Biblio

Extortion using digital platforms is an increasing form of crime. A commonly seen problem is extortion in the form of an infection of a Crypto Ransomware that encrypts the files of the target and demands a ransom to recover the locked data. By analyzing the four most common Crypto Ransomwares, at writing, a clear vulnerability is identified; all infections rely on tools available on the target system to be able to prevent a simple recovery after the attack has been detected. By renaming the system tool that handles shadow copies it is possible to recover from infections from all four of the most common Crypto Ransomwares. The solution is packaged in a single, easy to use script.

Safety applications are currently being developed in next generation vehicular networks to provide road safety. Broadcasting of safety messages unveils the need of reliability assessment since there are no request-to-send (RTS)/clear-to-send (CTS) handshaking and acknowledgment packets in broadcast vehicular communications. Therefore, the reliability of broadcast messages suffer from hidden terminal problem, interference and high mobility. To overcome these challenges, Signal-to-Interference-and-Noise Ratio (SINR) estimation is a key solution so that we can foresee the transmission collisions caused by hidden terminals and prevent its transmissions. Then, we can build a model to improve reliability of broadcast messages. Towards this aim, in this paper, we propose a SINR based hidden terminal estimation model. First, we introduce a method to specify hidden terminals and their transmissions, then we estimate accurate SINR level at the receiver in the near future. Second, we formulate the successfully received packets with a heuristic algorithm and, calculate throughput and hidden terminal radius. Our approach enables significant improvement in the reliability of broadcast vehicular communications.

Different applications concurrently running on modern MPSoCs can interfere with each other when they use shared resources. This interference can cause side channels, i.e., sources of unintended information flow between applications. To prevent such side channels, we propose a hybrid mapping methodology that attempts to ensure spatial isolation, i.e., a mutually-exclusive allocation of resources to applications in the MPSoC. At design time and as a first step, we compute compact and connected application mappings (called shapes). In a second step, run-time management uses this information to map multiple spatially segregated shapes to the architecture. We present and evaluate a (fast) heuristic and an (exact) SAT-based mapper, demonstrating the viability of the approach.

This tutorial will introduce participants to Grounded Theory, which is a qualitative framework to discover new theory from an empirical analysis of data. This form of analysis is particularly useful when analyzing text, audio or video artifacts that lack structure, but contain rich descriptions. We will frame Grounded Theory in the context of qualitative methods and case studies, which complement quantitative methods, such as controlled experiments and simulations. We will contrast the approaches developed by Glaser and Strauss, and introduce coding theory - the most prominent qualitative method for performing analysis to discover Grounded Theory. Topics include coding frames, first- and second-cycle coding, and saturation. We will use examples from security interview scripts to teach participants: developing a coding frame, coding a source document to discover relationships in the data, developing heuristics to resolve ambiguities between codes, and performing second-cycle coding to discover relationships within categories. Then, participants will learn how to discover theory from coded data. Participants will further learn about inter-rater reliability statistics, including Cohen's and Fleiss' Kappa, Krippendorf's Alpha, and Vanbelle's Index. Finally, we will review how to present Grounded Theory results in publications, including how to describe the methodology, report observations, and describe threats to validity.

Security-constrained optimal power flow (SCOPF) studies are used for assessing network performance during both planning and operational stages. The requirements for increased flexibility and improved security necessitate to use robust and computationally efficient SCOPF methods, which are crucial for "smart grid" applications requiring (close to) real-time network control. Conventional SCOPF methods solve the corresponding nonlinear power flow equations using gradient-based iterative approaches and are computationally efficient, but sensitive to selection of initial values and might suffer from convergence problems. Metaheuristic SCOPF methods are based on various approaches that search over the system state space and do not suffer from convergence problems, but are more computationally demanding. While network planners and operators regularly use conventional SCOPF methods, meta-heuristic methods are rarely implemented in practice, even for off-line analysis during the planning stage. Using as an example the IEEE 30-bus test network, this paper analyses and compares conventional and meta-heuristic methods for security-constrained OPF studies, showing that meta-heuristic methods can be used when conventional methods fail to converge and/or to provide a global optimum solution.

