Biblio

Information exchange occurs all the time in today’s internet era. Some of the data are public, and some are private. Asymmetric cryptography plays a critical role in securing private data transfer. However, technological advances caused private data at risk due to the presence of quantum computers. Therefore, we need a new method for securing private data. This paper proposes combining DNA cryptography methods based on the NTRU cryptosystem to enhance security data confidentiality. This method is compared with conventional public key cryptography methods. The comparison shows that the proposed method has a slow encryption and decryption time compared to other methods except for RSA. However, the key generation time of the proposed method is much faster than other methods tested except for ECC. The proposed method is superior in key generation time and considerably different from other tested methods. Meanwhile, the encryption and decryption time is slower than other methods besides RSA. The test results can get different results based on the programming language used.

With the advent of cloud storage services many users tend to store their data in the cloud to save storage cost. However, this has lead to many security concerns, and one of the most important ones is ensuring data integrity. Public verification schemes are able to employ a third party auditor to perform data auditing on behalf of the user. But most public verification schemes are vulnerable to procrastinating auditors who may not perform auditing on time. These schemes do not have fair arbitration also, i.e. they lack a way to punish the malicious Cloud Service Provider (CSP) and compensate user whose data has been corrupted. On the other hand, CSP might be storing redundant data that could increase the storage cost for the CSP and computational cost of data auditing for the user. In this paper, we propose a Blockchain-based public auditing and deduplication scheme with a fair arbitration system against procrastinating auditors. The key idea requires auditors to record each verification using smart contract and store the result into a Blockchain as a transaction. Our scheme can detect and punish the procrastinating auditors and compensate users in the case of any data loss. Additionally, our scheme can detect and delete duplicate data that improve storage utilization and reduce the computational cost of data verification. Experimental evaluation demonstrates that our scheme is provably secure and does not incur overhead compared to the existing public auditing techniques while offering an additional feature of verifying the auditor’s performance.

SQL Injection has been around as a harmful and prolific threat on web applications for more than 20 years, yet it still poses a huge threat to the World Wide Web. Rapidly evolving web technology has not eradicated this threat; In 2017 51 % of web application attacks are SQL injection attacks. Most conventional practices to prevent SQL injection attacks revolves around secure web and database programming and administration techniques. Despite developer ignorance, a large number of online applications remain susceptible to SQL injection attacks. There is a need for a more effective method to detect and prevent SQL Injection attacks. In this research, we offer a unique machine learning-based strategy for identifying potential SQL injection attack (SQL injection attack) threats. Application of the proposed method in a Security Information and Event Management(SIEM) system will be discussed. SIEM can aggregate and normalize event information from multiple sources, and detect malicious events from analysis of these information. The result of this work shows that a machine learning based SQL injection attack detector which uses SIEM approach possess high accuracy in detecting malicious SQL queries.

As a fundamental departure from the IP design which encodes source and destination addresses in each packet, Named Data Networking (NDN) directly uses application-defined data names for network layer communications. While bringing important data-centric benefits, the semantic richness of NDN names has also raised confidentiality and privacy concerns. In this paper, we first define the problem of name confidentiality, and then investigate the solution space through a comprehensive examination of all the proposed solutions up to date. Our work shows that the proposed solutions are simply different means to hide the actual data names via a layer of translation; they differ in where and how the translation takes place, which lead to different trade-offs in feasibility, efficiency, security, scalability, and different degrees of adherence to NDN's data-centric communications. Our investigation suggests the feasibility of a systematic design that can enable NDN to provide stronger name confidentiality and user privacy as compared to today's TCP/IP Internet.

