Biblio
Delivery service via ridesharing is a promising service to share travel costs and improve vehicle occupancy. Existing ridesharing systems require participating vehicles to periodically report individual private information (e.g., identity and location) to a central controller, which is a potential central point of failure, resulting in possible data leakage or tampering in case of controller break down or under attack. In this paper, we propose a Blockchain secured ridesharing delivery system, where the immutability and distributed architecture of the Blockchain can effectively prevent data tampering. However, such tamper-resistance property comes at the cost of a long confirmation delay caused by the consensus process. A Hash-oriented Practical Byzantine Fault Tolerance (PBFT) based consensus algorithm is proposed to improve the Blockchain efficiency and reduce the transaction confirmation delay from 10 minutes to 15 seconds. The Hash-oriented PBFT effectively avoids the double-spending attack and Sybil attack. Security analysis and simulation results demonstrate that the proposed Blockchain secured ridesharing delivery system offers strong security guarantees and satisfies the quality of delivery service in terms of confirmation delay and transaction throughput.
Blockchain technology is getting more attention due to its inherent nature in resistance to data modification. Blockchain combined with IoT enables to improve the level of services for various domains with security guarantees. Numerous research has begun in order to link the blockchain along with autonomous vehicles system on 5G networks. Ultrafast connections, speedier data downloads, and the ability to handle millions of connections more than LTE networks are crucial to support a rapid autonomous system. Therefore, the system requires proper data storage management, high secure transaction, and non-interference network. The blockchain is suitable for the 5G vehicular system since it is immutable, tamper-proof, and secure by design. Although the decentralized 5G autonomous vehicular network provides countless benefits, yet it raises more than a few challenges. This paper provides an initial stage of the blockchain-enabled 5G vehicular networks, architecture, and technical aspects. Some remarks and challenges are also discussed.
Interactive environments are more and more entering our daily life. Our homes are becoming increasingly smart and so do our working environments. Aiming to provide assistance that is not only suitable to the current situation, but as well for the involved individuals usually comes along with an increased scale of personal data being collected/requested and processed. While this may not be exceptionally critical as long as data does not leave one's smart home, circumstances change dramatically once smart home data is processed by cloud services, and, all the more, as soon as an interactive assistance system is operated by our employer who may have interest in exploiting the data beyond its original purpose, e. g. for secretly evaluating the work performance of his personnel. In this paper we discuss how a federated identity management could be augmented with distributed usage control and trusted computing technology so as to reliably arrange and enforce privacy-related requirements in externally operated interactive environments.
One of the effective ways of detecting malicious traffic in computer networks is intrusion detection systems (IDS). Though IDS identify malicious activities in a network, it might be difficult to detect distributed or coordinated attacks because they only have single vantage point. To combat this problem, cooperative intrusion detection system was proposed. In this detection system, nodes exchange attack features or signatures with a view of detecting an attack that has previously been detected by one of the other nodes in the system. Exchanging of attack features is necessary because a zero-day attacks (attacks without known signature) experienced in different locations are not the same. Although this solution enhanced the ability of a single IDS to respond to attacks that have been previously identified by cooperating nodes, malicious activities such as fake data injection, data manipulation or deletion and data consistency are problems threatening this approach. In this paper, we propose a solution that leverages blockchain's distributive technology, tamper-proof ability and data immutability to detect and prevent malicious activities and solve data consistency problems facing cooperative intrusion detection. Focusing on extraction, storage and distribution stages of cooperative intrusion detection, we develop a blockchain-based solution that securely extracts features or signatures, adds extra verification step, makes storage of these signatures and features distributive and data sharing secured. Performance evaluation of the system with respect to its response time and resistance to the features/signatures injection is presented. The result shows that the proposed solution prevents stored attack features or signature against malicious data injection, manipulation or deletion and has low latency.
