Biblio

The biggest challenge of sharing data stored in cloud-storage is privacy-preservation. In this paper, we propose a simple yet effective solution for enforcing the security of private data stored in some cloud storage for sharing. We consider an environment where even if the cloud service provider is not-reliable or is compromised, our data still remain secure. The data Owner encrypts the private files using a secret key, file identifier and hash function and then uploads the cipher text files to the cloud. When a Data user requests access to a file, the owner establishes a key with the user and creates a new key, which is sent to the user. The user can then extract the original key by using the mutually established secret key and use it to decrypt the encrypted file. Thus we propose a system which is computationally simple yet provides a secure mechanism for sharing private data even over an untrusted cloud service provider.

Anonymous Communication (AC) hides traffic patterns and protects message metadata from being leaked during message transmission. Many practical AC systems have been proposed aiming to reduce communication latency and support a large number of users. However, how to design AC systems which possess strong security property and at the same time achieve optimal performance (i.e., the lowest latency or highest horizontal scalability) has been a challenging problem. In this paper, we propose an ObliComm framework, which consists of six modular AC subroutines. We also present a strong security definition for AC, named oblivious communication, encompassing confidentiality, unobservability, and a new requirement sending-and-receiving operation hiding. The AC subroutines in ObliComm allow for modular construction of oblivious communication systems in different network topologies. All constructed systems satisfy oblivious communication definition and can be provably secure in the universal composability (UC) framework. Additionally, we model the relationship between the network topology and communication measurements by queuing theory, which enables the system's efficiency can be optimized and estimated by quantitative analysis and calculation. Through theoretical analyses and empirical experiments, we demonstrate the efficiency of our scheme and soundness of the queuing model.

Over the last decade, a technology called Internet of Things (IoT) has been evolving at a rapid pace. It enables the development of endless applications in view of availability of affordable components which provide smart ecosystems. The IoT devices are constrained devices which are connected to the internet and perform sensing tasks. Each device is identified by their unique address and also makes use of the Constrained Application Protocol (CoAP) as one of the main web transfer protocols. It is an application layer protocol which does not maintain secure channels to transfer information. For authentication and end-to-end security, Datagram Transport Layer Security (DTLS) is one of the possible approaches to boost the security aspect of CoAP, in addition to which there are many suggested ways to protect the transmission of sensitive information. CoAP uses DTLS as a secure protocol and UDP as a transfer protocol. Therefore, the attacks on UDP or DTLS could be assigned as a CoAP attack. An attack on DTLS could possibly be launched in a single session and a strong authentication mechanism is needed. Man-In-The-Middle attack is one the peak security issues in CoAP as cited by Request For Comments(RFC) 7252, which encompasses attacks like Sniffing, Spoofing, Denial of Service (DoS), Hijacking, Cross-Protocol attacks and other attacks including Replay attacks and Relay attacks. In this work, a client-server architecture is setup, whose end devices communicate using CoAP. Also, a proxy system was installed across the client side to launch an active interception between the client and the server. The work will further be enhanced to provide solutions to mitigate these attacks.

Continuously growing amount of research experiments using High Performance Computing (HPC) leads to the questions of research data management and in particular how to preserve a scientific experiment including all related data for long term for its future reproduction. This paper covers some challenges and possible solutions related to the preservation of scientific experiments on HPC systems and represents a concept of the preservation system for HPC computations. Storage of the experiment itself with some related data is not only enough for its future reproduction, especially in the long term. For that case preservation of the whole experiment's environment (operating system, used libraries, environment variables, input data, etc.) via containerization technology (e.g. using Docker, Singularity) is proposed. This approach allows to preserve the entire environment, but is not always possible on every HPC system because of security issues. And it also leaves a question, how to deal with commercial software that was used within the experiment. As a possible solution we propose to run a preservation process outside of the computing system on the web-server and to replace all commercial software inside the created experiment's image with open source analogues that should allow future reproduction of the experiment without any legal issues. The prototype of such a system was developed, the paper provides the scheme of the system, its main features and describes the first experimental results and further research steps.

