. In this paper, we experimentally verify the feasibility of the protocol in four different realistic settings and a laboratory experiment. The case studies include an office setting, a scenario where an attacker is capable of reproducing parts of the audio context, a setting near a traffic loaded road, and a crowded canteen environment. We apply statistical tests to show that the entropy of fingerprints based on ambient audio is high. The proposed scheme constitutes a totally unobtrusive but cryptographically strong security mechanism based on contextual information. We present an improved logic for analysing authentication properties of cryptographic protocols, based on the SVO logic of Syverson and van Oorschot (1994). Such logics are useful in electronic commerce, among other areas. We have constructed this logic in order to simplify automation, and we describe an implementation using the Isabelle theorem-proving system, and a GUI tool based on this implementation. The tool is typically operated by opening a list of propositions intended to be true, and clicking one button. Since the rules form a clean framework, the logic is easily extensible. We also present in detail a proof of soundness, using Kripke possible-worlds semantics. Two-factor authentication protects online accounts even if passwords are leaked. Most users, however, prefer password-only authentication. One reason why two-factor authentication is so unpopular is the extra steps that the user must complete in order to log in. Currently deployed two-factor authentication mechanisms require the user to interact with his phone to, for example, copy a verification code to the browser. Two-factor authentication schemes that eliminate user-phone interaction exist, but require additional software to be deployed. In this paper we propose Sound-Proof, a usable and deployable two-factor authentication mechanism. Sound-Proof does not require interaction between the user and his phone. In Sound-Proof the second authentication factor is the proximity of the user's phone to the device being used to log in. The proximity of the two devices is verified by comparing the ambient noise recorded by their microphones. Audio recording and comparison are transparent to the user, so that the user experience is similar to the one of password-only authentication. Sound-Proof can be easily deployed as it works with current phones and major browsers without plugins. We build a prototype for both Android and iOS. We provide empirical evidence that ambient noise is a robust discriminant to determine the proximity of two devices both indoors and outdoors, and even if the phone is in a pocket or purse. We conduct a user study designed to compare the perceived usability of Sound-Proof with Google 2-Step Verification. Participants ranked Sound-Proof as more usable and the majority would be willing to use Sound-Proof even for scenarios in which two-factor authentication is optional. Two-factor authentication protects online accounts even if passwords are leaked. Most users, however, prefer password-only authentication. One reason why two-factor authentication is so unpopular is the extra steps that the user must complete in order to log in. Currently deployed two-factor authentication mechanisms require the user to interact with his phone to, for example, copy a verification code to the browser. Two-factor authentication schemes that eliminate user-phone interaction exist, but require additional software to be deployed. In this paper we propose Sound-Proof, a usable and deployable two-factor authentication mechanism. Sound-Proof does not require interaction between the user and his phone. In Sound-Proof the second authentication factor is the proximity of the user's phone to the device being used to log in. The proximity of the two devices is verified by comparing the ambient noise recorded by their microphones. Audio recording and comparison are transparent to the user, so that the user experience is similar to the one of password-only authentication. Sound-Proof can be easily deployed as it works with current phones and major browsers without plugins. We build a prototype for both Android and iOS. We provide empirical evidence that ambient noise is a robust discriminant to determine the proximity of two devices both indoors and outdoors, and even if the phone is in a pocket or purse. We conduct a user study designed to compare the perceived usability of Sound-Proof with Google 2-Step Verification. Participants ranked Sound-Proof as more usable and the majority would be willing to use Sound-Proof even for scenarios in which two-factor authentication is optional. Common authentication methods based on passwords, tokens, or fingerprints perform one-time authentication and rely on users to log out from the computer terminal when they leave. Users often do not log out, however, which is a security risk. The most common solution, inactivity timeouts, inevitably fail security (too long a timeout) or usability (too short a timeout) goals. One solution is to authenticate users continuously while they are using the terminal and automatically log them out when they leave. Several solutions are based on user proximity, but these are not sufficient: they only confirm whether the user is nearby but not whether the user is actually using the terminal. Proposed solutions based on behavioral biometric authentication (e.g., keystroke dynamics) may not be reliable, as a recent study suggests. To address this problem we propose Zero-Effort Bilateral Recurring Authentication (ZEBRA). In ZEBRA, a user wears a bracelet (with a built-in accelerometer, gyroscope, and radio) on her dominant wrist. When the user interacts with a computer terminal, the bracelet records the wrist movement, processes it, and sends it to the terminal. The terminal compares the wrist movement with the inputs it receives from the user (via keyboard and mouse), and confirms the continued presence of the user only if they correlate. Because the bracelet is on the same hand that provides inputs to the terminal, the accelerometer and gyroscope data and input events received by the terminal should correlate because their source is the same - the user's hand movement. In our experiments ZEBRA performed continuous authentication with 85 accuracy in verifying the correct user and identified all adversaries within 11s. For a different threshold that trades security for usability, ZEBRA correctly verified 90 of users and identified all adversaries within 50s.