We conducted a series of in-depth focus groups wherein users provided rationales for their own online privacy behaviors. Our data suggest that individuals often take action with little thought or evaluation, even showing surprise when confronted with their own behaviors. Our analysis yielded a battery of cognitive heuristics, i.e., mental shortcuts / rules of thumb, that users seem to employ when they disclose or withhold information at the spur of the moment. A total of 4 positive heuristics (promoting disclosure) and 4 negative heuristics (inhibiting disclosure) were discovered. An understanding of these heuristics can be valuable for designing interfaces that promote secure and trustworthy computing.

Today many design houses must outsource their design fabrication to a third party which is often an overseas foundry. Split-fabrication is proposed for combining the FEOL capabilities of an advanced but untrusted foundry with the BEOL capabilities of a trusted foundry. Hardware security in this business model relates directly to the front-end foundry's ability to interpret the partial circuit design it receives in order to reverse engineer or insert malicious circuits. The published experimental results indicate that a relatively large percentage of the split nets can be correctly guessed and there is no easy way of detecting the possibly inserted Trojans. In this paper, we propose a secure split-fabrication design methodology for the Vertical Slit Field Effect Transistor (VeSFET) based integrated circuits. We take advantage of the VeSFET's unique and powerful two-side accessibility and monolithic 3D integration capability. In our approach the design is manufactured by two independent foundries, both of which can be untrusted. We propose the design partition and piracy prevention, hardware Trojan insertion prevention, and Trojan detection methods. In the 3D designs, some transistors are physically hidden from the front-end foundry\_1's view, which causes that it is impossible for this foundry to reconstruct the circuit. We designed 10 MCNC benchmark circuits using the proposed flow and executed an attack by an in-house developed proximity attacker. With 5% nets manufactured by the back-end foundry\_2, the average percentage of the correctly reconstructed partitioned nets is less than 1%.

3D die stacking and 2.5D interposer design are promising technologies to improve integration density, performance and cost. Current approaches face serious issues in dealing with emerging security challenges such as side channel attacks, hardware trojans, secure IC manufacturing and IP piracy. By utilizing intrinsic characteristics of 2.5D and 3D technologies, we propose novel opportunities in designing secure systems. We present: (i) a 3D architecture for shielding side-channel information; (ii) split fabrication using active interposers; (iii) circuit camouflage on monolithic 3D IC, and (iv) 3D IC-based security processing-in-memory (PIM). Advantages and challenges of these designs are discussed, showing that the new designs can improve existing countermeasures against security threats and further provide new security features.

Hardware Trojan detection has emerged as a critical challenge to ensure security and trustworthiness of integrated circuits. A vast majority of research efforts in this area has utilized side-channel analysis for Trojan detection. Functional test generation for logic testing is a promising alternative but it may not be helpful if a Trojan cannot be fully activated or the Trojan effect cannot be propagated to the observable outputs. Side-channel analysis, on the other hand, can achieve significantly higher detection coverage for Trojans of all types/sizes, since it does not require activation/propagation of an unknown Trojan. However, they have often limited effectiveness due to poor detection sensitivity under large process variations and small Trojan footprint in side-channel signature. In this paper, we address this critical problem through a novel side-channel-aware test generation approach, based on a concept of Multiple Excitation of Rare Switching (MERS), that can significantly increase Trojan detection sensitivity. The paper makes several important contributions: i) it presents in detail the statistical test generation method, which can generate high-quality testset for creating high relative activity in arbitrary Trojan instances; ii) it analyzes the effectiveness of generated testset in terms of Trojan coverage; and iii) it describes two judicious reordering methods can further tune the testset and greatly improve the side channel sensitivity. Simulation results demonstrate that the tests generated by MERS can significantly increase the Trojans sensitivity, thereby making Trojan detection effective using side-channel analysis.

