Biblio

With the rapid development of traffic encryption technology and the continuous emergence of various network services, the classification of encrypted zero-day applications has become a major challenge in network supervision. More seriously, many attackers will utilize zero-day applications to hide their attack behaviors and make attack undetectable. However, there are very few existing studies on zero-day applications. Existing works usually select and label zero-day applications from unlabeled datasets, and these are not true zero-day applications classification. To address the classification of zero-day applications, this paper proposes an Encrypted Zero-day Applications Classification (EZAC) method that combines Convolutional Neural Network (CNN) and K-Means, which can effectively classify zero-day applications. We first use CNN to classify the flows, and for the flows that may be zero-day applications, we use K-Means to divide them into several categories, which are then manually labeled. Experimental results show that the EZAC achieves 97.4% accuracy on a public dataset (CIC-Darknet2020), which outperforms the state-of-the-art methods.

Anonymity is an essential asset for a variety of communication systems, like humans' communication, the internet of things, and sensor networks. Establishing and maintaining such communication systems requires the exchange of information about their participants (called subjects). However, protecting anonymity reduces the availability of subject information, as these can be leveraged to break anonymity. Additionally, established techniques for providing anonymity often reduce the efficiency of communication networks. In this paper, we model four mechanisms to share routing information and discuss them with respect to their influence on anonymity and efficiency. While there is no ``one fits all'' solution, there are suitable trade-offs to establish routing information complying with the technical capabilities of the subjects. Distributed solutions like decentralized lookup tables reduce routing information in messages at the cost of local memory consumption; other mechanisms like multi-layer encrypted path information come with higher communication overhead but reduce memory consumption for each subject.

Cryptographic (crypto) algorithms are the essential ingredients of all secure systems: crypto hash functions and encryption algorithms, for example, can guarantee properties such as integrity and confidentiality. Developers, however, can misuse the application programming interfaces (API) of such algorithms by using constant keys and weak passwords. This paper presents CRYLOGGER, the first open-source tool to detect crypto misuses dynamically. CRYLOGGER logs the parameters that are passed to the crypto APIs during the execution and checks their legitimacy offline by using a list of crypto rules. We compared CRYLOGGER with CryptoGuard, one of the most effective static tools to detect crypto misuses. We show that our tool complements the results of CryptoGuard, making the case for combining static and dynamic approaches. We analyzed 1780 popular Android apps downloaded from the Google Play Store to show that CRYLOGGER can detect crypto misuses on thousands of apps dynamically and automatically. We reverse-engineered 28 Android apps and confirmed the issues flagged by CRYLOGGER. We also disclosed the most critical vulnerabilities to app developers and collected their feedback.

Load profiling is to cluster power consumption data to generate load patterns showing typical behaviors of consumers, and thus it has enormous potential applications in smart grid. However, short-interval readings would generate massive smart meter data. Although cloud computing provides an excellent choice to analyze such big data, it also brings significant privacy concerns since the cloud is not fully trustworthy. In this paper, based on a modified vector homomorphic encryption (VHE), we propose a privacy-preserving and outsourced k-means clustering scheme (PPOk M) for secure load profiling over encrypted meter data. In particular, we design a similarity-measuring method that effectively and non-interactively performs encrypted distance metrics. Besides, we present an integrity verification technique to detect the sloppy cloud server, which intends to stop iterations early to save computational cost. In addition, extensive experiments and analysis show that PPOk M achieves high accuracy and performance while preserving convergence and privacy.

Smart Meters (SM) are IoT end devices used to collect user utility consumption with limited processing power on the edge of the smart grid (SG). While SMs have great applications in providing data analysis to the utility provider and consumers, private user information can be inferred from SMs readings. For preserving user privacy, a number of methods were developed that use perturbation by adding noise to alter user load and hide consumer data. Most methods limit the amount of perturbation noise using differential privacy to preserve the benefits of data analysis. However, additive noise perturbation may have an undesirable effect on billing. Additionally, users may desire to select complete privacy without giving consent to having their data analyzed. We present a virtual battery model that uses perturbation with additive noise obtained from a virtual chargeable battery. The level of noise can be set to make user data differentially private preserving statistics or break differential privacy discarding the benefits of data analysis for more privacy. Our model uses fog aggregation with authentication and encryption that employs lightweight cryptographic primitives. We use Diffie-Hellman key exchange for symmetrical encryption of transferred data and a two-way challenge-response method for authentication.

