As digital forensic laboratories face regulation and seek accreditation, examiners must fully validate the software and hardware used during forensic analysis. Tool validation is critical to any laboratory science as it provides analysts the empirical data necessary to draw conclusions about how laboratory instruments perform in realistic conditions. While digital forensic tools perform many common tasks, few robust validation methods exist for evaluating how tools perform those tasks. Developing validation methods that are feasible and robust is critical to both establishing digital forensics as a reliable discipline and accreditation requirements. This paper proposes a more comprehensive model of tool validation by taking continuous measurements a tool validation process. This continuous measurement process could later be repeated over all the scenarios that lab would expect to encounter in day-to-day operations. We attempt to determine whether or not a continuous model provides the sort of data necessary for empirical analysis of a digital forensic tool. Moreover, we propose a fully automated model for tool validation, permitting researchers to concentrate on validation study design rather than performing time-consuming, error-prone tasks on the test platform.

Enormous benefits are expected from Electric Vehicle (EV) which is a promising alternative to replace traditional gasoline car. However, the EV's cruising range is much shorter than the range offered by gasoline cars. Congestion at the charging stations is expected not only because of the frequent charging demands of EVs, but for the long time of charging batteries as well. In this paper, we propose a privacy-aware and fair reservation scheme for EVs charging scenarios. The drivers submit their reservation requests to the charging stations anonymously to protect their location privacy. To achieve fairness, a selfish driver should not be able to submit/authenticate many reservation requests to fill the charging queue for his own benefit. The EVs use an efficient anonymous credentials from bilinear pairings for anonymous authentication with the charging station to protect their privacy and K-times anonymous authentication to restrict a selfish driver from submitting many reservation request. Our evaluations show that the proposed scheme can efficiently preserve the drivers' privacy, secure the communication and achieve fairness with low communication and computation overhead.

Unmanned Aerial Vehicles (UAVs) also known as drones are being used in many applications where they can record or stream video. One of such applications is the Intelligent Transportation Systems (ITS) where drones may need to record videos and send a control center to be shared by various clients such as law enforcement or emergency personnel. In such cases, the recording might include faces of civilians or other sensitive information that might pose privacy concerns. While the video can be encrypted and stored in the cloud that way, it can still be accessed once the keys are exposed to third parties. To prevent such cases, in this paper, we propose a proxy re-encryption technique that will provide a key to third parties that can be used only once to access the videos. The key management is handled by a trusted control center. The implementation results indicate that there is almost no additional overhead with the approach while it can still preserve the privacy.

In this paper, we propose privacy-preserving fine-grained data retrieval schemes for mobile social networks (MSNs). The schemes enable users to retrieve data from other users who are interested in some topics related to a subject of interest. We define a subject to be a broad term that can cover many fine-grained topics, e.g., History can be a subject and World War I can be a topic. We consider centralized and decentralized network models. Our centralized scheme allows users to securely outsource data to a server such that the server matches the users who are interested in same topic(s) and have defined social attributes with privacy preservation. Searchable encryption scheme and a proposed cryptography construct are used to enable the server to match the topics and attributes without knowing any private information. By using the social attributes, users can prescribe the other users who can be connected to. We also propose a decentralized scheme that can be used when there is no connection to the server, i.e, shortage of Internet connectivity. The scheme leverages friends-of-friends relationship and transferable trust concept, where each user trusts his friends and the friends of friends. If a friend is not interested in the requested subject, he/she can link him/her to his/her friends without knowing the requested subject to preserve privacy. Our schemes use Bloom filters to store the topics of interest to reduce the storage and communication overhead. This is important because the number of fine-grained topics can be large. Different techniques to store the topics in the filter are proposed and investigated. Performance metrics are proposed and evaluated using real implementations. Our analysis and implementation results demonstrate that our schemes can preserve the privacy of the MSN users with high performance.

