Practical Attacks Research Articles

Practical attacks on the round‐reduced PRINCE

The PRINCE cipher is the result of a cooperation between the Technical University of Denmark, NXP Semiconductors and the Ruhr University Bochum. The cipher was designed to reach an extremely low-latency encryption and instant response time. PRINCE has already gained a lot of attention from the academic community, however, most of the attacks are theoretical, usually with very high time or data complexity. This work helps to fill the gap in more practically oriented attacks, with more realistic scenarios and complexities. New attacks are presented, up to seven rounds, relying on integral and higher-order differential cryptanalysis.

Vulnerabilities, Attacks, and Countermeasures in Balise-Based Train Control Systems

In modern rail transport systems, balises are widely used to exchange track-train information via air-gap interface. In this paper, we first present the vulnerabilities on the standard balise air-gap interface, and then conduct vulnerability simulations using the system parameters that were specified in the European Train Control System. The simulation results show that the vulnerabilities can be exploited to launch effective and practical attacks, which could lead to catastrophic consequences, such as train derailment or collision. To mitigate the vulnerabilities and attacks, we propose to implement a challenge-response authentication process in the air-gap interface in the existing transport infrastructure.

Recoverable Random Numbers in an Internet of Things Operating System

Over the past decade, several security issues with Linux Random Number Generator (LRNG) on PCs and Androids have emerged. The main problem involves the process of entropy harvesting, particularly at boot time. An entropy source in the input pool of LRNG is not transferred into the non-blocking output pool if the entropy counter of the input pool is less than 192 bits out of 4098 bits. Because the entropy estimation of LRNG is highly conservative, the process may require more than one minute for starting the transfer. Furthermore, the design principle of the estimation algorithm is not only heuristic but also unclear. Recently, Google released an Internet of Things (IoT) operating system called Brillo based on the Linux kernel. We analyze the behavior of the random number generator in Brillo, which inherits that of LRNG. In the results, we identify two features that enable recovery of random numbers. With these features, we demonstrate that random numbers of 700 bytes at boot time can be recovered with the success probability of 90% by using time complexity for 5.20 × 2 40 trials. Therefore, the entropy of random numbers of 700 bytes is merely about 43 bits. Since the initial random numbers are supposed to be used for sensitive security parameters, such as stack canary and key derivation, our observation can be applied to practical attacks against cryptosystem.

Analysis of Software Countermeasures for Whitebox Encryption

Whitebox cryptography aims to ensure the security of cryptographic algorithms in the whitebox model where the adversary has full access to the execution environment. To attain security in this setting is a challenging problem: Indeed, all published whitebox implementations of standard symmetric-key algorithms such as AES to date have been practically broken. However, as far as we know, no whitebox implementation in real-world products has suffered from a key recovery attack. This is due to the fact that commercial products deploy additional software protection mechanisms on top of the whitebox implementation. This makes practical attacks much less feasible in real-world applications. There are numerous software protection mechanisms which protect against standard whitebox attacks. One such technique is control flow obfuscation which randomizes the order of table lookups for each execution of the whitebox encryption module. Another technique is randomizing the locations of the various Look up tables (LUTs) in the memory address space. In this paper we investigate the effectiveness of these countermeasures against two attack paradigms. The first known as Differential Computational Analysis (DCA) attack was developed by Bos, Hubain, Michiels and Teuwen in CHES 2016. The attack passively collects software execution traces for several plaintext encryptions and uses the collected data to perform an analysis similar to the well known differential power attacks (DPA) to recover the secret key. Since the software execution traces contain time demarcated physical addresses of memory locations being read/written into, they essentially leak the values of the inputs to the various LUTs accessed during the whitebox encryption operation, which as it turns out leaks sufficient information to perform the power attack. We found that if in addition to control flow obfuscation, one were to randomize the locations of the LUTs in the memory, then it is very difficult to perform the DCA on the resultant system using such table inputs and extract the secret key in reasonable time. As an alternative, we investigate the version of the DCA attack which uses the outputs of the tables instead of the inputs to mount the power analysis attack. This modified DCA is able to extract the secret key from the flow obfuscated and location randomized versions of several whitebox binaries available in crypto literature. We develop another attack called the Zero Difference Enumeration (ZDE) attack. The attack records software traces for several pairs of strategically selected plaintexts and performs a simple statistical test on the effective difference of the traces to extract the secret key. We show that ZDE is able to recover the keys of whitebox systems. Finally we propose a new countermeasure for protecting whitebox binaries based on insertion of random delays which aims to make both the ZDE and DCA attackspractically difficult by adding random noise in the information leaked to the attacker.

