Two-bit pattern analysis for quantitative information flow

Protecting confidential information from improper disclosure is a fundamental security goal. While encryption and access control are important tools for ensuring confidentiality, they cannot prevent an authorized system from leaking confidential information to its publicly observable outputs, whether inadvertently or maliciously. Hence, secure information flow aims to provide end-to-end control of information flow. Unfortunately, the traditionally-adopted policy of noninterference, which forbids all improper leakage, is often too restrictive. Theories of quantitative information flow address this issue by quantifying the amount of confidential information leaked by a system, with the goal of showing that it is intuitively "small" enough to be tolerated. Given such a theory, it is crucial to develop automated techniques for calculating the leakage in a system. ^ This dissertation is concerned with program analysis for calculating the maximum leakage, or capacity, of confidential information in the context of deterministic systems and under three proposed entropy measures of information leakage: Shannon entropy leakage, min-entropy leakage, and g-leakage. In this context, it turns out that calculating the maximum leakage of a program reduces to counting the number of possible outputs that it can produce. ^ The new approach introduced in this dissertation is to determine two-bit patterns, the relationships among pairs of bits in the output; for instance we might determine that two bits must be unequal. By counting the number of solutions to the two-bit patterns, we obtain an upper bound on the number of possible outputs. Hence, the maximum leakage can be bounded. We first describe a straightforward computation of the two-bit patterns using an automated prover. We then show a more efficient implementation that uses an implication graph to represent the two- bit patterns. It efficiently constructs the graph through the use of an automated prover, random executions, STP counterexamples, and deductive closure. The effectiveness of our techniques, both in terms of efficiency and accuracy, is shown through a number of case studies found in recent literature. ^

The 128-bit block cipher MARS

The purpose of the research is to investigate the emerging data security methodologies that will work with most suitable applications in the academic, industrial and commercial environments. Of several methodologies considered for Advanced Encryption Standard (AES), MARS (block cipher) developed by IBM, has been selected. Its design takes advantage of the powerful capabilities of modern computers to allow a much higher level of performance than can be obtained from less optimized algorithms such as Data Encryption Standards (DES). MARS is unique in combining virtually every design technique known to cryptographers in one algorithm. The thesis presents the performance of 128-bit cipher flexibility, which is a scaled down version of the algorithm MARS. The cryptosystem used showed equally comparable performance in speed, flexibility and security, with that of the original algorithm. The algorithm is considered to be very secure and robust and is expected to be implemented for most of the applications.

Algoritmo papílio como método de proteção de templates para aumentar a segurança em sistemas de identificação biométricos

There are authentication models which use passwords, keys, personal identifiers (cards, tags etc) to authenticate a particular user in the authentication/identification process. However, there are other systems that can use biometric data, such as signature, fingerprint, voice, etc., to authenticate an individual in a system. In another hand, the storage of biometric can bring some risks such as consistency and protection problems for these data. According to this problem, it is necessary to protect these biometric databases to ensure the integrity and reliability of the system. In this case, there are models for security/authentication biometric identification, for example, models and Fuzzy Vault and Fuzzy Commitment systems. Currently, these models are mostly used in the cases for protection of biometric data, but they have fragile elements in the protection process. Therefore, increasing the level of security of these methods through changes in the structure, or even by inserting new layers of protection is one of the goals of this thesis. In other words, this work proposes the simultaneous use of encryption (Encryption Algorithm Papilio) with protection models templates (Fuzzy Vault and Fuzzy Commitment) in identification systems based on biometric. The objective of this work is to improve two aspects in Biometric systems: safety and accuracy. Furthermore, it is necessary to maintain a reasonable level of efficiency of this data through the use of more elaborate classification structures, known as committees. Therefore, we intend to propose a model of a safer biometric identification systems for identification.

A PHR system with policy-based fine-grained access control and revocation mechanism

Collaborative sharing of information is becoming much more needed technique to achieve complex goals in today's fast-paced tech-dominant world. Personal Health Record (PHR) system has become a popular research area for sharing patients informa- tion very quickly among health professionals. PHR systems store and process sensitive information, which should have proper security mechanisms to protect patients' private data. Thus, access control mechanisms of the PHR should be well-defined. Secondly, PHRs should be stored in encrypted form. Cryptographic schemes offering a more suitable solution for enforcing access policies based on user attributes are needed for this purpose. Attribute-based encryption can resolve these problems, we propose a patient-centric framework that protects PHRs against untrusted service providers and malicious users. In this framework, we have used Ciphertext Policy Attribute Based Encryption scheme as an efficient cryptographic technique, enhancing security and privacy of the system, as well as enabling access revocation. Patients can encrypt their PHRs and store them on untrusted storage servers. They also maintain full control over access to their PHR data by assigning attribute-based access control to selected data users, and revoking unauthorized users instantly. In order to evaluate our system, we implemented CP-ABE library and web services as part of our framework. We also developed an android application based on the framework that allows users to register into the system, encrypt their PHR data and upload to the server, and at the same time authorized users can download PHR data and decrypt it. Finally, we present experimental results and performance analysis. It shows that the deployment of the proposed system would be practical and can be applied into practice.

