Memristor Device for Security and Radiation Applications

Part of the Analog Circuits and Signal Processing book series (ACSP)


The first physical demonstration of a non-volatile resistive-switching memory based on the nanostructured Pt/TiO2/Pt metal/insulator/metal stack from HP, has spurred the scientific community to develop memristive devices for a wide variety of applications. Owing to low-power and ultra-fast switching capabilities, memristors with nanoscale thickness geometry have been extensively investigated as potential replacements for flash memory technology in simple analog- and digital- computing applications. In Addition, both scalability and interconnectivity of memristors, through brain-inspired computing, have sparked a considerable move toward advancing of next-generation intelligent computing systems. On the horizon, other potential uses of the memristor have also emerged, particularly in sensing where attractive measurable changes in the IV fingerprint of some device configurations have been demonstrated under certain types of extrinsic disturbances. Additionally, the unique and chaotic IV response of some memristors opens the door for potential applications in hardware security. This chapter reports on novel approaches to utilize the electrical characteristics of the fabricated memristive devices for radiation sensing and security applications.


Memristor Micro Nano Radiation Key Characteristics Security Switching IoT Communication 

5.1 Introduction

The first physical demonstration, in 2008, of a non-volatile resistive-switching memory based on the nanostructured Pt/TiO2/Pt metal/insulator/metal stack from HP [1], has spurred the scientific community to develop memristive devices for a wide variety of applications. Owing to low-power and ultra-fast switching capabilities, memristors with nanoscale thickness geometry have been extensively investigated as potential replacements for flash memory technology in simple analog- and digital- computing applications [2, 3, 4, 5, 6, 7]. In Addition, both scalability and interconnectivity of memristors, through brain-inspired computing, have sparked a considerable move toward advancing of next-generation intelligent computing systems [8, 9, 10].

On the horizon, other potential uses of the memristor have also emerged, particularly in sensing where attractive measurable changes in the IV fingerprint of some device configurations have been demonstrated under certain types of extrinsic disturbances [11, 12, 13]. Additionally, the unique and chaotic IV response of some memristors opens the door for potential applications in hardware security [14, 15]. This chapter reports on novel approaches to utilize the electrical characteristics of the fabricated devices presented in Chaps. 2 and 3 for sensing and security applications.

5.1.1 Memristor-Based Sensing

A growing number of fundamental studies on nano-sized memristors are emerging in sensing applications [16, 17, 18]. Although this field is yet to be developed, biological implementation holds the biggest share where implant- or portable-based memristor sensors are nowadays considered highly attractive for reducing the overall operational costs of vital prognostic tools [19, 20].

In bio-sensing, geometry and chemical adaptations of the nano-insulator component have both been reported essential to establish both the fluidic operation and the label-free recognition (specific or non-specific) of target species with the use of the memristive electrical fingerprint for sensing [18, 12]. Typically, the alteration of the IV characteristics (e.g., voltage gap or ROFF/RON ratio [11, 13, 21]) in response to an external actuation (i.e., a change in physical or chemical environment) is considered to be the lead approach for exploiting the underlying operational features of memristor devices in sensing applications.

This chapter reports on a novel sensing area of using memristive devices for environmental health and safety applications. Ionizing electromagnetic radiation detection and dosimetry has been a worldwide challenge for general security purposes, particularly with regard to human exposure to x-rays and γ-rays. These radiations are extensively deployed for good purposes in research, medical imaging, radiation therapy, manufacturing, and environmental remediation [256–258]. They are also very frequently encountered in nuclear power plants and military industries, due to being primarily associated with the production, handling, and storage of hazardous materials and radioactive wastes [22, 23]. However, these radiations can be harmful due to their accumulative susceptibility and to their deleterious ionizing nature [24, 25]. Thus, frequent monitoring is mandatory to enhance public safety against undesired exposure due to accidental or hidden threats.

Classic radiation-protection dosimeters, based on (i) gas-ionization chambers [26], (ii) inorganic or organic scintillation (i.e., thermoluminescent) crystals [27, 28], (iii) radiographic or radiochromic dyes, [29] and (iv) semiconductor technologies [30, 31], have multiple shortcomings associated with either high power supply requirement, time consuming readout and calibration, lack of accuracy, and low spatial resolution or dynamic sensitivity with accumulated dose or temperature change [32]. Continuous advancements of existing technologies are hence necessary to simultaneously tackle the portability, recyclability, and real-time monitoring faults.

The novel radiation sensing concept utilizing the capabilities of memristive devices can be explored in a close pathway to that established with semiconductor field-effect transistors (MOSFETs). Radiation detection with a MOSFET device is achieved via in situ trapping of charge carriers (e.g., electrons and holes) ejected from the insulator oxide layer as a result of a photoelectric effect. A shift in the threshold voltage (i.e., minimum gate-to-source voltage differential) is measured across a transistor and translated into a linear function of the accumulated absorbed dose [32, 33]. Similar to MOSFETs, radiation-induced photoelectric interactions can be emulated in memristive metal-oxide systems. The non-volatility and low power consumption of the memristor give the device the potential to replace the existing semiconductor-based radiation detectors. Sensing in this case would be achieved if measurable changes in the memristance IVcharacteristics are observed, provided that standard device operation is maintained. In recent space-related studies, metal-oxide memristors (e.g., Pt/TiO2–x(26 nm)/Pt and TiN/Ta/TaOx(10 nm)/TiN) were shown to have substantial hardness to ionizing electromagnetic radiations, which was mainly ascribed to radiation transparency due to nanoscale device thicknesses [34, 35, 36, 37, 38, 39, 40]. Predictive simulations with Pt/TiO2–x/Pt memristor, passively exposed to 1 meV γ-rays, projected that the probability of interaction becomes non-negligible beyond micron-scale oxide thicknesses [36].

