Search

With the fast development of Internet of Things (IoT) especially for smart grid and electric vehicle (EV) networking, vehicle-to-grid (V2G) communications have been increasingly studied and recognized as one of the most convincing tools for general road transportation, to effectively reduce the oil demands and gas emissions. Unfortunately, a series of security and privacy issues have significantly impeded its wide adoption. The existing work mainly focused on the static environment, which cannot be directly applied to the mobile setting where EVs travel across regions. The dynamic pricing metric in V2G networks depends on the real-time electricity usage aggregation in one region. To address this issue, in this article, an efficient privacy-preserving data aggregation and dynamic pricing service PADP in V2G IoT is proposed, by designing an identity-based sequential aggregate signed data (SASD) based on factoring and a threshold homomorphic encryption. In the proposed threshold homomorphic encryption, a legal ciphertext can be generated if and only if no less than threshold $k$ individual illegal ciphertexts are aggregated. Therefore, the aggregated power consumption data can be successfully decrypted while the individual power consumption privacy of honest EV users can be well protected against even the collusion between a malicious power charging station and compromised EVs. Furthermore, the technique of SASD guarantees entity authentication with a minimized amount of transmitted data. Finally, formal security proof and extensive performance evaluation demonstrate the effectiveness and practicability of our proposed PADP.

It is a challenging issue in smart grid to provide flexible and efficient data aggregation and at the same time maintain data integrity and data privacy. To address this issue, we firstly propose a lightweight $t$ -times homomorphic encryption scheme, which can reduce the computational cost of smart devices further and resist quantum attacks. Based on it, we propose two efficient data aggregation schemes for two application scenarios. The first scheme is suitable for small network, such as home network and small-office network. The second scheme is appropriate for medium-size network, such as a part of smart city. More specifically, we explore how the number of smart devices and the number of home area networks affect the overhead of communication and computation. The experiment results show that the proposed schemes are efficient. Moreover, the proposed schemes not only meet security requirements of integrity, confidentiality, authenticity, resistance to intermediate attack, resistance to replay attack, forward and backward security and resistance to quantum attack, but also reduce the overhead of communication and computation.

The demands for the fairness, security, and efficiency of the supply chain have grown significantly due to the rise of globalization. However, some problems of the information flow, logistics, and capital flow in the supply chain remain a challenge, such as the information asymmetry between upstream and downstream, substandard quality of goods, difficulty in traceability, and default of payment. Therefore, this paper proposes a blockchain-based supply chain framework (SESCF), which solves the supply chain problems securely and efficiently. First, the use of blockchain and smart contracts ensures the information symmetry in the supply chain system. Second, the radio frequency identification (RFID) provides a unique identity of goods, which helps in real-time quality monitoring. Additionally, the immutability and distributed storage of the blockchain play an important role in tracking the origin of goods. Third, the efficient payment channel is used to solve the problem of payment defaults. Furthermore, simulations of smart contracts along with the security analyses are presented in this paper. We also implement a blockchain-based supply chain system (SescfDapp), which is built upon a Consortium blockchain. Large-scale experiments and detailed analysis prove the feasibility and efficiency of our proposed system.

Searchable encryption (SE) allows the cloud server to search over the encrypted data and leak information as little as possible. Most existing efficient SE schemes assume that the leakage of search pattern and access pattern is acceptable. A series of work was proposed, instructing malicious users to use this leakage to come up with attacks. Especially, with a devastating attack proposed by Zhang et al., the cloud server can reveal the keywords queried by normal users by using some injected files. From the method of constructing uniform $(k,n)$-set of a finite set $A$ proposed by Cao, we put forward a new file-injection attack. In our attack, the server needs fewer injected files than the previous attack when the size of $T$ is larger than 9 and the size of keyword set is larger than $2T$, where $T$ is the threshold of the number of keywords in each injected file. Our attack is more practical and easier to implement in the real scenario.

ABKS has drawn much attention from research and industry in recent years, an ABKS scheme is an encryption scheme that supports keyword search and access control. Attribute-Based Encryption is a public key encryption that enables users to encrypt and decrypt message based on attributes. In a typical implementation, the size of the ciphertext is proportional to the number of attributes associated with it and the decryption time is proportional to the number of attributes used during decryption. Inherit from ABE technology, the computation cost and ciphertext size in most ABKS schemes grow with the complexity of the access policy. On the other hand, we found that the traditional ABKS schemes cannot resist our secret-key-recovery attack. To deal with the above problems, we present new ciphertext policy attribute based encryption with fast keyword search constructions. Our constructions preserve the fine-grained access control inherited from the ABE system while supporting hidden policy and fast keyword search. Our constructions feature multi-value-independent compared with the existing attribute based searchable encryption schemes. The performance analysis demonstrates the efficiency of our constructions. We offer rigorous security proof of our second scheme, which is IND-CKA and IND-CPA secure.