PoisonIvy: Safe speculation for secure memory

Encryption and integrity trees guard against phys- ical attacks, but harm performance. Prior academic work has speculated around the latency of integrity verification, but has done so in an insecure manner. No industrial implementations of secure processors have included speculation. This work presents PoisonIvy, a mechanism which speculatively uses data before its integrity has been verified while preserving security and closing address-based side-channels. PoisonIvy reduces per- formance overheads from 40% to 20% for memory intensive workloads and down to 1.8%, on average.

Sharing in the Rain: Secure and Efficient Data Sharing for the Cloud

Cloud storage has rapidly become a cornerstone of many businesses and has moved from an early adopters stage to an early majority, where we typically see explosive deployments. As companies rush to join the cloud revolution, it has become vital to create the necessary tools that will effectively protect users' data from unauthorized access. Nevertheless, sharing data between multiple users' under the same domain in a secure and efficient way is not trivial. In this paper, we propose Sharing in the Rain – a protocol that allows cloud users' to securely share their data based on predefined policies. The proposed protocol is based on Attribute-Based Encryption (ABE) and allows users' to encrypt data based on certain policies and attributes. Moreover, we use a Key-Policy Attribute-Based technique through which access revocation is optimized. More precisely, we show how to securely and efficiently remove access to a file, for a certain user that is misbehaving or is no longer part of a user group, without having to decrypt and re-encrypt the original data with a new key or a new policy.

LocLess: Do You Really Care Where Your Cloud Files Are?

Physical location of data in cloud storage is a problem that gains a lot of attention not only from the actual cloud providers but also from the end users' who lately raise many concerns regarding the privacy of their data. It is a common practice that cloud service providers create replicate users' data across multiple physical locations. However, moving data in different countries means that basically the access rights are transferred based on the local laws of the corresponding country. In other words, when a cloud service provider stores users' data in a different country then the transferred data is subject to the data protection laws of the country where the servers are located. In this paper, we propose LocLess, a protocol which is based on a symmetric searchable encryption scheme for protecting users' data from unauthorized access even if the data is transferred to different locations. The idea behind LocLess is that "Once data is placed on the cloud in an unencrypted form or encrypted with a key that is known to the cloud service provider, data privacy becomes an illusion". Hence, the proposed solution is solely based on encrypting data with a key that is only known to the data owner.

Progress and Research in Cybersecurity - Supporting a resilient and trustworthy system for the UK

Executive summary
Digital systems have transformed, and will continue to transform, our world. Supportive government policy, a strong research base and a history of industrial success make the UK particularly well-placed to realise the benefits of the emerging digital society. These benefits have already been substantial, but they remain at risk. Protecting the benefits and minimising the risks requires reliable and robust cybersecurity, underpinned by a strong research and translation system.
Trust is essential for growing and maintaining participation in the digital society. Organisations earn trust by acting in a trustworthy manner: building systems that are reliable and secure, treating people, their privacy and their data with respect, and providing credible and comprehensible information to help people understand how secure they are.
Resilience, the ability to function, adapt, grow, learn and transform under stress or in the face of shocks, will help organisations deliver systems that are reliable and secure. Resilient organisations can better protect their customers, provide more useful products and services, and earn people’s trust.
Research and innovation in industry and academia will continue to make important contributions to creating this resilient and trusted digital environment. Research can illuminate how best to build, assess and improve digital systems, integrating insights from different disciplines, sectors and around the globe. It can also generate advances to help cybersecurity keep up with the continued evolution of cyber risks.
Translation of innovative ideas and approaches from research will create a strong supply of reliable, proven solutions to difficult to predict cybersecurity risks. This is best achieved by maximising the diversity and number of innovations that see the light of day as products.
Policy, practice and research will all need to adapt. The recommendations made in this report seek to set up a trustworthy, self-improving and resilient digital environment that can thrive in the face of unanticipated threats, and earn the trust people place in it.
Innovation and research will be particularly important to the UK’s economy as it establishes a new relationship with the EU. Cybersecurity delivers important economic benefits, both by underpinning the digital foundations of UK business and trade and also through innovation that feeds directly into growth. The findings of this report will be relevant regardless of how the UK’s relationship to the EU changes.
Headline recommendations
● Trust: Governments must commit to preserving the robustness of encryption, including end-to-end encryption, and promoting its widespread use. Encryption is a foundational security technology that is needed to build user trust, improve security standards and fully realise the benefits of digital systems.
● Resilience: Government should commission an independent review of the UK’s future cybersecurity needs, focused on the institutional structures needed to support resilient and trustworthy digital systems in the medium and longer term. A self-improving, resilient digital environment will need to be guided and governed by institutions that are transparent, expert and have a clear and widely-understood remit.
● Research: A step change in cybersecurity research and practice should be pursued; it will require a new approach to research, focused on identifying ambitious high-level goals and enabling excellent researchers to pursue those ambitions. This would build on the UK's existing strengths in many aspects of cybersecurity research and ultimately help build a resilient and trusted digital sector based on excellent research and world-class expertise.
● Translation: The UK should promote a free and unencumbered flow of cybersecurity ideas from research to practical use and support approaches that have public benefits beyond their short term financial return. The unanticipated nature of future cyber threats means that a diverse set of cybersecurity ideas and approaches will be needed to build resilience and adaptivity. Many of the most valuable ideas will have broad security benefits for the public, beyond any direct financial returns.