The concepts of information flow security and refinement are known to have had a troubled relationship ever since the seminal work of McLean. In this work we study refinements that support changes in data representation and semantics, including the addition of state variables that may induce new observational power or side channels. We propose a new epistemic approach to ignorance-preserving refinement where an abstract model is used as a specification of a system's permitted information flows, that may include the declassification of secret information. The core idea is to require that refinement steps must not induce observer knowledge that is not already available in the abstract model. Our study is set in the context of a class of shared variable multiagent models similar to interpreted systems in epistemic logic. We demonstrate the expressiveness of our framework through a series of small examples and compare our approach to existing, stricter notions of information-flow secure refinement based on bisimulations and noninterference preservation. Interestingly, noninterference preservation is not supported “out of the box” in our setting, because refinement steps may introduce new secrets that are independent of secrets already present at abstract level. To support verification, we first introduce a “cube-shaped” unwinding condition related to conditions recently studied in the context of value-dependent noninterference, kernel verification, and secure compilation. A fundamental problem with ignorance-preserving refinement, caused by the support for general data and observation refinement, is that sequential composability is lost. We propose a solution based on relational pre-and postconditions and illustrate its use together with unwinding on the oblivious RAM construction of Chung and Pass.

The most widely used method to prevent adversaries from eavesdropping on sensitive sensor, robot, and war fighter communications is mathematically strong cryptographic algorithms. However, prevailing cryptographic protocol mandates are often made without consideration of resource constraints of devices in the internet of Battlefield Things (IoBT). In this article, we address the challenges of IoBT sensor data exchange in contested environments. Battlefield IoT (Internet of Things) devices need to exchange data and receive feedback from other devices such as tanks and command and control infrastructure for analysis, tracking, and real-time engagement. Since data in IoBT systems may be massive or sparse, we introduced a machine learning classifier to determine what type of data to transmit under what conditions. We compared Support Vector Machine, Bayes Point Match, Boosted Decision Trees, Decision Forests, and Decision Jungles on their abilities to recommend the optimal confidentiality preserving data and transmission path considering dynamic threats. We created a synthesized dataset that simulates platoon maneuvers and IED detection components. We found Decision Jungles to produce the most accurate results while requiring the least resources during training to produce those results. We also introduced the JointField blockchain network for joint and allied force data sharing. With our classifier, strategists, and system designers will be able to enable adaptive responses to threats while engaged in real-time field conflict.

Recent work on intrusion-tolerance has shown that resilience to sophisticated network attacks requires system replicas to be deployed across at least three geographically distributed sites. While commodity data centers offer an attractive solution for hosting these sites due to low cost and management overhead, their use raises significant confidentiality concerns: system operators may not want private data or proprietary algorithms exposed to servers outside their direct control. We present a new model for Byzantine Fault Tolerant replicated systems that moves toward “intrusion tolerance as a service”. Under this model, application logic and data are only exposed to servers hosted on the system operator's premises. Additional offsite servers hosted in data centers can support the needed resilience without executing application logic or accessing unencrypted state. We have implemented this approach in the open-source Spire system, and our evaluation shows that the performance overhead of providing confidentiality can be less than 4% in terms of latency.

With their role as an integral part of its infrastructure, Industrial Control Systems (ICS) are a vital part of every nation's industrial development drive. Despite several significant advancements - such as controlled-environment agriculture, automated train systems, and smart homes, achieved in critical infrastructure sectors through the integration of Information Systems (IS) and remote capabilities with ICS, the fact remains that these advancements have introduced vulnerabilities that were previously either nonexistent or negligible, one being Remote Access Trojans (RATs). Present RAT detection methods either focus on monitoring network traffic or studying event logs on host systems. This research's objective is the detection of RATs by comparing actual utilized system capacity to reported utilized system capacity. To achieve the research objective, open-source RAT detection methods were identified and analyzed, a GAP-analysis approach was used to identify the deficiencies of each method, after which control algorithms were developed into source code for the solution.

Underwater acoustic sensor networks (UASNs) have been receiving more and more attention due to their wide applications and the marine data collection is one of the important applications of UASNs. However, the openness and unreliability of underwater acoustic communication links and the easy capture of underwater wireless devices make UASNs vulnerable to various attacks. On the other hand, due to the limited resources of underwater acoustic network nodes, the high bit error rates, large and variable propagation delays, and low bandwidth of acoustic channels, many mature security mechanisms in terrestrial wireless sensor networks cannot be applied in the underwater environment [1]. In this paper, a secure communication protocol for marine data collection was proposed to ensure the confidentiality and data integrity of communication between under sensor nodes and the sink node in UASNs.