Blockchain can be utilized to enhance both security and efficiency for location-based service (LBS) in vehicular social networks (VSNs), due to its inherent decentralization, anonymity, and trust properties. Unfortunately, the existing approaches either lack effective authentication, which is vulnerable to the man-in-the-middle attack, or require an online certificate authority (CA) where frequent interactions with resource-constrained vehicles are required. To address these challenging issues, in this article, a lightweight threshold CA for consortium blockchain along with a privacy-preserving LBS protocol in blockchain enforced VSNs is proposed. First, a lightweight threshold CA framework LTCA is proposed by devising a threshold proxy signature, where the proxy signing key is issued by a coalition of threshold number of CAs playing the roles of authorized nodes in the consortium blockchain. Without the intervene of an online CA, each vehicle in the online phase can authenticate its identity by itself each time its blockchain address (i.e., account address) is updated. Then, based on the proposed LTCA, an efficient privacy-preserving LBS protocol PPVC is contrived to protect each vehicle’s conditional identity privacy with a moderate cost. Finally, both security analysis and performance evaluation demonstrate the effectiveness and efficiency of our proposed LTCA and PPVC in blockchain enforced VSNs.

Location-based service (LBS) in vehicular ad hoc networks (VANETs) has significantly benefited information acquisition from geographically-based social networking. Authentication guarantees the unforgeability and the effectiveness of the LBS information. Unfortunately, owing to a large quantity of redundant or useless LBS messages disseminated in VANETs, the heavy authentication overhead of the existing work adopting a periodically released authentication key, filtering with message identifiers or exploiting public key (fully) homomorphic encryption (FHE), is either intolerable by resource-constrained on-board units (OBUs) or inappropriate to the realtime controlling requirement for VANETs. In this paper, an efficient multi-key secure outsourced computation scheme MSOC without exploiting public key FHE is first proposed, in the setting of two non-colluding servers, namely the cloud and the cryptographic service provider (CSP). Then, based on MSOC, an efficient and secure comparison protocol LSCP is devised, without the interaction between the server and the users. Furthermore, a lightweight privacy-preserving authentication protocol LPPA for LBS in VANETs is proposed, by eliminating duplicate and useless encrypted LBS messages before authentication is executed, through a newly devised efficient privacy-preserving information filtering system. Both user’s location privacy and interest privacy are well protected against even the collusion between the roadside units (RSUs) serving as the cloud (or CSP) and malicious users. Especially, the property of ciphertext re-encryption of our proposed MSOC also guarantees the interest pattern privacy whether two users accept the same LBS information. Finally, formal security proof and extensive simulation results verify the effectiveness and practicability of our proposed LPPA.

M-healthcare social networks are becoming increasingly important in supporting an efficient and promising e-healthcare platform. The moving patients suffering from the same disease or living in the neighborhood of the same healthcare provider constitute a delay tolerant network (DTN) to help each other forwarding the patient health information (PHI). Unfortunately, the mobile device carried on each patient collecting PHI from body sensors is subjected to sophisticated attacks. To reduce the probability of patients being threatened by a newly identified target node compromise attack, maximize the credits earned from transmitting packets and achieve the fairness among patients, a game theory based secure incentive mechanism GTSIM is proposed. Based on it, by exploiting the complete marriage theory in combinatorics, a patient-optimized privacy-preserving packet forwarding scheme POP is devised to protect the PHI confidentiality and the identity/location privacy of the patients, decrease the privacy exposure when intermediate patients are compromised and realize the property of patient-optimization required in m-healthcare systems. Last but not least, the security analysis shows both our proposed GTSIM and POP can resist various sophisticated attacks and the extensive simulation demonstrates the practicability and efficiency with high message delivery ratio, obtainable utility fraction and low average latency.

