Biblio

Differential Power Analysis (DPA) attacks were shown to be effective in recovering the secret key information from a variety cryptographic systems. In response, several design methods, ranging from the cell level to the algorithmic level, have been proposed to defend against DPA attacks. Cell level solutions depend on DPA resistant cell designs which attempt to minimize power variance during transitions while minimizing area and power consumption. In this paper, we discuss how a differential circuit design style is incorporated into a COTS tool set, resulting in a fully automated synthesis system DPA resistant integrated circuits. Based on the Secure Differential Multiplexer Logic (SDMLp), this system can be used to synthesize complete cryptographic processors which provide strong defense against DPA while minimizing area and power overhead. We discuss how both combinational and sequential cells are incorporated in the cell library. We show the effectiveness of the tool chain by using it to automatically synthesize the layouts, from RT level Verilog specifications, of both the DES and AES encryption ICs in 90nm CMOS. In each case, we present experimental data to demonstrate DPA attack resistance and area, power and performance overhead and compare these with circuits synthesized in another differential logic called MDPL as well as standard CMOS synthesis results.

Nowadays, multimedia content retrieval has become the major service requirement of the Internet and the traffic of these contents has dominated the IP traffic. To reduce the duplicated traffic and improve the performance of distributing massive volumes of multimedia contents, in-network caching has been proposed recently. However, because in-network content caching can be directly utilized to respond users' requests, multimedia content retrieval is beyond content providers' control and makes it hard for them to implement access control and service accounting. In this paper, we propose an attribute-based accountable access control scheme for multimedia content distribution while making the best of in-network caching, in which content providers can be fully offline. In our scheme, the attribute-based encryption at multimedia content provider side and access policy based authentication at the edge router side jointly ensure the secure access control, which is also efficient in both space and time. Besides, secure service accounting is implemented by letting edge routers collect service credentials generated during users' request process. Through the informal security analysis, we prove the security of our scheme. Simulation results demonstrate that our scheme is efficient with acceptable overhead.

IoT middleware is an additional layer between IoT devices and the cloud applications that reduces computation and data handling on the cloud. In a typical IoT system model, middleware primarily connects to different IoT devices via IoT gateway. Device data stored on middleware is sensitive and private to a user. Middleware must have built-in mechanisms to address these issues, as well as the implementation of user authentication and access control. This paper presents the current methods used for access control on middleware and introduces Attribute-based encryption (ABE) on middleware for access control. ABE combines access control with data encryption for ensuring the integrity of data. In this paper, we propose Ciphertext-policy attribute-based encryption, abbreviated CP-ABE scheme on the middleware layer in the IoT system architecture for user access control. The proposed scheme is aimed to provide security and efficiency while reducing complexity on middleware. We have used the AVISPA tool to strengthen the proposed scheme.

The Internet of Things (IoT) relies on sensor devices to measure real-world phenomena in order to provide IoT services. The sensor readings are shared with multiple entities, such as IoT services, other IoT devices or other third parties. The collected data may be sensitive and include personal information. To protect the privacy of the users, the data needs to be protected through an encryption algorithm. For sharing cryptographic cipher-texts with a group of users Attribute-Based Encryption (ABE) is well suited, as it does not require to create group keys. However, the creation of ABE cipher-texts is slow when executed on resource constraint devices, such as IoT sensors. In this paper, we present a modification of an ABE scheme, which not only allows to encrypt data efficiently using ABE but also reduces the size of the cipher-text, that must be transmitted by the sensor. We also show how our modification can be used to realise an instantaneous key revocation mechanism.

Motivated by the complexity of cryptographic proofs, we propose methods to automate the construction and verification of cryptographic proofs in the standard model. Proofs in the standard model (as opposed to the random oracle model) are the gold standard of cryptographic proofs, and most cryptographic protocols strive to achieve them. The burgeoning complexity of cryptographic proofs implies that such proofs are prone to errors, and are hard to write, much less verify. In this paper, we propose techniques to generate automated proofs for attribute-based encryption schemes in the standard model, building upon a prototype tool, AutoG&P due to Barthe et al. In doing so, we significantly expand the scope of AutoG&P to support a rich set of data types such as multi-dimensional arrays, and constructs commonly used in cryptographic protocols such as monotone-access structures, and linear secret-sharing schemes. We also provide support for a extended class of pairing-based assumptions. We demonstrate the usefulness of our extensions by giving automated proofs of the Lewko et al. attribute-based encryption scheme, and the Waters' ciphertext-policy attribute-based encryption scheme.