Time-Independent Discrete Gaussian Sampling for Post-Quantum Cryptography

As the development of a viable quantum computer nears, existing widely used public-key cryptosystems, such as RSA, will no longer be secure. Thus, significant effort is being invested into post-quantum cryptography (PQC). Lattice-based cryptography (LBC) is one such promising area of PQC, which offers versatile, efficient, and high performance security services. However, the vulnerabilities of these implementations against side-channel attacks (SCA) remain significantly understudied. Most, if not all, lattice-based cryptosystems require noise samples generated from a discrete Gaussian distribution, and a successful timing analysis attack can render the whole cryptosystem broken, making the discrete Gaussian sampler the most vulnerable module to SCA. This research proposes countermeasures against timing information leakage with FPGA-based designs of the CDT-based discrete Gaussian samplers with constant response time, targeting encryption and signature scheme parameters. The proposed designs are compared against the state-of-the-art and are shown to significantly outperform existing implementations. For encryption, the proposed sampler is 9x faster in comparison to the only other existing time-independent CDT sampler design. For signatures, the first time-independent CDT sampler in hardware is proposed. 

Theoretical and Quantitative Comparison of SensibleThings and GSN

This project is aimed at making comparison between current existing Internet- of-Things (IoT) platforms, SensibleThings (ST) and Global Sensors Networks (GSN). Project can be served as a further work of platforms’ investigation. Comparing and learning from each other aim to contribute to the improvement of future platforms development. Detailed comparison is mainly with the respect of platform feature, communication and data present-frequency performance under stress, and platform node scalability performance on one limited device. Study is conducted through developing applications on each platform, and making measuring performance under the same condition in household network environment. So far, all these respects have had results and been concluded. Qualitatively comparing, GSN performs better in the facets of node’s swift development and deployment, data management, node subscription and connection retry mechanism. Whereas, ST is superior in respects of network package encryption, platform reliability, session initializing latency, and degree of developing freedom. In quantitative comparison, nodes on GSN has better data push pressure resistence while ST nodes works with lower session latency. In terms of data present-frequency, ST node can reach higher updating frequency than GSN node. In the aspect of node sclability on one limited device, ST nodes take the advantage in averagely lower latency than GSN node when nodes number is less than 15 on limited device. But due to sharing mechanism of GSN, on one limited device, it's nodes shows more scalable if platform nodes have similar job.

Security through Obscurity: Layout Obfuscation of Digital Integrated Circuits using Don't Care Conditions