The rapid growth of Internet-of-things and other electronic devices make a huge impact on how and where data travel. The confidential data (e.g., personal data, financial information) that travel through unreliable channels can be exposed to attackers. In hardware, the confidential data such as secret cipher keys are facing the same issue. This problem is even more serious when the IP is from a 3rd party and contains scan-chains. Thus, data flow tracking is important to analyze possible leakage channels in fighting against such hardware security threats. This paper introduces a method for tracking data flow and detecting potential hardware Trojans in gate-level soft IPs using assets and Structural Checking tool.

A hardware Trojan (HT) detection method is presented that is based on measuring and detecting small systematic changes in path delays introduced by capacitive loading effects or series inserted gates of HTs. The path delays are measured using a high resolution on-chip embedded test structure called a time-to-digital converter (TDC) that provides approx. 25 ps of timing resolution. A calibration method for the TDC as well as a chip-averaging technique are demonstrated to nearly eliminate chip-to-chip and within-die process variation effects on the measured path delays across chips. This approach significantly improves the correlation between Trojan-free chips and a simulation-based golden model. Path delay tests are applied to multiple copies of a 90nm custom ASIC chip having two copies of an AES macro. The AES macros are exact replicas except for the insertion of several additional gates in the second hardware copy, which are designed to model HTs. Simple statistical detection methods are used to isolate and detect systematic changes introduced by these additional gates. We present hardware results which demonstrate that our proposed chip-averaging and calibration techniques in combination with a single nominal simulation model can be used to detect small delay anomalies introduced by the inserted gates of hardware Trojans.

The threat of inserting malicious logic in hardware design is increasing as the digital supply chains are becoming more deep and span the whole globe. Ring oscillators (ROs) can be used to detect deviations of circuit operations due to changes of its layout caused by the insertion of a hardware Trojan horse (Trojan). The placement and the length of the ring oscillator are two important parameters that define an RO sensitivity and capability to detect malicious alternations. We propose and study the use of ring oscillators with variable lengths, configurable at the runtime. Such oscillators push further the envelope for the attackers, as their design must be undetectable by all supported lengths. We study the efficiency of our proposal on defending against a family of hardware Trojans against an implementation of the AES cryptographic algorithm on an FPGA.

This work presents a new class of Covert Hardware Trojan Horses (Covert HTHs), which can be algorithmically implanted with no change to their host circuit's functional behavior and without the need for additional unrelated logic. As a result, Covert HTHs are invulnerable to functional detection methods. This work also proposes a formal methodology for implantation of Covert HTHs, which allows covert hardware to be embedded in any sufficiently-sized synchronous circuit. Synthesis results indicate that covert implantation results in nearly a 75% reduction in integrated circuit area used by the HTH. Furthermore, the covert implantation causes no increase in the host circuit's delay and, compared to the effect of an overtly implanted HTH on its host, the covert implantation results in a significantly lower dynamic and leakage power. These significant reductions in area, delay and power make a covertly implanted HTH highly resistant to existing non-functional detection methods.

We show how to securely obfuscate conjunctions, which are functions f(x1,...,xn) = ∧i∈I yi where I ⊆ [n] and each literal yi is either just xi or ¬ xi e.g., f(xi,...,x\_n) = xi ⊆ ¬ x3 ⊆ ¬ x7 ... ⊆ x\\textbackslashvphantom\n-1. Whereas prior work of Brakerski and Rothblum (CRYPTO 2013) showed how to achieve this using a non-standard object called cryptographic multilinear maps, our scheme is based on an "entropic" variant of the Ring Learning with Errors (Ring LWE) assumption. As our core tool, we prove that hardness assumptions on the recent multilinear map construction of Gentry, Gorbunov and Halevi (TCC 2015) can be established based on entropic Ring LWE. We view this as a first step towards proving the security of additional mutlilinear map based constructions, and in particular program obfuscators, under standard assumptions. Our scheme satisfies virtual black box (VBB) security, meaning that the obfuscated program reveals nothing more than black-box access to f as an oracle, at least as long as (essentially) the conjunction is chosen from a distribution having sufficient entropy.