In industrial internet of things, various devices are connected to external internet. For the connected devices, the authentication is very important in the viewpoint of security; therefore, physical unclonable functions (PUFs) have attracted attention as authentication techniques. On the other hand, the risk of modeling attacks on PUFs, which clone the function of PUFs mathematically, is pointed out. Therefore, a resistant-PUF such as a lightweight PUF has been proposed. However, new analytical methods (side-channel attacks: SCAs), which use side-channel information such as power or electromagnetic waves, have been proposed. The countermeasure method has also been proposed; however, an evaluation using actual devices has not been studied. Since PUFs use small production variations, the implementation evaluation is very important. Therefore, this study proposes a SCA countermeasure of the lightweight PUF. The proposed method is based on the previous studies, and maintains power consumption consistency during the generation of response. In experiments using a field programmable gate array, the measured power consumption was constant regardless of output values of the PUF could be confirmed. Then, experimental results showed that the predicted rate of the response was about 50 %, and the proposed method had a tamper resistance against SCAs.
Logic locking is an attractive defense against a series of hardware security threats. However, oracle guided attacks based on advanced Boolean reasoning engines such as SAT, ATPG and model-checking have made it difficult to securely lock chips with low overhead. While the majority of existing locking schemes focus on gate-level locking, in this paper we present a layout-inclusive interconnect locking scheme based on cross-bars of metal-to-metal programmable-via devices. We demonstrate how this enables configuring a large obfuscation key with a small number of physical key wires contributing to zero to little substrate area overhead. Dense interconnect locking based on these circuit level primitives shows orders of magnitude better SAT attack resiliency compared to an XOR/XNOR gate-insertion locking with the same key length which has a much higher overhead.
Considering their independent and environmentally-varied work-fashion, one of the most important factors in WSN applications is fault-tolerance. Due to the fact that the possibilities of an absent sensor node, damaged communication link or missing data are unavoidable in wireless sensor networks, fault-tolerance becomes a key-issue. Among the causes of these constant failures are environmental factors, battery exhaustion, damaged communications links, data collision, wear-out of memory and storage units and overloaded sensors. WSN can be in use for a variety of purposes, nevertheless its fault-tolerance needs to depend mostly on the application type. Scientific research, for example, tends to rely on accurate and precise massive amount of sensed data, thus demanding WSNs to support high degree of data sampling. The data storage capacity on the sensors is crucial because while some applications require instantaneous transmission to another node or directly to the base station, others demand intervallic or interrupted transmissions. Thus, if the amount of data is large - as a derivative of the data precision needed by the application - WSN nodes are required to store those amounts of data in a rapid and effective fashion till the transmission stage. However, since those requirements are mostly depend on the hardware and the wireless settings, WSNs frequently have distinguished amount of data loss, causing data integrity issues. Sensor nodes are inherently a cheap piece of hardware, due to the common need to use many of them over a large area, sometimes in a non-retrievable environment - a restriction that does not allow a usage of a pricey tampering or overflow resistant hardware (which also may not always be unfailing), and a damaged or overflowed sensor can harm the data integrity, or even completely reject incoming messages. The problem gets even worse when there is a need for high-rate sampling or when data should be received from many nodes since missing data becomes a more common phenomenon as deployed WSNs grow in scale. Therefore, high-rate sampling WSNs applications require fault-tolerant data storage, even though this requirement is not realistic. In cases of an overflow, our Distributed Adaptive Clustering algorithm (D-ACR) [1] reconfigures the network, by adaptively and hierarchically re-clustering parts of it, based on the rate of incoming data packages in order to minimize the energy-consumption, and prevent premature death of nodes. However, the re-clustering cannot prevent data loss caused by the nature of the sensors. We suggest to address this problem by an efficient distributed backup-placement algorithm named DBP-ACR, performed on the D-ACR refined clusters. The DBP-ACR algorithm re-directs packages from overloaded sensors to more efficient placements outside of the overloaded areas in the WSN cluster, thus increasing the fault-tolerance of the network and reducing the data loss.