Analysis of Software Countermeasures for Whitebox Encryption

Whitebox cryptography aims to ensure the security of cryptographic algorithms in the whitebox model where the adversary has full access to the execution environment. To attain security in this setting is a challenging problem: Indeed, all published whitebox implementations of standard symmetric-key algorithms such as AES to date have been practically broken. However, as far as we know, no whitebox implementation in real-world products has suffered from a key recovery attack. This is due to the fact that commercial products deploy additional software protection mechanisms on top of the whitebox implementation. This makes practical attacks much less feasible in real-world applications. There are numerous software protection mechanisms which protect against standard whitebox attacks. One such technique is control flow obfuscation which randomizes the order of table lookups for each execution of the whitebox encryption module. Another technique is randomizing the locations of the various Look up tables (LUTs) in the memory address space. In this paper we investigate the effectiveness of these countermeasures against two attack paradigms. The first known as Differential Computational Analysis (DCA) attack was developed by Bos, Hubain, Michiels and Teuwen in CHES 2016. The attack passively collects software execution traces for several plaintext encryptions and uses the collected data to perform an analysis similar to the well known differential power attacks (DPA) to recover the secret key. Since the software execution traces contain time demarcated physical addresses of memory locations being read/written into, they essentially leak the values of the inputs to the various LUTs accessed during the whitebox encryption operation, which as it turns out leaks sufficient information to perform the power attack. We found that if in addition to control flow obfuscation, one were to randomize the locations of the LUTs in the memory, then it is very difficult to perform the DCA on the resultant system using such table inputs and extract the secret key in reasonable time. As an alternative, we investigate the version of the DCA attack which uses the outputs of the tables instead of the inputs to mount the power analysis attack. This modified DCA is able to extract the secret key from the flow obfuscated and location randomized versions of several whitebox binaries available in crypto literature. We develop another attack called the Zero Difference Enumeration (ZDE) attack. The attack records software traces for several pairs of strategically selected plaintexts and performs a simple statistical test on the effective difference of the traces to extract the secret key. We show that ZDE is able to recover the keys of whitebox systems. Finally we propose a new countermeasure for protecting whitebox binaries based on insertion of random delays which aims to make both the ZDE and DCA attackspractically difficult by adding random noise in the information leaked to the attacker.

Trace Buffer Attack on the AES Cipher

Since the standardization of AES/Rijndael symmetric-key cipher by NIST in 2001, it gained widespread acceptance in various protocols and withstood intense scrutiny from the theoretical cryptanalysts. From the physical implementation point of view, however, AES remained vulnerable. Practical attacks on AES via fault injection, differential power analysis, scan-chain and cache-access timing have been demonstrated so far. In this paper, we propose a novel and effective attack, termed Trace Buffer Attack. Trace buffers are extensively used for post-silicon debug of integrated circuits. We identify the trace buffer as a source of information leakage. We first report the detailed process of trace buffer attack assuming that the register-transfer level (RTL) implementation is available. We further analyze the AES encryption algorithm and Rijndael’s key expansion algorithm, and illustrate that trace buffer attack is feasible without implementation (RTL) knowledge. Our experimental results show that trace buffer attack is capable of partially recovering the secret keys of different AES implementations.

Practical Key-Recovery Attack on MANTIS5

MANTIS is a lightweight tweakable block cipher published at CRYPTO 2016. In addition to the full 14-round version, MANTIS7, the designers also propose an aggressive 10-round version, MANTIS5. The security claim for MANTIS5 is resistance against “practical attacks”, defined as related-tweak attacks with data complexity 2d less than 230 chosen plaintexts (or 240 known plaintexts), and computational complexity at most 2126−d. We present a key-recovery attack against MANTIS5 with 228 chosen plaintexts and a computational complexity of about 238 block cipher calls, which violates this claim. Our attack is based on a family of differential characteristics and exploits several properties of the lightweight round function and tweakey schedule. To verify the validity of the attack, we also provide a practical implementation which recovers the full key in about 1 core hour using 230 chosen plaintexts.