Dynamic Taint Analysis (DTA) technique has been developed for analysis and understanding behavior of Android applications and privacy policy enforcement. Meanwhile, implicit information flows (IIFs) are major concern of security researchers because IIFs can evade DTA technique easily and give attackers an advantage over the researchers. Some researchers suggested approaches to the issue and developed analysis systems supporting privacy policy enforcement against IIF-accompanied attacks; however, there is still no effective technique of comprehensive analysis and privacy policy enforcement against IIF-accompanied attacks. In this paper, we propose an IIF detection technique to enforce privacy policy against IIF-accompanied attacks in Android applications. We developed a new analysis tool, called Smalien, that can discover data leakage caused by IIF-contained information flows as well as explicit information flows. We demonstrated practicability of Smalien by applying it to 16 IIF tricks from ScrubDroid and two IIF tricks from DroidBench. Smalien enforced privacy policy successfully against all the tricks except one trick because the trick loads code dynamically from a remote server at runtime, and Smalien cannot analyze any code outside of a target application. The results show that our approach can be a solution to the current attacker-superior situation.

This paper proposes a distributed deep learning framework for privacy-preserving medical data training. In order to avoid patients' data leakage in medical platforms, the hidden layers in the deep learning framework are separated and where the first layer is kept in platform and others layers are kept in a centralized server. Whereas keeping the original patients' data in local platforms maintain their privacy, utilizing the server for subsequent layers improves learning performance by using all data from each platform during training.

Nowadays, a massive number of data, referred as big data, are being collected from social networks and Internet of Things (IoT), which are of tremendous value. Many deep learning-based methods made great progress in the extraction of knowledge of those data. However, the knowledge extraction of the law data poses vast challenges on the deep learning, since the law data usually contain the privacy information. In addition, the amount of law data of an institution is not large enough to well train a deep model. To solve these challenges, some privacy-preserving deep learning are proposed to capture knowledge of privacy data. In this paper, we review the emerging topics of deep learning for the feature learning of the privacy data. Then, we discuss the problems and the future trend in deep learning for privacy-preserving feature learning on law data.

With cloud computing's development, more users are decide to store information on the cloud server. Owing to the cloud server's insecurity, many documents should be encrypted to avoid information leakage before being sent to the cloud. Nevertheless, it leads to the problem that plaintext search techniques can not be directly applied to the ciphertext search. In this case, many searchable encryption schemes based on single data owner model have been proposed. But, the actual situation is that users want to do research with encrypted documents originating from various data owners. This paper puts forward a privacy-preserving scheme that is based on fuzzy multi-keyword search (PPFMKS) for multiple data owners. For the sake of espousing fuzzy multi-keyword and accurate search, secure indexes on the basis of Locality-Sensitive Hashing (LSH) and Bloom Filter (BF)are established. To guarantee the search privacy under multiple data owners model, a new encryption method allowing that different data owners have diverse keys to encrypt files is proposed. This method also solves the high cost caused by inconvenience of key management.

This paper provides a proof of concept for using SRAM based Physically Unclonable Functions (PUFs) to generate private keys for IoT devices. PUFs are utilized, as there is inadequate protection for secret keys stored in the memory of the IoT devices. We utilize a custom-made Arduino mega shield to extract the fingerprint from SRAM chip on demand. We utilize the concepts of ternary states to exclude the cells which are easily prone to flip, allowing us to extract stable bits from the fingerprint of the SRAM. Using the custom-made software for our SRAM device, we can control the error rate of the PUF to achieve an adjustable memory-based PUF for key generation. We utilize several fuzzy extractor techniques based on using different error correction coding methods to generate secret keys from the SRAM PUF, and study the trade-off between the false authentication rate and false rejection rate of the PUF.