Real-time bidding (RTB), one of the major trading mechanisms used for online advertising, allows the advertiser to make an impression-level bid decision. However, the security and privacy concerns of RTB are gaining increasing attention with the recent enforcement of the European Union General Data Protection Regulation (GDPR). In this study, we present a novel privacy-preserving RTB (Pri-RTB) protocol, which aims at preserving both data privacy and utility by performing additively homomorphic encryption on the user profile. To our knowledge, this is the first work to address the privacy issue of the RTB paradigm. We present a formal proof for the security of Pri-RTB under the assumption of the decisional Diffie–Hellman (DDH) problem. We analyze and elaborate the superiority of Pri-RTB over other related works. We also developed a prototype for Pri-RTB and conducted several experiments to evaluate its feasibility and efficiency under different parameters. Our experiments demonstrate that Pri-RTB can work highly efficiently in a practical setting (for example, a scenario with approximately 200 advertisers per auction).

Incorporation of fog computing with low latency, preprocession (e.g., data aggregation) and location awareness, can facilitate fine-grained collection of smart metering data in smart grid and promotes the sustainability and efficiency of the grid. Recently, much attention has been paid to the research on smart grid, especially in protecting privacy and data aggregation. However, most previous works do not focus on privacy-preserving data aggregation and function computation query on enormous data simultaneously in smart grid based on fog computation. In this paper, we construct a novel verifiable privacy-preserving data collection scheme supporting multi-party computation(MPC), named VPDC-MPC, to achieve both functions simultaneously in smart grid based on fog computing. VPDC-MPC realizes verifiable secret sharing of users’ data and data aggregation without revealing individual reports via practical cryptosystem and verifiable secret sharing scheme. Besides, we propose an efficient algorithm for batch verification of share consistency and detection of error reports if the external adversaries modify the SMs’ report. Furthermore, VPDC-MPC allows both the control center and users with limited resources to obtain arbitrary arithmetic analysis (not only data aggregation) via secure multi-party computation between cloud servers in smart grid. Besides, VPDC-MPC tolerates fault of cloud servers and resists collusion. We also present security analysis and performance evaluation of our scheme, which indicates that even with tradeoff on computation and communication overhead, VPDC-MPC is practical with above features.

In recent years, the sharing economy is developing rapidly and has become a popular economic model. For example, sharing platforms such as Airbnb have gradually entered people ’s field of vision and obtained high economic benefits. However, the information managed by such a centralized platform may be used by criminals and people’s privacy may be violated. In order to achieve the goal of decentralization, we propose a blockchain-based house sharing platform. Users can directly conduct transactions on the blockchain by running smart contracts. Our scheme guarantees the anonymity of users through commitment scheme and zero-knowledge technology. In order to deal with the problems that may be encountered in reality, we propose a trusted authority to trace malicious users. In addition, our platform has reputation mechanism to restrict the behavior of users. We analyze its security and performance, and the result shows that it is feasible in reality.

In this paper, we introduce a new cryptographic primitive, called autonomous path proxy re-encryption (AP-PRE), which is motivated by several application scenarios where the delegator would like to control the whole delegation path in a multi-hop delegation process. Compared with the traditional proxy re-encryption, AP-PRE provides much better fine-grained access control to delegation path. Briefly speaking, in an AP-PRE scheme, the delegator designates a path of his preferred delegatees. The path consists of several delegatees with the privilege from high to low. If the delegatee in the path cannot complete the decryption, the decryption right is automatically delegated to the next one in the path. In this way, the delegator can ensure that the delegation has always been done among those delegatees the delegator trusts. Moreover, an AP-PRE scheme has to obey the following path rules. The delegation, for ciphertexts of a delegator $i$i, can only be carried out on the autonomous path $\mathsf {Pa}_i$Pai designated by the delegator $i$i, in the sense that (1) re-encrypted ciphertexts along the autonomous path $\mathsf {Pa}_i$Pai cannot branch off $\mathsf {Pa}_i$Pai with meaningful decryption, and (2) original ciphertexts generated under $pk_j$pkj for $j \ne i$j≠i (i.e., for a path $\mathsf {Pa}_j$Paj different from $\mathsf {Pa}_i$Pai) cannot be inserted into (i.e., cannot be transformed along) the autonomous path $\mathsf {Pa}_i$Pai with meaningful decryption. We give the formal definition, as well as the formal security model, for this cryptographic primitive. Under this concept, we construct an IND-CPA secure AP-PRE scheme under the decisional bilinear Diffie-Hellman (DBDH) assumption in the random oracle model. Our scheme is with the useful properties of proxy re-encryption, i.e., unidirectionality and multi-hop.

Privacy-protected signal and image processing for outsourced computing has hence recently been popular. We present a framework for privacy-preserving outsourced image feature Extraction(POIFE) in the semi-honest setting. Also we prove that the construction is simulation-based secure under the semi-honest adversaries. In our scheme, the user can be flexible to outsource his computation to the cloud without real-time online. Compared with the previous works, our solution improves privacy.