A sensor network is wireless with tiny nodes and widely used in various applications. To track the event and collect the data from a remote area or a hostile area sensor network is used. A WSN collects wirelessly connected tiny sensors with minimal resources like the battery, computation power, and memory. When a sensor collects data, it must be transferred to the control center through the gateway (Sink), and it must be transferred safely. For secure transfer of data in the network, the routing protocol must be safe and can use the cryptography method for authentication and confidentiality. An essential issue in WSN structure is the key management. WSN relies on the strength of the communicating devices, battery power, and sensor nodes to communicate in the wireless environment over a limited region. Due to energy and memory limitations, the construction of a fully functional network needs to be well arranged. Several techniques are available in the current literature for such key management techniques. Among the distribution of key over the network, sharing private and public keys is the most important. Network security is not an easy problem because of its limited resources, and these networks are deployed in unattended areas where they work without any human intervention. These networks are used to monitor buildings and airports, so security is always a major issue for these networks. In this paper, we proposed a dynamic key management scheme for the clustered sensor network that also supports the addition of a new node in the network later. Keys are dynamically generated and securely distributed to communication parties with the help of a cluster head. We verify the immunity of the scheme against various attacks like replay attack and node captured attacker. A simulation study was also done on energy consumption for key setup and refreshed the keys. Security analysis of scheme shows batter resiliency against node capture attack.

Internet of Things (IoT) devices use different types of media and protocols to communicate to Internet, but security is compromised since the devices are not using encryption, authentication and integrity. Virtual Private Network of Things (VPNoT) is a new technology designed to create end to end encrypted tunnels for IoT devices, in this case, the VPNoT device is based on OpenVPN that provides confidentiality and integrity, also based on Raspberry Pi as the hardware and Linux as the operating system, both provide connectivity using different types of media to access Internet and network management. IoT devices and sensors can be connected to the VPNoT device so an encrypted tunnel is created to an IoT Server. VPNoT device uses a profile generated by the server, then all devices form a virtual private network (VPN). VPNoT device can act like a router when necessary and this environment works for IPv6 and IPv4 with a great advantage that OpenVPN traverses NAT permitting private IoT servers be accessible to the VPN. The annual cost of the improvement is about \$455 USD per year for 10 VPNoT devices.

Currently, data security issues are remaining as a major concern during digital communication. A large amount of crucial data is transmitted through the communication channel. There are many cryptographic algorithms available, which are used for providing data security during communication and storage process. However, the data needs to be decrypted for performing operations, which may lead to elevation of the privilege of data. The pin or passwords used for decryption of data can be easily identified using a brute force attack. This leads to losing the confidentiality of crucial data to an unauthorized user. In the proposed system, a combination of Homomorphic and Honey encryption is used to improve data confidentiality and user authentication problems. Thus, the system provides better data security for the issues related to outsourced databases.

The article is devoted to the choice of personal means of the 5G defense in dependence of hard- and software available to the user. The universal module MS 127.04 and its software compatible unit can be universally configured for use. An intelligent hardware and software platform is proposed for multi-core setting of policies for the automatic encryption of confidential data and selective blocking related to the implementation of computing security and confidentiality of data transfer, using such additional specially. A platform that resists the external influences is described. The platform is based on a universal module MS 127.05 (produced in Russia), that is a heterogeneous multiprocessor system on a chip), the system features 16 processor cores (NeuroMatrix Core 4) and five ARM Cortex-A5 units (ULSI 1879VM8Ya.

Today, Linux is one of the main operating systems (OS) used both on desktop computers and various mobile devices. This OS is also widely applied in state and municipal structures, including law enforcement agencies and automated control systems used in the Armed Forces of the Russian Federation. It's worth noting that the process of replacing the Linux OS with domestic protected OSs that use the Linux kernel has now begun. In this regard, the analysis of threats to information security of the Linux OS is highly relevant. In this article, the authors discuss the security problems of Linux OS associated with unauthorized user privileges increase, as a result of which an attacker can gain full control over the OS. The approaches to differentiating user privileges in Linux are analyzed and their advantages and disadvantages are considered. As an example, the causes of the vulnerability CVE-2018-14665 were identified and measures to eliminate it were proposed.