Data tracing is an important topic in the era of digital economy when data are considered as one of the core factors in economic activities. However, the current data traceability systems often fail to obtain public trust due to their centralization and opaqueness. Blockchain possesses natural technical features such as data tampering resistance, anonymity, encryption security, etc., and shows great potential of improving the data tracing credibility. In this paper, we propose a blockchain-PROV-based multi-center data provenance solution in where the PROV model standardizes the data record storage and provenance on the blockchain automatically and intelligently. The solution improves the transparency and credibility of the provenance data, such as to help the efficient control and open sharing of data assets.

Blockchain is a decentralized technology that provides untampered and anonymous security service to users. Without relying on trusted third party, it can establish the value transfer between nodes and reduce the transaction costs. Mature public key cryptosystem and signature scheme are important basis of blockchain security. Currently, most of the public key cryptosystems are based on classic difficult problems such as RSA and ECC. However, the above asymmetric cryptosystems are no longer secure with the development of quantum computing technology. To resist quantum attacks, researchers have proposed encryption schemes based on lattice recently. Although existing schemes have theoretical significance in blockchain, they are not suitable for the practical application due to the large size of key and signature. To tackle the above issues, this paper proposes an anti-quantum signature scheme over ideal lattice in blockchain. First, we transfer the signature scheme from the standard lattice to the ideal lattice, which reduces the size of public key. Afterwards, a novel signature scheme is proposed to reduce both the size of the private and public key significantly. Finally, we theoretically prove the security of our ideal lattice-based signature scheme with a reduction to the hardness assumption of Ideal Small Integer Sulotion problem which can resist quantum attacks. The efficiency analysis demonstrates that our signature scheme can be practically used in blockchain.

Due to the popularity of Windows system, BitLocker is widely used as a built-in disk encryption tool. As a commercial application, the design of BitLocker has to consider a capability of disaster recovery, which helps a user to recover data stored on encrypted disk when a regular access is not available. In this case, it will inevitably lead to some security risks when using BitLocker. We have a deep exploration of BitLocker encryption mechanism in this paper. We present the decryption method of encrypted VMK in case of system partition encryption and non-system partition encryption, respectively. VMK is the core key in BitLocker, with which the encrypted partition or the entire disk can be further decrypted. As for security analysis on BitLocker, we firstly make a difficulty analysis of brute force cracking on BitLocker keys, and then we analyze a possible threat caused by key theft. Based on this, we propose a few countermeasures about BitLocker usage. Additionally, we give some suggestions about security enhancement of BitLocker encryption.

As the configuration used for the Mobile Ad hoc Networks (MANET) does not have a fixed infrastructure as well, the mechanism varies for each MANET. The finding of the route in this mechanism also varies because it does not have any fixed path route for routing as well every node in this structure behaves like a base station. MANET has such freedom for its creation, so it also faces various types of attacks on it. Some of the attacks are a black hole, warm hole etc. The researchers have provided various methods to prevent warm hole attacks, as the warm hole attack is seen as difficult to prevent. So here a mechanism is proposed to detect and prevent the warm hole attack using the AODV protocol which is based on trust calculation. In our method, the multiple path selection is used for finding the best path for routing. The path is tested for the warm hole attack, as the node is detected the data packet sent in between the source and destination selects the path from the multi-paths available and the packet delivery is improved. The packet delivery ratio (PDR) is calculated for the proposed mechanism, and the results have improved the PDR by 71.25%, throughput by 74.09 kbps, and the E to E delay is decreased by 57.92ms for the network of 125 nodes.

In view of the security threats caused by the code execution vulnerability of the industrial control system, design the trusted security architecture of the industrial control system based on the embedded system. From the trusted startup of industrial control equipment, the safety protection for industrial control system is completed. The scheme is based on TPM and Xilinx Zynq-7030 to build an industrial trusted computing environment and complete the trusted startup process. Experiment shows that this method can effectively prevent the destruction of malicious code during the startup process of embedded system and provide technical support for the construction of trusted computing environment of industrial control system.

Trusted Platform Modules (TPMs) are specialized chips that store RSA keys specific to the host system for hardware authentication. The RSA keys refer to an encryption technology developed by RSA Data Security. The RSA algorithm accounts for the fact that there is no efficient way to factor extremely large numbers. Each TPM chip contains an RSA Key pair known as the Endorsement Key that cannot be accessed by software. The TPM contains an additional key, called the Attestation Identity Key that protects the device itself against unauthorized firmware and software modification by implementing hash functions on critical sections of the software and firmware before execution. As a result, the TPM can be used as a chip for handling encryption for a larger system to offer an additional layer of security. Furthermore, the TPM can also be used for managing encryption keys, as a Storage Root Key is created when a user or administrator takes ownership of the system. However, merging the TPM into a system does come with additional costs along with potential benefits. This paper focuses on integrating a TPM into a system implemented on an ARM processor that engages with power electronics, and then presents the security benefits associated with a TPM.