Contemporary integrated circuits are designed and manufactured in a globalized environment leading to concerns of piracy, overproduction and counterfeiting. One class of techniques to combat these threats is circuit obfuscation which seeks to modify the gate-level (or structural) description of a circuit without affecting its functionality in order to increase the complexity and cost of reverse engineering. Most of the existing circuit obfuscation methods are based on the insertion of additional logic (called “key gates”) or camouflaging existing gates in order to make it difficult for a malicious user to get the complete layout information without extensive computations to determine key-gate values. However, when the netlist or the circuit layout, although camouflaged, is available to the attacker, he/she can use advanced logic analysis and circuit simulation tools and Boolean SAT solvers to reveal the unknown gate-level information without exhaustively trying all the input vectors, thus bringing down the complexity of reverse engineering. To counter this problem, some ‘provably secure’ logic encryption algorithms that emphasize methodical selection of camouflaged gates have been proposed previously in literature [1,2,3]. The contribution of this paper is the creation and simulation of a new layout obfuscation method that uses don't care conditions. We also present proof-of-concept of a new functional or logic obfuscation technique that not only conceals, but modifies the circuit functionality in addition to the gate-level description, and can be implemented automatically during the design process. Our layout obfuscation technique utilizes don’t care conditions (namely, Observability and Satisfiability Don’t Cares) inherent in the circuit to camouflage selected gates and modify sub-circuit functionality while meeting the overall circuit specification. Here, camouflaging or obfuscating a gate means replacing the candidate gate by a 4X1 Multiplexer which can be configured to perform all possible 2-input/ 1-output functions as proposed by Bao et al. [4]. It is important to emphasize that our approach not only obfuscates but alters sub-circuit level functionality in an attempt to make IP piracy difficult. The choice of gates to obfuscate determines the effort required to reverse engineer or brute force the design. As such, we propose a method of camouflaged gate selection based on the intersection of output logic cones. By choosing these candidate gates methodically, the complexity of reverse engineering can be made exponential, thus making it computationally very expensive to determine the true circuit functionality. We propose several heuristic algorithms to maximize the RE complexity based on don’t care based obfuscation and methodical gate selection. Thus, the goal of protecting the design IP from malicious end-users is achieved. It also makes it significantly harder for rogue elements in the supply chain to use, copy or replicate the same design with a different logic. We analyze the reverse engineering complexity by applying our obfuscation algorithm on ISCAS-85 benchmarks. Our experimental results indicate that significant reverse engineering complexity can be achieved at minimal design overhead (average area overhead for the proposed layout obfuscation methods is 5.51% and average delay overhead is about 7.732%). We discuss the strengths and limitations of our approach and suggest directions that may lead to improved logic encryption algorithms in the future. References: [1] R. Chakraborty and S. Bhunia, “HARPOON: An Obfuscation-Based SoC Design Methodology for Hardware Protection,” IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, vol. 28, no. 10, pp. 1493–1502, 2009. [2] J. A. Roy, F. Koushanfar, and I. L. Markov, “EPIC: Ending Piracy of Integrated Circuits,” in 2008 Design, Automation and Test in Europe, 2008, pp. 1069–1074. [3] J. Rajendran, M. Sam, O. Sinanoglu, and R. Karri, “Security Analysis of Integrated Circuit Camouflaging,” ACM Conference on Computer Communications and Security, 2013. [4] Bao Liu, Wang, B., "Embedded reconfigurable logic for ASIC design obfuscation against supply chain attacks,"Design, Automation and Test in Europe Conference and Exhibition (DATE), 2014 , vol., no., pp.1,6, 24-28 March 2014.

Bitcoin mining is about to become a lot less profitable.

Imagine being told that your wage was going to be cut in half. Well, that’s what’s soon going to happen to those who make money from Bitcoin mining, the process of earning the online currency Bitcoin. The current expected date for this change is 11 July 2016. Many see this as the day when Bitcoin prices will rocket and when Bitcoin owners could make a great deal of money. Others see it as the start of a Bitcoin crash. At present no one quite knows which way it will go. Bitcoin was created in 2009 by someone known as Satoshi Nakamoto, borrowing from a whole lot of research methods. It is a cryptocurrency, meaning it uses digital encryption techniques to create bitcoins and secure financial transactions. It doesn’t need a central government or organisation to regulate it, nor a broker to manage payments. Conventional currencies usually have a central bank that creates money and controls its supply. Bitcoin is instead created when individuals “mine” for it by using their computers to perform complex calculations through special software. The algorithm behind Bitcoin is designed to limit the number of bitcoins that can ever be created. All Bitcoin transactions are recorded on a public database known as a blockchain. Every time someone mines for Bitcoin, it is recorded with a new block that is transmitted to every Bitcoin app across the network, like a bank updating its online records.