In recent years, the computation security of edge computing has been raised as a major concern since the edge devices are often distributed on the edge of the network, less trustworthy than cloud servers and have limited storage/ computation/ communication resources. Recently, coded computing has been proposed to protect the confidentiality of computing data under edge device's independent attack and minimize the total cost (resource consumption) of edge system. In this paper, for the cooperative attack, we design an efficient scheme to ensure the information-theory security (ITS) of user's data and further reduce the total cost of edge system. Specifically, we take matrix multiplication as an example, which is an important module appeared in many application operations. Moreover, we theoretically analyze the necessary and sufficient conditions for the existence of feasible scheme, prove the security and decodeability of the proposed scheme. We also prove the effectiveness of the proposed scheme through considerable simulation experiments. Compared with the existing schemes, the proposed scheme further reduces the total cost of edge system. The experiments also show a trade-off between storage and communication.

Visible light communication (VLC) is considered as an emerging system for wireless indoor multimedia communications. As any wireless communication system, its channels are open and reachable to both licensed and unlicensed users owing to the broadcast character of visible-light propagation in public areas or multiple-user scenarios. In this work, we consider the physical-layer security approaches for VLC to mitigate this limitation. The physical-layer security approaches can be divided into two categories: keyless security and key-based security approaches. In the last category, recently, the authors introduced physical-layer key-generation approaches for optical orthogonal frequency division multiplexing (OFDM) systems. In these approaches, the cyclic prefix (CP) samples are exploited for key generation. In this paper, we study the effect of the length of key space and order of modulation on the security level, BER performance, and key-disagreement-rate (KDR) of the introduced key-based security approaches. From the results, our approaches are more efficient in higher order of modulation as the KDR decreases with the increase of order of modulation.

Cloud is the perfect way to hold our data every day. Yet the confidentiality of our data is a big concern in the handling of cloud data. Data integrity, authentication and confidentiality are basic security threats in the cloud. Cryptography techniques and Third Party Auditor (TPA) are very useful to impose the integrity and confidentiality of data. In this paper, a system is proposed Enhancing data protection that is housed in cloud computing. The suggested solution uses the RSA algorithm and the AES algorithm to encrypt user data. The hybridization of these two algorithms allows better data protection before it is stored in the cloud. Secure hash algorithm 512 is used to compute the Hash Message Authentication Code (HMAC). A stable audit program is also introduced for Third Party Auditor (TPA) use. The suggested algorithm is applied in python programming and tested in a simple sample format. It is checked that the proposed algorithm functions well to guarantee greater data protection.

Steganography is a data hiding technique, which is generally used to hide the data within a file to avoid detection. It is used in the police department, detective investigation, and medical fields as well as in many more fields. Various techniques have been proposed over the years for Image Steganography and also attackers or hackers have developed many decoding tools to break these techniques to retrieve data. In this paper, CAPTCHA codes are used to ensure that the receiver is the intended receiver and not any machine. Here a randomized CAPTCHA code is created to provide additional security to communicate with the authenticated user and used Image Steganography to achieve confidentiality. For achieving secret and reliable communication, encryption and decryption mechanism is performed; hence a machine cannot decode it using any predefined algorithm. Once a secure connection has been established with the intended receiver, the original message is transmitted using the LSB algorithm, which uses the RGB color spectrum to hide the image data ensuring additional encryption.

Modern communication systems rely heavily on cryptography to ensure authenticity, confidentiality and integrity of exchanged messages. Elliptic Curve Cryptography 1 (ECC) is one of the common used standard methods for encrypting and signing messages. In this paper we present our implementation of a design supporting four different NIST Elliptic Curves. The design supports two B-curves (B-233, B-283) and two P-curves (P-224, P-256). The implemented designs are sharing the following hardware components bus, multiplier, alu and registers. By implementing the 4 curves in a single design and reusing some resources we reduced the area 20 by 14% compared to a design without resource sharing. Compared to a pure software solution running on an Arm Cortex A9 operating at 1GHz, our design ported to a FPGA is 1.2 to 6 times faster.