The Internet of Things (IoT) is enabling a new generation of innovative services based on the seamless integration of smart objects into information systems. Such IoT devices generate an uninterrupted flow of information that can be transmitted through an untrusted network and stored on an untrusted infrastructure. The latter raises new security and privacy challenges that require novel cryptographic methods. Attribute-Based Encryption (ABE) is a new type of public-key encryption that enforces a fine-grained access control on encrypted data based on flexible access policies. The feasibility of ABE adoption in fully-fledged computing systems, i.e. smartphones or embedded systems, has been demonstrated in recent works. In this paper we assess the feasibility of the adoption of ABE in typical IoT constrained devices, characterized by limited capabilities in terms of computing, storage and power. Specifically, an implementation of three ABE schemes for ESP32, a low-cost popular platform to deploy IoT devices, is developed and evaluated in terms of encryption/decryption time and energy consumption. The performance evaluation shows that the adoption of ABE on constrained devices is feasible, although it has a cost that increases with the number of attributes. The analysis in particular highlights how ABE has a significant impact in the lifetime of battery-powered devices, which is impaired significantly when a high number of attributes is adopted.

The Internet of Things (IoT) is a technological vision in which constrained or embedded devices connect together through the Internet. This enables common objects to be empowered with communication and cooperation capabilities. Industry can take an enormous advantage of IoT, leading to the so-called Industrial IoT. In these systems, integrity, confidentiality, and access control over data are key requirements. An emerging approach to reach confidentiality and access control is Attribute-Based Encryption (ABE), which is a technique able to enforce cryptographically an access control over data. In this paper, we propose fABElous, an ABE scheme suitable for Industrial IoT applications which aims at minimizing the overhead of encryption on communication. fABElous ensures data integrity, confidentiality, and access control, while reducing the communication overhead of 35% with respect to using ABE techniques naively.

Modern cloud applications can consist of hundreds of services with thousands of instances. In order to solve the problems of interservice interaction in this highly dynamic environment, an additional software infrastructure layer called service mesh is introduced. This layer provides a single point of interaction with the network for each service. Service mesh mechanisms are responsible for: load balancing, processing of network requests, service discovery, authentication, authorization, etc. However, the following questions arise: complex key management, fine-grained access control at the application level, confidentiality of data and many-to-many communications. It is possible to solve these problems with Attribute-based encryption (ABE) methods. This paper presents an abstract model of a service mesh and a protocol for interservice communications, which uses ABE for authorization and confidentiality of the messages.

Multi-authority attribute-based encryption (MA-ABE) is a promising technique to protect data privacy and achieve fine-grained access control in edge computing for Internet of Things (IoT). However, most of the existing MA-ABE schemes suffer from expensive computational cost in the encryption and decryption phases, which are not practical for resource constrained users in IoT. We propose a large-universe MA-CP-ABE scheme with online/offline encryption and outsourced decryption. In our scheme, most expensive encryption operations have been executed in the user's initialization phase by adding reusable ciphertext pool besides splitting the encryption algorithm to online encryption and offline encryption. Moreover, massive decryption operation are outsourced to the near edge server for reducing the computation overhead of decryption. The proposed scheme is proven statically secure under the q-DPBDHE2 assumption. The performance analysis results indicate that the proposed scheme is efficient and suitable for resource-constrained users in edge computing for IoT.

Decentralized attestation methods for blockchains are currently being discussed and standardized for use cases such as certification, identity and existence proofs. In a blockchain-based attestation, a claim made about the existence of information can be cryptographically verified publicly and transparently. In this paper we explore the attestation of models through globally unique identifiers as a first step towards decentralized applications based on models. As a proof-of-concept we describe a prototypical implementation of a software connector for the ADOxx metamodeling platform. The connector allows for (a.) the creation of claims bound to the identity of an Ethereum account and (b.) their verification on the blockchain by anyone at a later point in time. For evaluating the practical applicability, we demonstrate the application on the Ethereum network and measure and evaluate limiting factors related to transaction cost and confirmation times.