Evaluating the Privacy Guarantees of Location Proximity Services

Location-based services have become an integral part of everyday life. To address the privacy issues that emerge from the use and sharing of location information, social networks and smartphone applications have adopted location proximity schemes as a means of balancing user privacy with utility. Unfortunately, despite the extensive academic literature on this topic, the schemes that large service providers have adopted are not always designed or implemented correctly, rendering users vulnerable to location-disclosure attacks. Such attacks have recently received major publicity as, in some cases, they even exposed citizens of oppressive regimes to life-threatening risks. In this article, we systematically assess the defenses that popular location-based services and mobile applications deploy to guard against adversaries seeking to identify a user’s location. We provide the theoretical foundations for formalizing the privacy guarantees of currently adopted proximity models, design practical attacks for each case, and prove tight bounds on the number of queries required for carrying out successful attacks in practice. To evaluate the completeness of our approach, we conduct extensive experiments against popular services including Facebook, Foursquare, and Grindr. Our results demonstrate that, even though the aforementioned services implement various privacy-preserving techniques to protect their users, they are still vulnerable to attacks. In particular, we are able to pinpoint Facebook users within 5m of their exact location. For Foursquare and Grindr, users are pinpointed within 15m of their location in 90% of the cases, even with the strictest privacy settings enabled. Our attacks are highly efficient and complete within a few seconds. The severity of our findings was acknowledged by Facebook and Foursquare, both of which have followed our recommendations and adopted our design of a safe proximity scheme in their production systems. As the number of mobile applications offering location functionality will continue to increase, service providers and software developers must be able to assess the privacy guarantees that their services offer. To that end, we discuss viable defenses that can be currently adopted by all major services, and provide an open-source testing framework to be used by researchers and service providers who wish to evaluate the privacy-preserving properties of applications offering proximity functionality.

On the security of TLS resumption and renegotiation

The Transport Layer Security (TLS) protocol is the most important standard on the Internet for key exchange. TLS standard supports many additional handshake modes such as resumption and renegotiation besides the full handshake. The interaction and dependence of different modes may lead to some practical attacks on TLS. In 2014, Bhargavan et al. described a triple handshake attack on TLS 1.2 by exploiting the sequential running of three different modes of TLS, which can lead to a client impersonation attack after the third handshake. Subsequently, TLS 1.2 was patched with the extended master secret extension of RFC 7627 to prevent this attack. In this paper we introduce a new definition of uniqueness and present a renegotiable & resumable ACCE security model. We identify the triple handshake attack within the new model, and furthermore show TLS with the proposed fix can be proven secure in our model.

Structural Data De-Anonymization: Theory and Practice

In this paper, we study the quantification, practice, and implications of structural data de-anonymization, including social data, mobility traces, and so on. First, we answer several open questions in structural data de-anonymization by quantifying perfect and (1 - ε)-perfect structural data de-anonymization, where ε is the error tolerated by a de-anonymization scheme. To the best of our knowledge, this is the first work on quantifying structural data de-anonymization under a general data model, which closes the gap between the structural data de-anonymization practice and theory. Second, we conduct the first large-scale study on the de-anonymizability of 26 real world structural data sets, including social networks, collaborations networks, communication networks, autonomous systems, peer-to-peer networks, and so on. We also quantitatively show the perfect and (1 - ε)-perfect de-anonymization conditions of the 26 data sets. Third, following our quantification, we present a practical attack [a novel single-phase cold start optimization-based de-anonymization (ODA) algorithm]. An experimental analysis of ODA shows that ~77.7%-83.3% of the users in Gowalla (196 591 users and 950 327 edges) and 86.9%-95.5% of the users in Google+ (4692 671 users and 90751 480 edges) are de-anonymizable in different scenarios, which implies that the structure-based de-anonymization is powerful in practice. Finally, we discuss the implications of our de-anonymization quantification and our ODA attack and provide some general suggestions for future secure data publishing.

Practical security and privacy attacks against biometric hashing using sparse recovery

Biometric hashing is a cancelable biometric verification method that has received research interest recently. This method can be considered as a two-factor authentication method which combines a personal password (or secret key) with a biometric to obtain a secure binary template which is used for authentication. We present novel practical security and privacy attacks against biometric hashing when the attacker is assumed to know the user’s password in order to quantify the additional protection due to biometrics when the password is compromised. We present four methods that can reconstruct a biometric feature and/or the image from a hash and one method which can find the closest biometric data (i.e., face image) from a database. Two of the reconstruction methods are based on 1-bit compressed sensing signal reconstruction for which the data acquisition scenario is very similar to biometric hashing. Previous literature introduced simple attack methods, but we show that we can achieve higher level of security threats using compressed sensing recovery techniques. In addition, we present privacy attacks which reconstruct a biometric image which resembles the original image. We quantify the performance of the attacks using detection error tradeoff curves and equal error rates under advanced attack scenarios. We show that conventional biometric hashing methods suffer from high security and privacy leaks under practical attacks, and we believe more advanced hash generation methods are necessary to avoid these attacks.