Big data will bring revolutionary changes from life to thinking for society as a whole. At the same time, the massive data and potential value of big data are subject to many security risks. Aiming at the above problems, a data privacy protection model for big data platform is proposed. First, the data privacy protection model of big data for data owners is introduced in detail, including protocol design, logic design, complexity analysis and security analysis. Then, the query privacy protection model of big data for ordinary users is introduced in detail, including query protocol design and query mode design. Complexity analysis and safety analysis are performed. Finally, a stand-alone simulation experiment is built for the proposed privacy protection model. Experimental data is obtained and analyzed. The feasibility of the privacy protection model is verified.

With the continuous development of information technology, our country has achieved great progress and development in Electronic Science and technology. Nowadays mobile embedded systems are gradually coming into people's vision. Mobile embedded system is a brand-new computer technology in the current computer technology. Now it has been widely used in enterprises. Mobile embedded system extends its functions mainly by combining the access capability of the Internet. Nowadays, embedded system network is widely welcomed by people. But for the embedded system network, there are also a variety of network attacks. Therefore, in the research process of this paper, we mainly start with the way of embedded network security and network attack, and then carry out the countermeasures to improve the network security of embedded system, which is to provide a good reference for improving the security and stability of embedded system.

As a new generation of network architecture with subversive changes to traditional IP networks, Content Centric Networks (CCN) has attracted widespread attention from domestic and foreign scholars for its efficient content distribution, multi-path and secure routing features. The design architecture of CCN network has many advantages. However, it is also easily used illegally, which brings certain security problems. For example, objectified network resources which include requesters, publishers, content and node routes, are faced with many security threats, such as privacy attribute disclosure, privacy detection, content information disclosure, and spoofing and denial of service attacks. A node routing security scheme based on dynamic reputation value is proposed for the security problem of node routing. It is convenient for detecting node routing attacks and defending in time. And it could provide security for the Content Centric Networks node routing without affecting the node routing advantages and normal user requests.

Smart Farming is driven by the emergence of precise positioning systems and Internet of Things technologies which have already enabled site-specific applications, sustainable resource management, and interconnected machinery. Nowadays, so-called Farm Management Information Systems (FMISs) enable farm-internal interconnection of agricultural machines and implements and, thereby, allow in-field data exchange and the orchestration of collaborative agricultural processes. Machine data is often directly logged during task execution. Moreover, interconnection of farms, agricultural contractors, and marketplaces ease the collaboration. However, current FMISs lack in security and particularly in user authentication. In this paper, we present a security architecture for a decentralized, manufacturer-independent, and open-source FMIS. Special attention is turned on the Radio Frequency Identification (RFID)-based continuous user authentication which greatly improves security and credibility of automated documentation, while at the same time preserves usability in practice.

Partitioning security components of IoT devices to enable the use of Trusted Execution Environments adds resilience against side-channel attacks. Devices are hardened against extraction of sensitive information, but at the same time additional effort must be spent for the integration of the TEE and software partitioning. To perform partitioning, the developer typically inserts Remote Procedure Calls into the software. Existing RPC-based solutions require the developer to write Interface Definition Language files to generate RPC stubs. In this work, we present an RPC-based framework that supports software partitioning via a graphical user interface. The framework extracts required information about the interfaces from source-code header files to eliminate the need for IDL files. With this approach the TEE integration time is reduced and reuse of existing libraries is supported. We evaluate a Proof-of-Concept by partitioning a TLS library for IoT devices and compare our approach to other RPC-based solutions.