On-road emergencies necessitates the availability of the patient's medical records to the emergency centers for better treatment. However, these medical records are often encrypted to preserve the patient's privacy. Revealing the secret key used to encrypt these records to the emergency center would not only give unlimited unauthorized future access to the medical records but also pose privacy concerns for the patient. In this paper, we propose a secure medical records access scheme that can be used to serve the patient effectively. An emergency medical center is able to decrypt a patient's medical records without revealing the secret key used to encrypt them with the help of the patient's smart phone and the cloud server. We use proxy re-encryption scheme to trigger a re-encryption process at the cloud server by sending the required credentials. With the help of the cloud server, only a specific emergency center is able to decrypt the medical records and access the patient's medical history. Our scheme allows in-time and more efficient health care and recovery in extreme life-threatening situations. Our analysis and evaluations show that the proposed scheme can secure the medical records and preserve the privacy of the patient with acceptable computation and communication overhead.

The cryptographic credentials of misbehaving vehicles should be revoked in a timely manner to prevent jeopardizing the network. However, the revocation is a challenging problem in VANETs because of its stringent privacy requirements and the large network scalability. Each vehicle receives a large number of unlinkable certified pseudonyms to protect privacy. Large storage and computation are required to store the revocation list and verify the authenticity of messages, respectively. In this paper, we propose a scalable revocation scheme that reduces the revocation list storage overhead and the revocation checking delay in pseudonym-based VANETs. The revocation of vehicle's credentials is achieved by adding a single trapdoor in a revocation list. The vehicles use the published trapdoors for revocation check by computing simple operations instead of sequentially searching a large set of pseudonyms. Chameleon hashing is used to generate the pseudonyms and revoke them if needed. Using computationally efficient multi-signature, vehicles can cooperatively vote to revoke the credentials of a misbehaved vehicle. The objective of using multi-signature is to increase the creditability of revocation requests. Our experiments and extensive evaluations show that our scheme can revoke a large number of pseudonyms with minimum storage and computation overhead.

One of the most promising technologies that will be used for charging Electric Vehicles (EVs) is wireless charging. By employing this technology, an EV is able to charge its battery without the need to stop. The charging stations should authenticate the EVs before allowing them to charge their batteries. Traditional digital signature reveals the real identity of the driver and degrades the location privacy. In this paper, we propose an efficient privacy-preserving authentication scheme for EVs wireless charging scenario. Our objective is not only to enable the EVs and the charging station to perform mutual authentication but to protect the privacy of the drivers without the need of a Third Trusted Party (TTP). The EVs use blind signature for authentication with the charging station to protect their privacy. Then, they use hash chains to authenticate themselves to the charging pads which are limited constraint devices. The verification of a hash chain requires performing simple hash operations which is computationally cheap and light-weight. The communication between the EVs and the charging station is secured by establishing an encrypted session. Our extensive evaluations demonstrate that our scheme preserves the drivers' privacy while mutually authenticate the EVs and the charging pads with low communication and computation overhead.

Ride sharing can reduce the number of vehicles in the streets by increasing the occupancy of vehicles, which can facilitate traffic and reduce crashes and the number of needed parking slots. Autonomous vehicles can make ride sharing convenient, popular, and also necessary because of the elimination of the driver effort and the expected high cost of the vehicles. However, the organization of ride sharing requires the users to disclose sensitive detailed information not only on the pick-up/drop-off locations but also on the trip time and route. In this paper, we propose a scheme to organize ride sharing and address the unique privacy issues. Our scheme uses a similarity measurement technique over encrypted data to preserve the privacy of trip data. The ride sharing region is divided into cells and each cell is represented by one bit in a binary vector. Each user should represent trip data as binary vectors and submit the encryptions of the vectors to a server. The server can measure the similarity of the users' trip data and find users who can share rides without knowing the data. Our analysis has demonstrated that the proposed scheme can organize ride sharing without disclosing private information. We have implemented our scheme using Visual C on a real map and the measurements have confirmed that our scheme is effective when ride sharing becomes popular and the server needs to organize a large number of rides in short time.