5.1.2 Memristor-Based Security Applications

Ensuring that security aspects and key performance indicators (KPIs) are met is a challenge that adds value to any innovation in the technology domain. Hence, the evolution in electronic devices works hand in hand with security enhancement. The nonlinear IV characteristic of memristors attracts the attention toward device deployment in security applications. Even though many researchers have highlighted the difficulties of producing similar memristor device behavior as a challenge for traditional memory and logic application [41], this randomness [42] and uniqueness of the memristor device behavior can be utilized for security applications.

Few secure communication systems are proposed in literature based on memristor devices. The work presented in the [14, 15] proposed building secures physical unclonable functions (PUFs) using the significant resistance variations of memristive crossbar. Encryption and decryption between the communicating devices using identical keys are considered an obstacle in this system, owing to the unpredictable behavior variations of the identical crossbars. Alternatively, the work presented in this chapter utilizes the uniqueness property of the fabricated nano/micro-thick memristor device to generate master and session keys. Moreover, a novel secure and efficient IoT conference communication system is proposed based on the unique memristive-based keys generated at the connected devices.

Many group secure communication systems are provided in literature. Burmester and Desmed (BD) [43] provided numerous conference key systems. Just and Vadenay [44] showed that the authentication feature is missing in BD system. Du et al. [45] proposed a modified synchronous counter-based scheme. Through such enhancements, Shim [46] showed that the verification of all the messages from all applicants is required to avoid the insider impersonation attack. The work in [47] proposed the practical enhancements of BD authenticated group key agreement systems that identify malicious insiders. This is achieved by using the trusted arbiter if the cheating has occurred in Mobile Ad hoc Network (MANET).

All the preceding systems are application layer-based algorithms using public key cryptography, which is not as efficient as symmetric key cryptography due to the required heavy computational cost. Alternatively, the work proposed in this chapter is the first to introduce secure IoT conference communication system based on memristor hardware, using symmetric key cryptography [48, 49].

5.2 Memristive-Based Radiation Sensing

The extensive fabrication and electrical testing mentioned in Chap. 2 have enabled the use of micro-thick TiO2memristors based on the optimal Al/Cu–D2 structure for radiation sensing experiments. Due to the great understanding of the basic electronic behavior of these devices without radiation; it is possible to ascribe novel observations to interactions developing with the radiation sources.

A cesium-137 γ-ray emitting source (type-D disk, Eckert & Ziegler, Germany), with an active diameter of 5 mm, a radioactivity of 18.1 μCi (0.67 MBq), and a primary emitted photon energy of 662 keV, was applied during the radiation sensing experiments. Radiation exposure tests were performed by placing the radioactive source on top of the hybrid Al/Cu memristor, facing the aluminum electrode. Radiation effects were monitored at room temperature, via real-time current measurement under non-switching −0.5 V pulse bias (pulse width 0.1 s, hold time 0.1 s).

Prior to radiation exposure, fresh Al/TiO2/Cu–D2 devices were electroformed at −5 V for 30 s and tested against ±1 V sweep cycling, as reference conditions. Passive exposure to 662 keV γ-rays was first carried out by generally placing a device in contact with a Cs-137 source for a certain period of time (e.g., 5 min). Afterward, the exposure is ceased and the resistance of the device is measured and compared to the last state recorded prior irradiation. Using this approach, no measureable change in resistance value could be observed even after prolonged exposure durations (>20 min). Failure to achieve passive sensing could either be due to (i) total device transparency to γ-rays (i.e., very low probability of radiation deposition within the active layer due to highly penetrating energy) [36], or to (ii) fast non-radiative recombination of induced electron-hole pair carriers in the semiconductor junctions [50]. Further investigations were performed in active sensing mode by continuously applying a non-switching ON voltage of −0.5 V (i.e., ≤1 V) to the memristor throughout radiation exposure, while monitoring the fluctuations in current measurements. A prior blank run was carried out in absence of the radiation source to verify the absence of switch-on event that could potentially be electrically induced throughout the duration of the experiment. According to the blue baseline reported in Fig. 5.1, no measurable change in current was observed for about 850 s (~14.2 min) under the −0.5 V bias.
Fig. 5.1

Absolute current measured through a D2 device under constant −0.5 V bias, before exposure (dashed blue baseline) and in contact with Cs-137 (662 keV) radioactive γ-ray source (black line). After the blank run, the device was reset to its initial resistance value prior to radiation exposure. Measurements were collected at a compliance current of 100 nA