Intrusion detection has been an active field of research for more than 35 years. Numerous systems had been built based on the two fundamental detection principles, knowledge-based and behavior-based detection. Anyway, having a look at day-to-day news about data breaches and successful attacks, detection effectiveness is still limited. Even more, heavy-weight intrusion detection systems cannot be installed in every endangered environment. For example, Industrial Control Systems are typically utilized for decades, charging off huge investments of companies. Thus, some of these systems have been in operation for years, but were designed afore without security in mind. Even worse, as systems often have connections to other networks and even the Internet nowadays, an adequate protection is mandatory, but integrating intrusion detection can be extremely difficult - or even impossible to date. We propose a new lightweight current-based IDS which is using a difficult to manipulate measurement base and verifiable ground truth. Focus of our system is providing intrusion detection for ICS and SCADA on a low-priced base, easy to integrate. Dr. WATTson, a prototype implemented based on our concept provides high detection and low false alarm rates.
The physical unclonable functions (PUFs) have been attracted attention to prevent semiconductor counterfeits. However, the risk of machine learning attack for an arbiter PUF, which is one of the typical PUFs, has been reported. Therefore, an XOR arbiter PUF, which has a resistance against the machine learning attack, was proposed. However, in recent years, a new machine learning attack using power consumption during the operation of the PUF circuit was reported. Also, it is important that the detailed tamper resistance verification of the PUFs to consider the security of the PUFs in the future. Therefore, this study proposes a new machine learning attack using electromagnetic waveforms for the XOR arbiter PUF. Experiments by an actual device evaluate the validity of the proposed method and the security of the XOR arbiter PUF.
The advanced encryption standard (AES) has been sufficiently studied to confirm that its decryption is computationally impossible. However, its vulnerability against fault analysis attacks has been pointed out in recent years. To verify the vulnerability of electronic devices in the future, into which cryptographic circuits have been incorporated, fault Analysis attacks must be thoroughly studied. The present study proposes a new fault analysis attack method which utilizes the tendency of an operation error due to a glitch. The present study also verifies the validity of the proposed method by performing evaluation experiments using FPGA.
The Advanced Encryption Standard (AES) enables secure transmission of confidential messages. Since its invention, there have been many proposed attacks against the scheme. For example, one can inject errors or faults to acquire the encryption keys. It has been shown that the AES algorithm itself does not provide a protection against these types of attacks. Therefore, additional techniques like error control codes (ECCs) have been proposed to detect active attacks. However, not all the proposed solutions show the adequate efficacy. For instance, linear ECCs have some critical limitations, especially when the injected errors are beyond their fault detection or tolerance capabilities. In this paper, we propose a new method based on a non-linear code to protect all four internal stages of the AES hardware implementation. With this method, the protected AES system is able to (a) detect all multiplicity of errors with a high probability and (b) correct them if the errors follow certain patterns or frequencies. Results shows that the proposed method provides much higher security and reliability to the AES hardware implementation with minimal overhead.
This work presents a highly reliable and tamper-resistant design of Physical Unclonable Function (PUF) exploiting Resistive Random Access Memory (RRAM). The RRAM PUF properties such as uniqueness and reliability are experimentally measured on 1 kb HfO2 based RRAM arrays. Firstly, our experimental results show that selection of the split reference and offset of the split sense amplifier (S/A) significantly affect the uniqueness. More dummy cells are able to generate a more accurate split reference, and relaxing transistor's sizes of the split S/A can reduce the offset, thus achieving better uniqueness. The average inter-Hamming distance (HD) of 40 RRAM PUF instances is 42%. Secondly, we propose using the sum of the read-out currents of multiple RRAM cells for generating one response bit, which statistically minimizes the risk of early retention failure of a single cell. The measurement results show that with 8 cells per bit, 0% intra-HD can maintain more than 50 hours at 150 °C or equivalently 10 years at 69 °C by 1/kT extrapolation. Finally, we propose a layout obfuscation scheme where all the S/A are randomly embedded into the RRAM array to improve the RRAM PUF's resistance against invasive tampering. The RRAM cells are uniformly placed between M4 and M5 across the array. If the adversary attempts to invasively probe the output of the S/A, he has to remove the top-level interconnect and destroy the RRAM cells between the interconnect layers. Therefore, the RRAM PUF has the “self-destructive” feature. The hardware overhead of the proposed design strategies is benchmarked in 64 × 128 RRAM PUF array at 65 nm, while these proposed optimization strategies increase latency, energy and area over a naive implementation, they significantly improve the performance and security.