Preventing encrypted traffic analysis

Many existing encrypted Internet protocols leak information through packet sizes and timing. Though seemingly innocuous, prior work has shown that such leakage can be used to recover part or all of the plaintext being encrypted. The prevalence of encrypted protocols as the underpinning of such critical services as e-commerce, remote login, and anonymity networks and the increasing feasibility of attacks on these services represent a considerable risk to communications security. Existing mechanisms for preventing traffic analysis focus on re-routing and padding. These prevention techniques have considerable resource and overhead requirements. Furthermore, padding is easily detectable and, in some cases, can introduce its own vulnerabilities. To address these shortcomings, we propose embedding real traffic in synthetically generated encrypted cover traffic. Novel to our approach is our use of realistic network protocol behavior models to generate cover traffic. The observable traffic we generate also has the benefit of being indistinguishable from other real encrypted traffic further thwarting an adversary's ability to target attacks. In this dissertation, we introduce the design of a proxy system called TrafficMimic that implements realistic cover traffic tunneling and can be used alone or integrated with the Tor anonymity system. We describe the cover traffic generation process including the subtleties of implementing a secure traffic generator. We show that TrafficMimic cover traffic can fool a complex protocol classification attack with 91% of the accuracy of real traffic. TrafficMimic cover traffic is also not detected by a binary classification attack specifically designed to detect TrafficMimic. We evaluate the performance of tunneling with independent cover traffic models and find that they are comparable, and, in some cases, more efficient than generic constant-rate defenses. We then use simulation and analytic modeling to understand the performance of cover traffic tunneling more deeply. We find that we can take measurements from real or simulated traffic with no tunneling and use them to estimate parameters for an accurate analytic model of the performance impact of cover traffic tunneling. Once validated, we use this model to better understand how delay, bandwidth, tunnel slowdown, and stability affect cover traffic tunneling. Finally, we take the insights from our simulation study and develop several biasing techniques that we can use to match the cover traffic to the real traffic while simultaneously bounding external information leakage. We study these bias methods using simulation and evaluate their security using a Bayesian inference attack. We find that we can safely improve performance with biasing while preventing both traffic analysis and defense detection attacks. We then apply these biasing methods to the real TrafficMimic implementation and evaluate it on the Internet. We find that biasing can provide 3-5x improvement in bandwidth for bulk transfers and 2.5-9.5x speedup for Web browsing over tunneling without biasing.

Uma API criptográfica para aplicações embarcadas

This document presents GEmSysC, an unified cryptographic API for embedded systems. Software layers implementing this API can be built over existing libraries, allowing embedded software to access cryptographic functions in a consistent way that does not depend on the underlying library. The API complies to good practices for API design and good practices for embedded software development and took its inspiration from other cryptographic libraries and standards. The main inspiration for creating GEmSysC was the CMSIS-RTOS standard, which defines an unified API for embedded software in an implementation-independent way, but targets operating systems instead of cryptographic functions. GEmSysC is made of a generic core and attachable modules, one for each cryptographic algorithm. This document contains the specification of the core of GEmSysC and three of its modules: AES, RSA and SHA-256. GEmSysC was built targeting embedded systems, but this does not restrict its use only in such systems – after all, embedded systems are just very limited computing devices. As a proof of concept, two implementations of GEmSysC were made. One of them was built over wolfSSL, which is an open source library for embedded systems. The other was built over OpenSSL, which is open source and a de facto standard. Unlike wolfSSL, OpenSSL does not specifically target embedded systems. The implementation built over wolfSSL was evaluated in a Cortex- M3 processor with no operating system while the implementation built over OpenSSL was evaluated on a personal computer with Windows 10 operating system. This document displays test results showing GEmSysC to be simpler than other libraries in some aspects. These results have shown that both implementations incur in little overhead in computation time compared to the cryptographic libraries themselves. The overhead of the implementation has been measured for each cryptographic algorithm and is between around 0% and 0.17% for the implementation over wolfSSL and between 0.03% and 1.40% for the one over OpenSSL. This document also presents the memory costs for each implementation.

Enabling fine-grained multi-keyword search supporting classified sub-dictionaries over encrypted cloud data

Using cloud computing, individuals can store their data on remote servers and allow data access to public users through the cloud servers. As the outsourced data are likely to contain sensitive privacy information, they are typically encrypted before uploaded to the cloud. This, however, significantly limits the usability of outsourced data due to the difficulty of searching over the encrypted data. In this paper, we address this issue by developing the fine-grained multi-keyword search schemes over encrypted cloud data. Our original contributions are three-fold. First, we introduce the relevance scores and preference factors upon keywords which enable the precise keyword search and personalized user experience. Second, we develop a practical and very efficient multi-keyword search scheme. The proposed scheme can support complicated logic search the mixed “AND”, “OR” and “NO” operations of keywords. Third, we further employ the classified sub-dictionaries technique to achieve better efficiency on index building, trapdoor generating and query. Lastly, we analyze the security of the proposed schemes in terms of confidentiality of documents, privacy protection of index and trapdoor, and unlinkability of trapdoor. Through extensive experiments using the real-world dataset, we validate the performance of the proposed schemes. Both the security analysis and experimental results demonstrate that the proposed schemes can achieve the same security level comparing to the existing ones and better performance in terms of functionality, query complexity and efficiency.