Given the scalability of the advanced metering infrastructure (AMI) networks, maintenance and access of certificate revocation lists (CRLs) pose new challenges. It is inefficient to create one large CRL for all the smart meters (SMs) or create a customized CRL for each SM since too many CRLs will be required. In order to tackle the scalability of the AMI network, we divide the network into clusters of SMs, but there is a tradeoff between the overhead at the certificate authority (CA) and the overhead at the clusters. We use Bloom filters to reduce the size of the CRLs in order to alleviate this tradeoff by increasing the clusters' size with acceptable overhead. However, since Bloom filters suffer from false positives, there is a need to handle this problem so that SMs will not discard important messages due to falsely identifying the certificate of a sender as invalid. To this end, we propose two certificate revocation schemes that can identify and nullify the false positives. While the first scheme requires contacting the gateway to resolve them, the second scheme requires the CA additionally distribute the list of certificates that trigger false positives. Using mathematical models, we have demonstrated that the probability of contacting the gateway in the first scheme and the overhead of the second scheme can be very low by properly designing the Bloom filters. In order to assess the scalability and validate the mathematical formulas, we have implemented the proposed schemes using Visual C. The results indicate that our schemes are much more scalable than the conventional CRL and the mathematical and simulation results are almost identical. Moreover, we simulated the distribution of the CRLs in a wireless mesh-based AMI network using ns-3 network simulator and assessed its distribution overhead.

In this paper, we propose an efficient scheme that utilizes symmetric-key-cryptography and hashing operations to collect consumption data. The idea is based on sending masked power consumption readings from the meters and removing these masks by adding all the meters' messages, so that the utility can learn the aggregated reading but cannot learn the individual readings. We also introduce a key management procedure that uses asymmetric key operations, but unlike the power consumption collection that is done very frequently, the key management procedure is run every long time for key renewals. Our evaluations indicate that the cryptographic operations needed in our scheme are much more efficient than the operations needed in the existing schemes. In addition, we have shown that the proposed scheme can preserve the consumers' privacy and provide high protection level against collusion attacks. Finally, ns-3 simulation results demonstrate that the network performance of the proposed scheme outperforms the performance of the existing schemes due to reducing the packet size and computational overhead.

In this paper, we propose a trust-based and privacy-preserving fine-grained data retrieval scheme for mobile social networks (MSNs). The scheme enables users to create a log of trusted users who store (or are interested in) some topics related to a subject of interest. A subject is a broad term that can cover many fine-grained topics. In creating logs, we leverage friends-of-friends relationships and transferrable trust concept. Each user trusts its friends and the friends of friends. If a friend is not interested in a subject, he can help his friend in creating the log by linking the friend to his friends without knowing the subject to preserve privacy. In order to reduce the storage and computation overhead, we use Bloom filters to store the topics. A distinctive feature in our scheme is that it can query users who possess a fine-grained topic, rather than querying users who are interested in the broad subject but they may not have the specific topic of interest. We analyze the security and privacy of our scheme and evaluate the communication and computation overhead.

Wireless communication capabilities of Vehicular Ad Hoc Networks (VANETs) have been utilized in various cutting-edge applications such as Vehicular Social Networks (VSNs). One of the benefits of VSNs is sharing of common-interest information among vehicle drivers. Drivers may benefit from identifying neighbors that have interest common with them along with the extent of their interest. However, there are some privacy issues that should be addressed. Revealing the nature and degree of interests (DOI) of drivers can be in violation of their privacy. In this paper, we propose an efficient chatting scheme among drivers that preserves such privacy. We use attribute based encryption (ABE) technique for anonymous common interest verification and homomorphic encryption technique for anonymous DOI verification. Moreover, we propose an efficient search mechanism to enable vehicles to check if they have common interests with low computation and communication overhead. To secure conversation, a key agreement protocol is used to enable the drivers that have the same interest and the desired DOI to establish a shared secret key. Our extensive evaluations demonstrate that our scheme can successfully preserve drivers' privacy with low communication and computation overhead.