Security is often a critical problem in software systems. The consequences of the failure lead to substantial economic loss or extensive environmental damage. Developing secure software is challenging, and retrofitting existing systems to introduce security is even harder. In this paper, we propose an automated approach for Finding and Repairing Bugs based on security patterns (FireBugs), to repair defects causing security vulnerabilities. To locate and fix security bugs, we apply security patterns that are reusable solutions comprising large amounts of software design experience in many different situations. In the evaluation, we investigated 2,800 Android app repositories to apply our approach to 200 subject projects that use javax.crypto APIs. The vision of our automated approach is to reduce software maintenance burdens where the number of outstanding software defects exceeds available resources. Our ultimate vision is to design more security patterns that have a positive impact on software quality by disseminating correlated sets of best security design practices and knowledge.

Bitcoin is a decentralized, pseudonymous cryptocurrency that is one of the most used digital assets to date. Its unregulated nature and inherent anonymity of users have led to a dramatic increase in its use for illicit activities. This calls for the development of novel methods capable of characterizing different entities in the Bitcoin network. In this paper, a method to attack Bitcoin anonymity is presented, leveraging a novel cascading machine learning approach that requires only a few features directly extracted from Bitcoin blockchain data. Cascading, used to enrich entities information with data from previous classifications, led to considerably improved multi-class classification performance with excellent values of Precision close to 1.0 for each considered class. Final models were implemented and compared using different machine learning models and showed significantly higher accuracy compared to their baseline implementation. Our approach can contribute to the development of effective tools for Bitcoin entity characterization, which may assist in uncovering illegal activities.

Cloud-assisted Internet of Vehicles (IoV)which merges the advantages of both cloud computing and Internet of Things that can provide numerous online services, and bring lots of benefits and conveniences to the connected vehicles. However, the security and privacy issues such as confidentiality, access control and driver privacy may prevent it from being widely utilized for message dissemination. Existing attribute-based message encryption schemes still bring high computational cost to the lightweight vehicles. In this paper, we introduce a secure and privacy-preserving dissemination scheme for warning message in cloud-assisted IoV. Firstly, we adopt attribute-based encryption to protect the disseminated warning message, and present a verifiable encryption and decryption outsourcing construction to reduce the computational overhead on vehicles. Secondly, we present a conditional privacy preservation mechanism which utilizes anonymous identity-based signature technique to ensure anonymous vehicle authentication and message integrity checking, and also allows the trusted authority to trace the real identity of malicious vehicle. We further achieve batch verification to improve the authentication efficiency. The analysis indicate that our scheme gains more security properties and reduces the computational overhead on the vehicles.

Vehicular ad hoc networks (VANETs) have been growing rapidly because it can improve traffic safety and efficiency in transportation. In VANETs, messages are broadcast in wireless environment, which is vulnerable to be attacked in many ways. Accordingly, it is essential to authenticate the legitimation of vehicles to guarantee the performance of services. In this paper, we propose an anonymous conditional privacy-preserving authentication scheme based on message authentication code (MAC) for VANETs. With verifiable secret sharing (VSS), vehicles can obtain a group key for message generation and authentication after a mutual authentication phase. Security analysis and performance evaluation show that the proposed scheme satisfies basic security and privacy-preserving requirements and has a better performance compared with some existing schemes in terms of computational cost and communication overhead.

Hiding contents of users' messages has been successfully addressed before, while anonymization of message senders remains a challenge since users do not usually trust ISPs and messaging application providers. To resolve this challenge, several solutions have been proposed so far. Among them, the Dining Cryptographers network protocol (DC-net) provides the strongest anonymity guarantees. However, DC-net suffers from two critical issues that makes it impractical, i.e., (1) collision possibility and (2) vulnerability against disruptions. Apart from that, we noticed a third critical issue during our investigation. (3) DC-net users can be deanonymized after they publish at least three messages. We name this problem the short stability issue and prove that anonymity is provided only for a few cycles of message publishing. As far as we know, this problem has not been identified in the previous research works. In this paper, we propose Harmonized and Stable DC-net (HSDC-net), a self-organizing protocol for anonymous communications. In our protocol design, we first resolve the short stability issue and obtain SDC-net, a stable extension of DC-net. Then, we integrate the Slot Reservation and Disruption Management sub-protocols into SDC-net to overcome the collision and security issues, respectively. The obtained HSDC-net protocol can also be integrated into blockchain-based cryptocurrencies (e.g. Bitcoin) to mix multiple transactions (belonging to different users) into a single transaction in such a way that the source of each payment is unknown. This preserves privacy of blockchain users. Our prototype implementation shows that HSDC-net achieves low latencies that makes it a practical protocol.