Authentication is the fundamental security service used in almost all remote applications. All such sensitive applications over an open network need authentication mechanism that should be delivered in a trusted way. In this paper, we design an RSA based authentication system for smart IoT environment over the air network using state-of-the-art industry standards. Our system provide security services including X.509 certificate, RSA based Public Key Infrastructure (PKI), challenge/response protocols with the help of proxy induced security service provider. We describe an innovative system model, protocol design, system architecture and evaluation against known threats. Also the implemented solution designed as an add on service for multiple other sensitive applications (smart city apps, cyber physical systems etc.) which needs the support of X.509 certificate based on hard tokens to populate other security services including confidentiality, integrity, non-repudiation, privacy and anonymity of the identities. The proposed scheme is evaluated against known vulnerabilities and given detail comparisons with popular known authentication schemes. The result shows that our proposed scheme mitigate all the known security risks and provide highest level assurance to smart gadgets.

The emergence of IPv6 protocol extends the address pool, but it also exposes all the Internet-connected devices to danger. Currently, there are some traditional schemes on security management of network addresses, such as prevention, traceability and encryption authentication, but few studies work on IPv6 protocol. In this paper, we propose a hierarchical authentication mechanism for the IPv6 source address with the technology of software defined network (SDN). This mechanism combines the authentication of three parts, namely the access network, the intra-domain and the inter-domain. And it can provide a fine-grained security protection for the devices using IPv6 addresses.

With the rapid development of micro-electronics and Information and Communication Technology (ICT), users can utilize various service such as Internet of Things(IoT), smart-healthcare and smart-home using wearable devices. However, the sensitive information of user are revealed by attackers because the medical services are provided through open channel. Therefore, secure mutual authentication and key establishment are essential to provide secure services for legitimate users in Wireless Body Area Networks(WBAN). In 2019, Gupta et al. proposed a lightweight anonymous user authentication and key establishment scheme for wearable devices. We demonstrate that their scheme cannot withstand user impersonation, session key disclosure and wearable device stolen attacks. We also propose a secure and lightweight mutual authentication and key establishment scheme using wearable devices to resolve the security shortcomings of Gupta et al.'s scheme. The proposed scheme can be suitable to resource-limited environments.

The usage of cloud for data storage has become ubiquitous. To prevent data leakage and hacks, it is common to encrypt the data (e.g. PDF files) before sending it to a cloud. However, this limits the search for specific files containing certain keywords over an encrypted cloud data. The traditional method is to take down all files from a cloud, store them locally, decrypt and then search over them, defeating the purpose of using a cloud. In this paper, we propose a method, called SecureCSearch, to perform keyword search operations on the encrypted PDF files over cloud in an efficient manner. The proposed method makes use of Shamir's Secret Sharing scheme in a novel way to create encrypted shares of the PDF file and the keyword to search. We show that the proposed method maintains the security of the data and incurs minimal computation cost.

Cloud computing is one of the emerging area in the business world that help to access resources at low expense with high privacy. Security is a standout amongst the most imperative difficulties in cloud network for cloud providers and their customers. In order to ensure security in cloud, we proposed a framework using different encryption algorithm namely Extended hill cipher and homomorphic encryption. Firstly user data/information is isolated into two parts which is static and dynamic data (critical data). Extended hill cipher encryption is applied over more important dynamic part where we are encrypting the string using matrix multiplication. While homomorphic encryption is applied over static data in which it accepts n number of strings as information, encode each string independently and lastly combine all the strings. The test results clearly manifests that the proposed model provides better information security.

With the development of cloud computing technology, developed countries including the U.S. are performing the efficiency of national defense and public sector, national innovation, and construction of the infrastructure for cloud computing environment through the policies that apply cloud computing. Korea Military is also considering that apply the cloud computing technology into its national defense command control system. However, only existing security requirements for national defense information system cannot solve the problem related security vulnerabilities of cloud computing. In order to solve this problem, it is necessary to design the secure security architecture of national defense command control system considering security requirements related to cloud computing. This study analyze the security requirements needed when the U.S. military apply the cloud computing system. It also analyze existing security requirements for Korea national defense information system and security requirements for cloud computing system and draw the security requirements needed to Korea national defense information system based on cloud computing.