Anonymous Identity-Based Broadcast Encryption (AIBBE) allows a sender to broadcast a ciphertext to multi-receivers, and keeps receivers' anonymity. The existing AIBBE schemes fail to achieve efficient decryption or strong security, like the constant decryption complexity, the security under the adaptive attack, or the security in the standard model. Hence, we propose two new AIBBE schemes to overcome the drawbacks of previous schemes in the state-of-art. The biggest contribution in our work is the proposed AIBBE scheme with constant decryption complexity and the provable security under the adaptive attack in the standard model. This scheme should be the first one to obtain advantages in all above mentioned aspects, and has sufficient contribution in theory due to its strong security. We also propose another AIBBE scheme in the Random Oracle (RO) model, which is of sufficient interest in practice due to our experiment.

In the emerging Internet of Things, lightweight public-key cryptography is an essential component for many cost-efficient security solutions. Since conventional public-key schemes, such as ECC and RSA, remain expensive and energy hungry even after aggressive optimization, this work investigates a possible alternative. In particular, we show the practical potential of replacing the Gaussian noise distribution in the Ring-LWE based encryption scheme by Lindner and Peikert/Lyubashevsky et al. with a binary distribution. When parameters are carefully chosen, our construction is resistant against any state-of-the-art cryptanalytic techniques (e.g., attacks on original Ring-LWE or NTRU) and suitable for low-cost scenarios. In the end, our scheme can enable public-key encryption even on very small and low-cost 8-bit (ATXmega128) and 32-bit (Cortex-M0) microcontrollers.

In this paper, we present the notion of recipient-revocable identity-based broadcast encryption scheme. In this notion, a content provider will produce encrypted content and send them to a third party (which is a broadcaster). This third party will be able to revoke some identities from the ciphertext. We present a security model to capture these requirements, as well as a concrete construction. The ciphertext consists of k+3 group elements, assuming that the maximum number of revocation identities is k. That is, the ciphertext size is linear in the maximal size of R, where R is the revocation identity set. However, we say that the additional elements compared to that from an IBBE scheme are only for the revocation but not for decryption. Therefore, the ciphertext sent to the users for decryption will be of constant size (i.e.,3 group elements). Finally, we present the proof of security of our construction.

In this paper, we propose a hierarchical identity-based encryption (HIBE) scheme in the random oracle (RO) model based on the learning with rounding (LWR) problem over small modulus \$q\$. Compared with the previous HIBE schemes based on the learning with errors (LWE) problem, the ciphertext expansion ratio of our scheme can be decreased to 1/2. Then, we utilize the HIBE scheme to construct a deterministic hierarchical identity-based encryption (D-HIBE) scheme based on the LWR problem over small modulus. Finally, with the technique of binary tree encryption (BTE) we can construct HIBE and D-HIBE schemes in the standard model based on the LWR problem over small modulus.

Proxy Re-Encryption (PRE) is a favorable primitive to realize a cryptographic cloud with secure and flexible data sharing mechanism. A number of PRE schemes with versatile capabilities have been proposed for different applications. The secure data sharing can be internally achieved in each PRE scheme. But no previous work can guarantee the secure data sharing among different PRE schemes in a general manner. Moreover, it is challenging to solve this problem due to huge differences among the existing PRE schemes in their algebraic systems and public-key types. To solve this problem more generally, this paper uniforms the definitions of the existing PRE and Public Key Encryption (PKE) schemes, and further uniforms their security definitions. Then taking any uniformly defined PRE scheme and any uniformly defined PKE scheme as two building blocks, this paper constructs a Generally Hybrid Proxy Re-Encryption (GHPRE) scheme with the idea of temporary public and private keys to achieve secure data sharing between these two underlying schemes. Since PKE is a more general definition than PRE, the proposed GHPRE scheme also is workable between any two PRE schemes. Moreover, the proposed GHPRE scheme can be transparently deployed even if the underlying PRE schemes are implementing.