Generalized chaos systems have more complex dynamic behavior than conventional chaos systems. If a generalized response system can be synchronized with a conventional drive system, the flexible control parameters and unpredictable synchronization state will increase significantly. The study first constructs a four-dimensional nonlinear dynamic equation with quadratic variables as a drive system. The numerical simulation and analyses of the Lyapunov exponent show that it is also a chaotic system. Based on the generalized chaos synchronization (GCS) theory, a four-dimensional diffeomorphism function is designed, and the corresponding GCS response system is generated. Simultaneously, the structural and synchronous circuits of information interaction and control are constructed with Multisim™ software, with the circuit simulation resulting in a good agreement with the numerical calculations. In order to verify the practical effect of generalized synchronization, an RGB digital image secure communication scheme is proposed. We confuse a 24-bit true color image with the designed GCS system, extend the original image to 48-bits, analyze the scheme security from keyspace, key sensitivity and non-symmetric identity authentication, classical types of attacks, and statistical average from the histogram, image correlation. The research results show that this GCS system is simple and feasible, and the encryption algorithm is closely related to the confidential information, which can resist the differential attack. The scheme is suitable to be applied in network images or other multimedia safe communications.

Due to the potential security problem about key management and distribution for the symmetric image encryption schemes, a novel asymmetric image encryption method is proposed in this paper, which is based on the elliptic curve ElGamal (EC-ElGamal) cryptography and chaotic theory. Specifically, the SHA-512 hash is first adopted to generate the initial values of a chaotic system, and a crossover permutation in terms of chaotic index sequence is used to scramble the plain-image. Furthermore, the generated scrambled image is embedded into the elliptic curve for the encrypted by EC-ElGamal which can not only improve the security but also can help solve the key management problems. Finally, the diffusion combined chaos game with DNA sequence is executed to get the cipher image. The experimental analysis and performance comparisons demonstrate that the proposed method has high security, good efficiency, and strong robustness against the chosen-plaintext attack which make it have potential applications for the image secure communications.

As the technological progress of mobile Internet, smartphone based on Android OS accounts for the vast majority of market share. The traditional encryption technology cannot resolve the dilemma in smartphone information leakage, and the Android-based authentication system in view of biometric recognition emerge to offer more reliable information assurance. In this paper, we summarize several biometrics providing their attributes. Furthermore, we also review the algorithmic framework and performance index acting on authentication techniques. Thus, typical identity authentication systems including their experimental results are concluded and analyzed in the survey. The article is written with an intention to provide an in-depth overview of Android-based biometric verification systems to the readers.

With the current significant penetration of mobile devices (i.e. smartphones and tablets) and the tremendous increase in the number of the corresponding mobile applications, they have become an indispensable part of our lives. Nowadays, there is a significant growth in the number of sensitive applications such as personal health applications, personal financial applications, home monitoring applications, etc. In addition, with the significant growth of Internet-of-Things (IoT) devices, smartphones and the corresponding applications are widely considered as the Internet gateways for these devices. Mobile devices mostly use wireless LANs (WLANs) (i.e., WiFi networks) as the prominent network interface to the Internet. However, due to the broadcast nature of WiFi links, wireless traffics are exposed to any eavesdropping adversary within the WLAN. Despite WiFi encryption, studies show that application usage information could be inferred from the encrypted wireless traffic. The leakage of this sensitive information is very serious issue that will significantly impact users' privacy and security. In addressing this privacy concern, we design and develop a lightweight programmable privacy framework, called PrivacyGuard. PrivacyGuard is inspired by the vision of pushing the Software Defined Network (SDN)-like paradigm all the way to wireless network edge, is designed to support of adopting privacy preserving policies to protect the wireless communication of the sensitive applications. In this paper, we demonstrate and evaluate a prototype of PrivacyGuard framework on Android devices showing the flexibility and efficiency of the framework.