Autonomous vehicles are expected to significantly enhance the human mobility. However, recently researchers have discovered and demonstrated some attacks on vehicles, which have caused a panic among the public. Furthermore, these attacks have demonstrated that the security issue is still one of the major challenges of vehicles. In this paper, we propose a novel edge computing based anomaly detection, coined edge computing based vehicle anomaly detection (EVAD), which exploits edge based sensor data fusion to identify the anomaly events. The time domain property, i.e., the correlation between different intra-vehicle sensors, and the frequency domain property of sensor data are utilized to judge whether an anomaly has occurred within the vehicle. Especially, to reduce the computation overhead and improve the performance, multiple sensors will be organized as ring architecture, which is a tradeoff of detection accuracy and complexity. In addition, the major components (e.g., anomaly detection module) of EVAD are embedded in edge computing devices, which make the anomaly detection be more efficient and privacy preserving. Meanwhile, a more appropriate model is generated on the cloud server, of which computation overhead maybe heavy for edge computing devices. This paper evaluates the performance of EVAD under different scenarios, and the experimental results demonstrate its feasibility and efficiency. The average true positive rate achieves 99.5% with 1% false positive rate.

Fault-tolerant aggregate signatures allow the verification algorithm to recognize and verify all the valid individual signatures in an aggregate signature. However, in ordinary aggregate signature schemes, if there is a single faulty individual signature in the valid aggregate, the whole aggregate will be invalid. This will make great difficulties in many applications including secure logging and batch verification in vehicular ad hoc network et al. In this paper, inspired by the finite set theory called uniform (k,n)-set proposed by Cao, we put forward a novel fault-tolerant aggregate signature scheme. Our new scheme is more efficient compared with previous fault-tolerant aggregate signature scheme based on cover-free family. It is noted that our scheme is quite easy to be implemented in the real scenario.

Lossy trapdoor functions (LTDFs) were introduced by Peikert and Waters (STOC 2008) and have a number of applications in cryptography. All-but-many lossy trapdoor functions (ABM-LTDFs) are generalizations of LTDFs studied by Hofheinz (Eurocrypt 2012). Specially, using ABM-LTDFs to construct public key encryption (PKE) scheme with selective opening security has been proven feasible. Existing ABM-LTDFs were built on pairings, lattices and decisional composite residuosity (DCR) assumption. However, pairing-based ABM-LTDFs and DCR-based ABM-LTDFs rely on non-standard assumptions. In this paper, we construct an ABM-LTDF under the decisional RSA subgroup (DRSA) assumption, and we employ it to construct PKE scheme with selective opening security. We also propose a construction of DCR-based ABM-LTDF relying on standard assumption in Appendix.

Public key encryption scheme with keyword search (PEKS) is a promising technique supporting search on encrypted data without leaking any information about the keyword. In real applications, it's critical to find an effective revocation method to revoke users in multi-user cryptosystems, when user's secret keys are exposed.In this paper, we propose the first designated server-aided revocable identity-based encryption scheme with keyword search (dSR-IBKS) from lattice. The dSR-IBKS model requires each user to keep just one private key corresponding with his identity and does not need to communicate with the key generation center or the server during key updating. We have proved that our scheme can achieve chosen keyword indistinguishability in the standard model. In particular, our scheme can designate a unique tester to test and return the search results, therefore no other entity can guess the keyword embedded in the ciphertext by generating search queries and doing the test by itself. We provide a formal security proof of our scheme assuming the hardness of the learning with errors (LWE) problem on the standard model.

With the location-based services (LBS) booming, the volume of spatial data inevitably explodes. In order to reduce local storage and computational overhead, users tend to outsource data and initiate queries to the cloud. However, sensitive data or queries may be compromised if cloud server has access to raw data and plaintext token. To cope with this problem, searchable encryption for geometric range is applied. Geometric range search has wide applications in many scenarios, especially the circular range search. In this paper, a practical and secure circular range search scheme (PSCS) is proposed to support searching for spatial data in a circular range. With our scheme, a semi-honest cloud server will return data for a given circular range correctly without uncovering index privacy or query privacy. We propose a polynomial split algorithm which can decompose the inner product calculation neatly. Then, we define the security of our PSCS formally and prove that it is secure under same-closeness-pattern chosen-plaintext attacks (CLS-CPA) in theory. In addition, we demonstrate the efficiency and accuracy through analysis and experiments compared with existing schemes.