Practical anonymity models on protecting private weighted graphs

Identity disclosure control (IDC) on graph data has attracted increasing interest in security and database communities. Most existing work focuses on preventing identity disclosure derivable from certain structural information in unweighted graphs. In weighted graphs, when the weight of an edge implying relevance/association between its adjacency vertices is taken into account, this problem becomes more complex due to the diversity of weight-related information which may expose to many types of background knowledge attacks and hence significantly increases the time complexity for preventing privacy breaches. This paper systematically studies IDC in weighted graphs, which has no known solution to our knowledge, by employing elementary weight invariants as background knowledge. We propose a general anonymity model against weight-related attacks, and introduce a new utility metric based on spectral graph theory. Then we distinguish two types of practical breaches, namely volume and histogram attack, which the adversary has the knowledge of the sum and the set of adjacent weights for each vertex respectively. We propose an efficient method for volume anonymization, and a heuristic scheme for histogram anonymization which we show to be NP-hard. We show how to construct the graph under these anonymized properties to protect a graph from both attacks. Our approaches are effective in terms of efficiency and data utility preservation: run in near-quadratic time on graph size, and preserve a similar utility as the original graph. The performances of the algorithms have been validated by extensive experiments on both synthetic and real-world datasets.

Practical continuous-variable quantum key distribution without finite sampling bandwidth effects.

In a practical continuous-variable quantum key distribution system, finite sampling bandwidth of the employed analog-to-digital converter at the receiver's side may lead to inaccurate results of pulse peak sampling. Then, errors in the parameters estimation resulted. Subsequently, the system performance decreases and security loopholes are exposed to eavesdroppers. In this paper, we propose a novel data acquisition scheme which consists of two parts, i.e., a dynamic delay adjusting module and a statistical power feedback-control algorithm. The proposed scheme may improve dramatically the data acquisition precision of pulse peak sampling and remove the finite sampling bandwidth effects. Moreover, the optimal peak sampling position of a pulse signal can be dynamically calibrated through monitoring the change of the statistical power of the sampled data in the proposed scheme. This helps to resist against some practical attacks, such as the well-known local oscillator calibration attack.

Inference Attack on Browsing History of Twitter Users Using Public Click Analytics and Twitter Metadata

Twitter is a popular online social network service for sharing short messages (tweets) among friends. Its users frequently use URL shortening services that provide (i) a short alias of a long URL for sharing it via tweets and (ii) public click analytics of shortened URLs. The public click analytics is provided in an aggregated form to preserve the privacy of individual users. In this paper, we propose practical attack techniques inferring who clicks which shortened URLs on Twitter using the combination of public information: Twitter metadata and public click analytics. Unlike the conventional browser history stealing attacks, our attacks only demand publicly available information provided by Twitter and URL shortening services. Evaluation results show that our attack can compromise Twitter users’ privacy with high accuracy.

Vulnerability Analysis of CSP Based on Stochastic Game Theory

With the development of industrial informatization, the industrial control network has gradually become much accessible for attackers. A series of vulnerabilities will therefore be exposed, especially the vulnerability of exclusive industrial communication protocols (ICPs), which has not yet been attached with enough emphasis. In this paper, stochastic game theory is applied on the vulnerability analysis of clock synchronization protocol (CSP), one of the pivotal ICPs. The stochastic game model is built strictly according to the protocol with both Man-in-the-Middle (MIM) attack and dependability failures being taken into account. The situation of multiple attack routes is considered for depicting the practical attack scenarios, and the introduction of time aspect characterizes the success probabilities of attackers actions. The vulnerability analysis is then realized through determining the optimal strategies of attacker under different states of system, respectively.

Practical Attacks on Security and Privacy Through a Low-Cost Android Device

As adoption of smartphones and tablets increases, and budget device offerings become increasingly affordable, the vision of bringing universal connectivity to the developing world is becoming more and more viable. Nonetheless, it is important to consider the diverse use-cases for smartphones and tablets today, particularly where a user may only have access to a single connected device. In many regions, banking and other important services can be accessed from mobile connected devices, expanding the reach of these services. This paper highlights the practical risks of one such lowcost computing device, highlighting the ease with which a very recent (manufacturered September 2015) Android-based internet tablet, designed for the developing world, can be completely compromised by an attacker. The weaknesses identified allow an attacker to gain full root access and persistent malicious code execution capabilities. We consider the implications of these attacks, and the ease with which these attacks may be carried out, and highlight the difficulty in effectively mitigating these weaknesses as a user, even on a recently manufactured device.