Researchers are trying to find new ways of finding and pointing out Cybersecurity vulnerabilities by using innovative metrics. New theoretical proposals need to be tested in a real environment, using Cybersecurity tools applications that can validate the applicability of those in real life. This paper presents an experimental flexible environment, which can be used for the validation of several theoretical claims based on an “easy to use” architecture implemented in a cloud environment. The framework provides a much shorter time setup in the real world as well as a much better understanding based on log analysis provided by MS Azure. As a proof of concept, we have tested three different claims and provided proves of results such as screenshots and log samples.

Manufacturing enterprises are constantly exploring new ways to improve their own production processes to address the increasing demand of customized production. However, such enterprises show a low degree of flexibility, which mainly results from the need to configure new production equipment at design and run time. In this paper we propose self-adaptation as an approach to improve data transmission flexibility in Industry 4.0 environments. We implement an autonomic manager using a generic autonomic management framework, which applies the most appropriate data transmission configuration based on security and business process related requirements, such as performance. The experimental evaluation is carried out in a MQTT infrastructure and the results show that using self-adaptation can significantly improve the trade-off between security and performance. We then propose to integrate anomaly detection methods as a solution to support self-adaptation by monitoring and learning the normal behavior of an industrial system and show how this can be used by the generic autonomic management framework.

Authentication is achieved by using different techniques, like using smart-card, identity password and biometric techniques. Some of the proposed schemes use a single factor for authentication while others combine multiple ways to provide multi-factor authentication for better security. lately, a new scheme for multi-factor authentication was presented by Cao and Ge and claimed that their scheme is highly secure and can withstand against all known attacks. In this paper, it is revealed that their scheme is still vulnerable and have some loopholes in term of reflection attack. Therefore, an improved scheme is proposed to overcome the security weaknesses of Cao and Ge's scheme. The proposed scheme resists security attacks and secure. Formal testing is carried out under a broadly-accepted simulated tool ProVerif which demonstrates that the proposed scheme is well secure.

Rapid evolution of cyber threats and recent trends in the increasing number of cyber-attacks call for adopting robust and agile cybersecurity techniques. Cybersecurity information sharing is expected to play an effective role in detecting and defending against new attacks. However, reservations and or-ganizational policies centering the privacy of shared data have become major setbacks in large-scale collaboration in cyber defense. The situation is worsened by the fact that the benefits of cyber-information exchange are not realized unless many actors participate. In this paper, we argue that privacy preservation of shared threat data will motivate entities to share threat data. Accordingly, we propose a framework called CYBersecurity information EXchange with Privacy (CYBEX-P) to achieve this. CYBEX-P is a structured information sharing platform with integrating privacy-preserving mechanisms. We propose a complete system architecture for CYBEX-P that guarantees maximum security and privacy of data. CYBEX-P outlines the details of a cybersecurity information sharing platform. The adoption of blind processing, privacy preservation, and trusted computing paradigms make CYBEX-P a versatile and secure information exchange platform.

An increasing number of IoT scenarios involve mobile, resource-constrained IoT devices that rely on untrusted networks for Internet connectivity. In such environments, attackers can derive sensitive private information of IoT device owners, e.g., daily routines or secret supply chain procedures, when sniffing on IoT communication and linking IoT devices and owner. Furthermore, untrusted networks do not provide IoT devices with any protection against attacks from the Internet. Anonymous communication using onion routing provides a well-proven mechanism to keep the relationship between communication partners secret and (optionally) protect against network attacks. However, the application of onion routing is challenged by protocol incompatibilities and demanding cryptographic processing on constrained IoT devices, rendering its use infeasible. To close this gap, we tailor onion routing to the IoT by bridging protocol incompatibilities and offloading expensive cryptographic processing to a router or web server of the IoT device owner. Thus, we realize resource-conserving access control and end-to-end security for IoT devices. To prove applicability, we deploy onion routing for the IoT within the well-established Tor network enabling IoT devices to leverage its resources to achieve the same grade of anonymity as readily available to traditional devices.