With the emerging Science and Technology, network security has become a major concern. Researchers have proposed new theories and applications to eradicate the unethical access to the secret message. This paper presents a new algorithm on Symmetric Key Cryptography. The algorithm comprises of a bitwise shifting operation, folding logic along with simple mathematical operations. The fundamental security of the algorithm lies in the dual-layered encryption and decryption processes which divide the entire method into various phases. The algorithm implements a ciphered array key which itself hides the actual secret key to increase the integrity of the cryptosystem. The algorithm has been experimentally tested and the test results are promising.

The development of variable software, in general, and feature models, in particular, is an error-prone and time-consuming task. It gets increasingly more challenging with industrial-size models containing hundreds or thousands of features and constraints. Each change may lead to anomalies in the feature model such as making some features impossible to select. While the detection of anomalies is well-researched, giving explanations is still a challenge. Explanations must be as accurate and understandable as possible to support the developer in repairing the source of an error. We propose an efficient and generic algorithm for explaining different anomalies in feature models. Additionally, we achieve a benefit for the developer by computing short explanations expressed in a user-friendly manner and by emphasizing specific parts in explanations that are more likely to be the cause of an anomaly. We provide an open-source implementation in FeatureIDE and show its scalability for industrial-size feature models.

Active Cyber Defense (ACD) reconfigures cyber systems (networks and hosts) in timely manner in order to automatically respond to cyber incidents and mitigate potential risks or attacks. However, to launch a successful cyber defense, ACD strategies need to be proven effective in neutralizing the threats and enforceable under the current state and capabilities of the network. In this paper, we present a bounded model checking framework based on SMT to verify that the network can support the given ACD strategies accurately and safely without jeopardizing cyber mission invariants. We abstract the ACD strategies as sets of serializable reconfigurations and provide user interfaces to define cyber mission invariants as reachability, security, and QoS properties. We then verify the satisfaction of these invariants under the given strategies. We implemented this system on OpenFlow-based Software Defined Networks and we evaluated the time complexity for verifying ACD strategies on OpenFlow networks of over two thousand nodes and thousands of rules.

It is standard practice in enterprises to analyze large amounts of logs to detect software failures and malicious behaviors. Mobile applications pose a major challenge to centralized monitoring as network and storage limitations prevent fine-grained logs to be stored and transferred for off-line analysis. In this paper we introduce EMMA, a framework for automatic anomaly detection that enables security analysis as well as in-the-field quality assurance for enterprise mobile applications, and incurs minimal overhead for data exchange with a back-end monitoring platform. EMMA instruments binary applications with a lightweight anomaly-detection layer that reveals failures and security threats directly on mobile devices, thus enabling corrective measures to be taken promptly even when the device is disconnected. In our empirical evaluation, EMMA detected failures in unmodified Android mobile applications.

As Industries and Data Center plan to implement Software Defined Networking (SDN), the main concern is the anxiety about security. The Industries and Data Centers are curious to know how a SDN product will support them that their data, supporting applications and built in infrastructure are not vulnerable to threats. The initiation of SDN, will demand new pathways for securing control plane traffic. The traditional networks usually trust switching intelligence to implement various defense mechanisms besides known attacks. Many attacks which distress traditional networks also affect SDNs, partially due to SDN architecture complexities and most prominent among them is DoS. This paper identifies the pathways of threats to SDN systems and discuss methods to ways to mitigate them.

The threat from insiders is an ever-growing concern for organisations, and in recent years the harm that insiders pose has been widely demonstrated. This paper describes our recent work into how we might support insider threat detection when actions are taken which can be immediately determined as of concern because they fall into one of two categories: they violate a policy which is specifically crafted to describe behaviours that are highly likely to be of concern if they are exhibited, or they exhibit behaviours which follow a pattern of a known insider threat attack. In particular, we view these concerning actions as something that we can design and implement tripwires within a system to detect. We then orchestrate these tripwires in conjunction with an anomaly detection system and present an approach to formalising tripwires of both categories. Our intention being that by having a single framework for describing them, alongside a library of existing tripwires in use, we can provide the community of practitioners and researchers with the basis to document and evolve this common understanding of tripwires.