On Known-Plaintext Attacks to a Compressed Sensing-Based Encryption: A Quantitative Analysis

Despite the linearity of its encoding, compressed sensing (CS) may be used to provide a limited form of data protection when random encoding matrices are used to produce sets of low-dimensional measurements (ciphertexts). In this paper, we quantify by theoretical means the resistance of the least complex form of this kind of encoding against known-plaintext attacks. For both standard CS with antipodal random matrices and recent multiclass encryption schemes based on it, we show how the number of candidate encoding matrices that match a typical plaintext-ciphertext pair is so large that the search for the true encoding matrix inconclusive. Such results on the practical ineffectiveness of known-plaintext attacks underlie the fact that even closely related signal recovery under encoding matrix uncertainty is doomed to fail. Practical attacks are then exemplified by applying CS with antipodal random matrices as a multiclass encryption scheme to signals such as images and electrocardiographic tracks, showing that the extracted information on the true encoding matrix from a plaintext-ciphertext pair leads to no significant signal recovery quality increase. This theoretical and empirical evidence clarifies that, although not perfectly secure, both standard CS and multiclass encryption schemes feature a noteworthy level of security against known-plaintext attacks, therefore increasing its appeal as a negligible-cost encryption method for resource-limited sensing applications.

FPGA Trojans Through Detecting and Weakening of Cryptographic Primitives

This paper investigates a novel attack vector against cryptography realized on FPGAs, which poses a serious threat to real-world applications. We demonstrate how a targeted bitstream modification can seriously weaken cryptographic algorithms, which we show with the examples of AES and 3-DES. The attack is performed by modifying the FPGA bitstream that configures the hardware elements during initialization. Recently, it has been shown that cloning of FPGA designs is feasible, even if the bitstream is encrypted. However, due to its proprietary file format, a meaningful modification is challenging. While some previous work addressed bitstream reverse-engineering, so far it has not been evaluated how difficult it is to detect and modify cryptographic elements. We outline two possible practical attacks that have serious security implications. We target the S-boxes of block ciphers that can be implemented in look-up tables or stored as precomputed set of values in the memory of the FPGA. We demonstrate that it is possible to detect and apply meaningful changes to cryptographic elements inside an unknown, proprietary, and undocumented bitstream. Our proposed attack does not require any knowledge of the internal routing. Furthermore, we show how an AES key can be revealed within seconds. Finally, we discuss countermeasures that can raise the bar for an adversary to successfully perform this kind of attack.

Mathematical Model of System of Protection of Computer Networks against Attacks DOS/DDOS

In practice the most part of connections of subjects of a wide area network uses the virtual connections as this method is the dynamic protection of network connection and won't use static key information. Therefore, the interaction without establishing a virtual channel is one of the possible reasons for the success of remote attacks such as DoS / DDoS. An abstract considers the mathematical model of system of protection of computer networks against attacks such as DoS/DDoS, allowing in practice to detect attacks such as DoS / DDoS. Grounded way to prevent attacks through the use of network reconfiguration procedures, it is difficult for practical implementation attacks such as DoS / DDoS. The algorithm to create new virtual data channels to ensure a minimum amount of traffic regardless of reconfiguring computer network. The article presents an approach to detection of the distributed network attacks to refusal in service, the offered method increases efficiency of use of the calculated resource of a computer network at the big distributed network attacks to “Denial of Service”.

On selection of samples in algebraic attacks and a new technique to find hidden low degree equations

The best way of selecting samples in algebraic attacks against block ciphers is not well explored and understood. We introduce a simple strategy for selecting the plaintexts and demonstrate its strength by breaking reduced-round KATAN32, LBlock and SIMON. For each case, we present a practical attack on reduced-round version which outperforms previous attempts of algebraic cryptanalysis whose complexities were close to exhaustive search. The attack is based on the selection of samples using cube attack and ElimLin which was presented at FSE'12, and a new technique called Universal Proning. In the case of LBlock, we break 10 out of 32 rounds. In KATAN32, we break 78 out of 254 rounds. Unlike previous attempts which break smaller number of rounds, we do not guess any bit of the key and we only use structural properties of the cipher to be able to break a higher number of rounds with much lower complexity. We show that cube attacks owe their success to the same properties and therefore can be used as a heuristic for selecting the samples in an algebraic attack. The performance of ElimLin is further enhanced by the new Universal Proning technique, which allows to discover linear equations that are not found by ElimLin.