GPS signals, the main origin of navigation, are not functional in indoor environments. Therefore, Wi-Fi access points have started to be increasingly used for localization and tracking inside the buildings by relying on fingerprint-based approach. However, with these types of approaches, several concerns regarding the privacy of the users have arisen. Malicious individuals can determine a clients daily habits and activities by simply analyzing their wireless signals. While there are already efforts to incorporate privacy to the existing fingerprint-based approaches, they are limited to the characteristics of the homo-morphic cryptographic schemes they employed. In this paper, we propose to enhance the performance of these approaches by exploiting another homomorphic algorithm, namely DGK, with its unique encrypted sorting capability and thus pushing most of the computations to the server side. We developed an Android app and tested our system within a Columbia University dormitory. Compared to existing systems, the results indicated that more power savings can be achieved at the client side and DGK can be a viable option with more powerful server computation capabilities.

In pervasive computing, the human-computer interaction emphasizes on information and communication technology and user experience. Now it is possible to communicate scientific and engineering technique informally through leisure activities, for instance aquascaping. It is necessary to keep the aquascape environment fresh and healthy, and the fish have to be feed regularly. This paper proposes an autonomous aquascape preservation system based on Arduino controller connected to a remote Android smartphone. However, it is widely known that the wireless communication is not as reliable as the wired counterpart. An unauthorized party should not be able to take control of the wireless aquascape preservation system. SIMON lightweight cryptography is used to tackle security issues in constrained devices. From experiments result, the DS18B20 sensor is able to measure aquascape temperature precisely with approximately 0.5% tolerance. The Android graphical user interface application is user-friendly. Moreover, the SIMON lightweight encryption SIMON64/128 is able to secure wireless communication channel efficiently with small hardware footprints.

The paper is devoted to the comparison of performance of prospective lightweight block cipher Cypress with performances of the known modern lightweight block ciphers such as AES, SPECK, SPARX etc. The measurement was done on different platforms: Windows, Linux and Android. On all platforms selected, the block cipher Cypress showed the best results. The block cipher Cypress-256 showed the highest performance on Windows x32 (almost 3.5 Gbps), 64-bit Linux (over 8 Gbps) and Android (1.3 Gbps). On Windows x64 the best result was obtained by Cypress- 512 (almost 5 Gbps).

Recently, damage caused by ransomware has been increasing in PC and Android environments. There are many studies into real-time ransomware detection because the most important time to prevent encryption is before ransomware is able to execute its malicious process. Traditional analyses determine an application is ransomware or not by static/dynamic methods. Those analyses can serve as components of a method to detect ransomware in real time. However, problems can occur such as the inability to detect new/variant/unknown ransomware. These types require signed patches from a trusted party that can only be created after attacks occur. In a previous study into realtime new/variant/unknown ransomware detection in a PC environment, important files are monitored and only programs that have been previously analyzed and evaluated as nonmalicious are allowed. As such, programs that have not been analyzed are restricted from accessing important files. In an Android environment, this method can be applied using Android applications to prevent emerging threats and verify consistency with user intent. Thus, this paper proposes a method of detecting new/variant/unknown ransomware in real time in an Android environment.

Advanced Persistent Threat (APT) attack has the characteristics of complex attack means, long duration and great harmfulness. Based on the idea of dynamic deception, the paper proposed an APT defense system framework, and analyzed the deception defense process. The paper proposed a hybrid encryption communication mechanism based on socket, a dynamic IP address generation method based on SM4, a dynamic timing selection method based on Viterbi algorithm and a dynamic policy allocation mechanism based on DHCPv6. Tests show that the defense system can dynamically change and effectively defense APT attacks.

Machine Learning as a Service (MLaaS) is becoming a popular practice where Service Consumers, e.g., end-users, send their data to a ML Service and receive the prediction outputs. However, the emerging usage of MLaaS has raised severe privacy concerns about users' proprietary data. PrivacyPreserving Machine Learning (PPML) techniques aim to incorporate cryptographic primitives such as Homomorphic Encryption (HE) and Multi-Party Computation (MPC) into ML services to address privacy concerns from a technology standpoint. Existing PPML solutions have not been widely adopted in practice due to their assumed high overhead and integration difficulty within various ML front-end frameworks as well as hardware backends. In this work, we propose PlaidML-HE, the first end-toend HE compiler for PPML inference. Leveraging the capability of Domain-Specific Languages, PlaidML-HE enables automated generation of HE kernels across diverse types of devices. We evaluate the performance of PlaidML-HE on different ML kernels and demonstrate that PlaidML-HE greatly reduces the overhead of the HE primitive compared to the existing implementations.