This article describes the process assembling of Encryption & Decryption In Trusted Platform Module of encoding information in NM640X \textregistered. Encoding of information, carried out in assembly language according to Gost 28147-89. It is a realisation of standard GOST 28147-89- Russian state symmetric key block cipher. GOST 28147-89 has 64-bit to access the kernel, trust, and allocated memory in the BlockSize and 256-bit KeySize.

Hardware security has long been an important issue in the current IC design. In this paper, a hardware Trojan detection method based on frequency domain characteristics of power consumption is proposed. For some HTs, it is difficult to detect based on the time domain characteristics, these types of hardware Trojan can be analyzed in the frequency domain, and Mahalanobis distance is used to classify designs with or without HTs. The experimental results demonstrate that taking 10% distance as the criterion, the hardware Trojan detection results in the frequency domain have almost no failure cases in all the tested designs.

This paper uses side channel analysis to detect hardware Trojan based on back propagation neural network. First, a power consumption collection platform is built to collect power waveforms, and the amplifier is utilized to amplify power consumption information to improve the detection accuracy. Then the small difference between the power waveforms is recognized by the back propagation neural network to achieve the purpose of detection. This method is validated on Advanced Encryption Standard circuit. Results show this method is able to identify the circuits with a Trojan occupied 0.19% of Advanced Encryption Standard circuit. And the detection accuracy rate can reach 100%.

Smart grid employs intelligent transmission and distribution networks for effective and reliable delivery of electricity. It uses fine-grained electrical measurements to attain optimized reliability and stability by sharing these measurements among different entities of energy management systems of the grid. There are many stakeholders like users, phasor measurement units (PMU), and other entities, with changing requirements involved in the sharing of the data. Therefore, data security plays a vital role in the correct functioning of a power grid network. In this paper, we propose an attribute-based encryption (ABE) for secure data sharing in Smart Grid architectures as ABE enables efficient and secure access control. Also, the access policy is obfuscated to preserve privacy. We use Linear Secret Sharing (LSS) Scheme for supporting any monotone access structures, thereby enhancing the expressiveness of access policies. Finally, we also analyze the security, access policy privacy and collusion resistance properties along with efficiency analysis of our cryptosystem.

This paper analyzes the vulnerability in the process of key negotiation between the main mode and aggressive mode of IKEv1 protocol in IPSec VPN, and proposes a DOS attack method based on OSPF protocol adjacent route spoofing. The experiment verifies the insecurity of IPSec VPN using IKEv1 protocol. This attack method has the advantages of lower cost and easier operation compared with using botnet.

As a general interface for chip system testing and on-chip debugging, JTAG is facing serious security threats. By analyzing the typical JTAG attack model and security protection measures, this paper designs a secure JTAG debugging model based on Schnorr identity authentication protocol, and takes RISCV as an example to build a set of SoC prototype system to complete functional verification. Experiments show that this secure JTAG debugging model has high security, flexible implementation, and good portability. It can meet the JTAG security protection requirements in various application scenarios. The maximum clock frequency can reach 833MHZ, while the hardware overhead is only 47.93KGate.

In order to develop safety-reliable standards for IoT (Internet of Things) networks, appropriate tools for their verification are needed. Among them there is a group of tools based on automated symbolic analysis. Such a tool is Tamarin software. Its usage for creating formal proofs of security protocols correctness has been presented in this paper using the simple example of an exchange of messages with asynchronous encryption between two agents. This model can be used in sensor networks or IoT e.g. in TLS protocol to provide a mechanism for secure cryptographic key exchange.

Internet of Things (IoT) have offered great opportunities for the growth of smart objects in the last decade. Smart devices are deployed in many fields such as smart cities, healthcare and agriculture. One of the applications of IoT is Wireless Sensor Networks (WSN) that require inexpensive and space-economic design for remote sensing and communication capabilities. This, unfortunately, lead to their inherent security vulnerabilities. Lightweight cryptography schemes are designed to counter many attacks in low-powered devices such as the IoT and WSN. These schemes can provide support for data encryption and key management while maintaining some level of efficiency. Most of these block ciphers provide good security. However, due to the complex cryptographic scheme's efficiency and optimisation is an issue. In this work, we focus on a new lightweight encryption scheme called the Klein block cipher. The algorithms of Klein block cipher are analysed for performance and security optimisations. A new algorithm which consists of 3-layer substitute box is proposed to reduce the need for resource consumption but maintain the security.