In Vehicular Ad Hoc Networks (VANETs), the roadside units (RSUs) need to know the number of vehicles in their vicinity to be used in traffic management. However, an attacker may launch a Sybil attack by pretending to be multiple simultaneous vehicles. This attack is severe when a vehicle colludes with others to use valid credentials to authenticate the Sybil vehicles. If RSUs are unable to identify such an attack, they will report wrong number of vehicles to the traffic management center, which may result in disseminating wrong traffic instructions to vehicles. In this paper, we propose a cross-layer scheme to enable the RSUs to identify such Sybil vehicles. Since Sybil vehicles do not exist in their claimed locations, our scheme is based on verifying the vehicles' locations. A challenge packet is sent the vehicle's claimed location using directional antenna to detect the presence of a vehicle. If the vehicle is at the expected location, it should be able to receive the challenge and send back a valid response packet. In order to reduce the overhead and instead of sending challenge packets to all the vehicles all the time, packets are sent only when there is a suspicion of Sybil attack. We also discuss several Sybil attack alarming techniques. The evaluation results demonstrate that our scheme can achieve high detection rate with low probability of false alarm. Additionally, the scheme requires acceptable communication and computation overhead.

With the large increase in the number of registered vehicles, the congestion and slow traffic problems are expected to worsen. Vehicular Ad Hoc Networks (VANETs) can play a great role in avoiding these problems by sending guidance to vehicles to pursue alternative routes. However, the published schemes require vehicles to report their future routes which can seriously violate privacy. In this paper, we present privacy-preserving route reporting scheme that suits VANET-enabled traffic management rather than warning vehicles after congestion happens. Vehicles provide encrypted segment-based route information to road side units (RSUs). Instead of sending one message for each route segment, all the segments' data can be collected by one message using homomorphic encryption. RSUs compute the encryption of the expected number of vehicles in each segment of the road without knowing the actual routes of vehicles. Each RSU shares the vehicles' routes information with a traffic management center (TMC), which decrypts the expected total number of vehicles at different segments of the road without knowing the individual vehicles' routes. Then, it conducts analysis and sends predictions and recommendations back to the RSUs. Passing vehicles solicit hints from RSUs on the expected traffic condition in order to decide to take an alternating route if there is a potential of congestion or slow traffic in its main route. Our analysis and evaluation results demonstrate that our scheme can preserve the privacy of the drivers' future routes in an efficient and secure way.

In vehicular ad hoc networks, vehicles should report events to warn the drivers of unexpected hazards on the roads. While these reports can contribute to safer driving, vehicular ad hoc networks suffer from various security threats; a major one is Sybil attacks. In these attacks, an individual attacker can pretend as several vehicles that report a false event. In this paper, we propose a secure event-reporting scheme that is resilient to Sybil attacks and preserves the privacy of drivers. Instead of using asymmetric key cryptography, we use symmetric key cryptography to decrease the computation overhead. We propose an efficient pseudonym generation technique. The vehicles receive a small number of long-term secrets to compute pseudonyms/keys to be used in reporting the events without leaking private information about the drivers. In addition, we propose a scheme to identify the vehicles that use their pool of pseudonyms to launch Sybil attacks without leaking private information to road side units. We also study a strong adversary model assuming that attackers can share their pool of pseudonyms to launch colluding Sybil attacks. Our security analysis and simulation results demonstrate that our scheme can detect Sybil attackers effectively with low communication and computation overhead. Copyright © 2015John Wiley & Sons, Ltd.

Given the large geographic deployment and scalability of the Advanced Metering Infrastructure (AMI) networks, it is inefficient to create one large certificate revocation list (CRL) for all the networks. It is also inefficient to create a CRL for each meter having the certificates it needs because too many CRLs will be required. It is beneficial to balance the size of the CRLs and the overhead of forming and distributing them. In this paper, the certificate authority (CA) groups the AMI networks and composes one CRL for each group. We use Bloom filter to reduce the number of CRLs by increasing the groups size with acceptable overhead on the meters. However, Bloom filters suffer from false positives which is not acceptable in AMI networks because meters may miss important messages. We propose a novel scheme to identify and mitigate the false positives by making use of the fact that Bloom filters are free of false negatives. The meters should contact the gateway to resolve the false positives. We use Merkle tree to enable the gateway to provide efficient proof for certificate revocation without contacting the CA. We derive a mathematical formula to the probability of contacting the gateway as a function of the filter's parameters. We will show that this probability can be low by properly designing the Bloom filter. In order to assess the performance and the applicability of the proposed scheme, we use ns-3 network simulator to implement the scheme in a IEEE 802.11s-based mesh AMI networks. The results demonstrate that our scheme can be used efficiently for AMI networks.