We all are living in the digital era, where the maximum of the information is available online. The digital world has made the transfer of information easy and provides the basic needs of security like authentication, integrity, nonrepudiation, etc. But, with the improvement in security, cyber-attacks have also increased. Security researchers have provided many techniques to prevent these cyber-attacks; one is a Digital Signature (DS). The digital signature uses cryptographic key pairs (public and private) to provide the message's integrity and verify the sender's identity. The private key used in the digital signature is confidential; if attackers find it by using various techniques, then this can result in an attack. This paper presents a brief introduction about the digital signature and how it is vulnerable to a man-in-the-middle attack. Further, it discusses a technique to prevent this attack in the digital signature.

Privacy preservation is a challenging task with the huge amount of data that are available in social media. The data those are stored in the distributed environment or in cloud environment need to ensure confidentiality to data. In addition, representing the voluminous data is graph will be convenient to perform keyword search. The proposed work initially reads the data corresponding to social media and converts that into a graph. In order to prevent the data from the active attacks Advanced Encryption Standard algorithm is used to perform graph encryption. Later, search operation is done using two algorithms: kNK keyword search algorithm and top k nearest keyword search algorithm. The first scheme is used to fetch all the data corresponding to the keyword. The second scheme is used to fetch the nearest neighbor. This scheme increases the efficiency of the search process. Here shortest path algorithm is used to find the minimum distance. Now, based on the minimum value the results are produced. The proposed algorithm shows high performance for graph generation and searching and moderate performance for graph encryption.

As 5G transitions from an industrial vision to a tangible, next-generation mobile technology, security remains key business driver. Heterogeneous environment, new networking paradigms and novel use cases makes 5G vulnerable to new security threats. This in turn necessitates a flexible and dependable security mechanism. End-to-End (E2E) data protection provides better security, avoids repeated security operations like encryption/decryption and provides differentiated security based on the services. E2E security deals with authentication, integrity, key management and confidentiality. The attack surface of a 5G system is larger as 5G aims for a heterogeneous networked society. Hence attack resistance needs to be a design consideration when defining new 5G protocols. This framework has been designed for accessing the manifold applications with high security and trust by offering E2E security for various services. The proposed framework is evaluated based on computation complexity, communication complexity, attack resistance rate and security defensive rate. The protocol is also evaluated for correctness, and resistance against passive, active and dictionary attacks using random oracle model and Automated Validation of Internet Security Protocols and Applications (AVISPA) tool.

Securing wireless communication is significant for privacy and confidentiality of sensing data in Cyber-Physical Systems (CPS). However, due to broadcast nature of radio channels, disseminating sensory data is vulnerable to eavesdropping and message modification. Generating secret keys by extracting the shared randomness in a wireless fading channel is a promising way to improve the communication security. In this poster, we present a novel secret key generation protocol for securing real-time data dissemination in CPS, where the sensor nodes cooperatively generate a shared key by estimating the quantized fading channel randomness. A 2-hop wireless sensor network testbed is built and preliminary experimental results show that the quantization intervals and distance between the nodes lead to a secret bit mismatch.

Increased use of secure chat and voice/ video apps has transformed the social life. While the benefits and facilitations are seemingly limitless, so are the asscoiacted vulnerabilities and threats. Besides ensuring confidentiality requirements for common users, known facts of non-readable contents over the network make these apps more attractive for criminals. Though access to contents of cryptograhically secure sessions is not possible, network forensics of secure apps can provide interesting information which can be of great help during criminal invetigations. In this paper, we presented a novel framework of profiling the secure chat and voice/ video calling apps which can be employed to extract hidden patterns about the app, information of involved parties, activities of chatting, voice/ video calls, status indications and notifications while having no information of communication protocol of the app and its security architecture. Signatures of any secure app can be developed though our framework and can become base of a large scale solution. Our methodology is considered very important for different cases of criminal investigations and bussiness intelligence solutions for service provider networks. Our results are applicable to any mobile platform of iOS, android and windows.

Given two strings: pattern p of length m and text t of length n. The string matching problem is to find all (or some) occurrences of the pattern p in the text t. We introduce a new simple data structure, called index arrays, and design fast privacy-preserving matching algorithm for string matching. The motivation behind introducing index arrays is determined by the need for pattern matching on distributed cloud-based datasets with semi-trusted cloud providers. It is intended to use encrypted index arrays both to improve performance and protect confidentiality and privacy of user data.