For classical fault analysis, a transient fault is required to be injected during runtime, e.g., only at a specific round. Instead, Persistent Fault Analysis (PFA) introduces a powerful class of fault attacks that allows for a fault to be present throughout the whole execution. One limitation of original PFA as introduced by Zhang et al. at CHES'18 is that the adversary needs know (or brute-force) the faulty values prior to the analysis. While this was addressed at a follow-up work at CHES'20, the solution is only applicable to a single faulty value. Instead, we use the potency of Statistical Fault Analysis (SFA) in the persistent fault setting, presenting Statistical Persistent Fault Analysis (SPFA) as a more general approach of PFA. As a result, any or even a multitude of unknown faults that cause an exploitable bias in the targeted round can be used to recover the cipher's secret key. Indeed, the undesired faults in the other rounds that occur due the persistent nature of the attack converge to a uniform distribution as required by SFA. We verify the effectiveness of our attack against LED and AES.

System-on-Chip (SoC) supply chain is widely acknowledged as a major source of security vulnerabilities. Potentially malicious third-party IPs integrated on the same Network-on-Chip (NoC) with the trusted components can lead to security and trust concerns. While secure communication is a well studied problem in computer networks domain, it is not feasible to implement those solutions on resource-constrained SoCs. In this paper, we present a lightweight anonymous routing protocol for communication between IP cores in NoC based SoCs. Our method eliminates the major overhead associated with traditional anonymous routing protocols while ensuring that the desired security goals are met. Experimental results demonstrate that existing security solutions on NoC can introduce significant (1.5X) performance degradation, whereas our approach provides the same security features with minor (4%) impact on performance.

This paper presents a self-securing decentralized on-chip network interface (NI) architecture to Multicore System-on-Chip (McSoC) platforms. To protect intra-chip communication within McSoC, security framework proposal resides in initiator and target NIs. A comparison between block cipher and lightweight cryptographic algorithms is then given, so we can figure out the most suitable cipher for network-on-chip (NoC) architectures. AES and LED security algorithms was a subject of this comparison. The designs are developed in Xilinx ISE 14.7 tool using VHDL language.

Network-on-chip (NoC) has become the standard communication fabric for on-chip components in modern System-on-chip (SoC) designs. Since NoC has visibility to all communications in the SoC, it has been one of the primary targets for security attacks. While packet encryption can provide secure communication, it can introduce unacceptable energy and performance overhead due to the resource-constrained nature of SoC designs. In this paper, we propose a lightweight encryption scheme that is implemented on the network interface. Our approach improves the performance of encryption without compromising security using incremental cryptography, which exploits the unique NoC traffic characteristics. Experimental results demonstrate that our proposed approach significantly (up to 57%, 30% on average) reduces the encryption time compared to traditional approaches with negligible (less than 2%) impact on area overhead.

The paper presents shared memory implementation of chaotic RGB LSB steganography technique, The proposed technique involves hiding the secret information into RGB components of the cover image. Chaotic logistic map has been used to generate highly random numbers for enhancing the security of embedded information. Encryption and decryption process is parallelized using OpenMP API in multicore environment, and results show significant speed up and highly scalable results even with large amount of data.

Mobile Adhoc networks (MANETs) comprises of mobile devices or nodes that are connected wirelessly and have no infrastructure. Detecting malicious activities in MANETs is a challenging task as they are vulnerable to attacks where the performance of the entire network degrades. Hence it is necessary to provide security to the network so that the nodes are prone to attack. Selecting a good routing protocol in MANET is also important as frequent change of topology causes the route reply to not arrive at the source node. In this paper, R-AODV (Reverse Adhoc On-Demand Distance Vector) protocol along with ECC (Elliptic Key Cryptography) algorithm is designed and implemented to detect and to prevent the malicious node and to secure data transmission against blackhole attack. The main objective is to keep the data packets secure. ECC provides a smaller key size compared to other public-key encryption and eliminates the requirement of pre-distributed keys also makes the path more secure against blackhole attacks in a MANET. The performance of this proposed system is simulated by using the NS-2.35 network simulator. Simulation results show that the proposed protocol provides good experimental results on various metrics like throughput, end-to-end delay, and PDR. Analysis of the results points to an improvement in the overall network performance.