After resetting the device to the original resistance value, the same experiment was repeated, during which the radiation source was put in contact with the operational device at 375 s from the beginning of the run. The initial nanoscale flowing current under −0.5 V bias gradually increased by 100-fold within 150 s window until it reached a value of 100 nA, which was fixed as the compliance value. When the radiation source was removed after 200 s of exposure, the current instantly dropped to 5 nA, and another turn-on was recorded 50 s earlier than that observed when the radiation was applied. Compared with the blank data, the first current jump reflects some probability of a radiation-induced conduction event. The second jump suggests persisting radiation-induced phenomena that would have exerted a synergy with the small voltage bias, both inducing faster switch-on, in agreement with associative effects, O’Kelly et al. recently explored with optical light and voltage pulses in neuromorphic nanowire devices.

To ascertain the probability of radiation-induced events in facilitating the turn-on behavior of micro-thick memristors, changes in the full memristive hysteresis pattern were further explored throughout eleven consecutive ON/OFF switching tests, as illustrated in Fig. 5.2. For these runs, a fresh Al/TiO2/Cu–D2 device was electroformed just enough to be turned on near—2 V in the negative sweep—that is at twice the voltage range previously explored in Fig. 2.6, to allow larger margin for discrimination of any voltage-related hysteresis shifts that would be caused by irradiation effects. For the first three successive ON/OFF sweeps done before irradiation, (see Fig. 5.2a, cycles 1, 2 and 3/black curves) the turn-on threshold voltage was about—1.84 V (±SD = 0.14 V)—with a small spread (see black dual arrow) showing good electrical endurance. During irradiation with the Cs-137 662 keV γ-ray source (see Fig. 5.2a), cycles 4, 5 and 6/red curves), the initial turn-on voltage corresponding to cycle 4 (equal to −1.70 V) was found within the spread of measurements of the preceding blank runs. Following to cycle 4, faster switch-on was observed in both cycles 5 and 6 (see red arrow), with both experimental turn-on voltage values being outside the 3 × SD range of the blank measurements. The faster turn-on indicates the formation of extra conductive pathways across the memristor during γ-irradiation. However, the time lag observed on sensing typical shift indicates threshold and time-dependent accumulative dose effects, both controlling the limit of detection and the response time of the memristor. To understand these observations, five blank runs were repeated subsequently after the radiation source was removed (Fig. 5.2b). In the starting blank cycle 7, the memristor turned further faster than during the concluding cycle 6 of irradiation tests. During the next cycles 8 through 11, the threshold turn-on voltage progressively turned back close to its original value recorded before irradiation (see horizontal blue arrow). These results further confirmed a temporal dissipation or decay of radiation-induced interactions throughout the memristive material.
Fig. 5.2

Evolution of eleven consecutives ON/OFF switching cycles of an Al/Cu-D2 memristor. a “three consecutive blank runs before irradiation” (cycles 1–3 corresponding to black traces), and “three consecutive active sensing testing under exposure to Cs-137 662 keV radioactive γ-ray source” (cycles 4–6 associated with red traces); b “five consecutive blank runs repeated after irradiation” (cycles 7–11 corresponding to blue traces). Prior to testing, the Al/Cu-D2 device was electroformed just enough to make functional within −2 V/+ 1 V window. The compliance current was set to 1 mA in the negative sweep polarity and to 10 mA in the positive sweep mode

Perceptible changes in the size of the negative hysteresis loop, in both Figs. 5.2a and b, provide further evidence of the sensing phenomenon from a different view that is based on the evolution of the hysteretic gap between the turn-off and turn-on currents. In this case, the ability of the memristor to detect γ-rays could also be traced from measurable changes seen in the ROFF/RON ratio of the device. Since the turn-on current was fixed by the compliance value, the changes in the size of the hysteresis gap reflected gradual modification of the ROFF value. In Fig. 5.2a, the ROFF value concluded from the turn-off current in the negative loop is found to be going further smaller under γ-irradiation. Since the ionizing radiations used are several orders of magnitude more energetic than the semiconductor’s bandgap, the deposited energy can create a photoelectric effect that generates a population of in situ secondary electrons within the switching material. The radiation sensing mechanism would hence be established on reading a lower device OFF resistance state (or higher OFF current) when enough charge trapping or tunneling leakage [51] is generated across the device. Both smaller OFF resistance state and shorter turn-on onset support the idea of a synergistic actuation pathway in active sensing mode; while γ-ray interactions could have participated in generating additional population of labile secondary electrons/holes pairs by photoelectric effect; the external electric field applied would have substantially minimized the recombination rate of these carriers by promoting charge transport. In Fig. 5.2b, seeing the gap gradually restoring back to its original magnitude in absence of the radiation source (as indicated by the tilted blue arrow), concludes that the memristor’s response time is not instantaneous and would require further material optimization for real-time monitoring applications [52].

5.3 Memristor-Based Secure Communication

5.3.1 IV Characteristics and Key Generation

The memristive key generation scheme presented in this section depends mainly on the uniqueness property of the electrical characteristics of the fabricated memristor devices. This is realized and observed in both micro-thick and nano-thick memristor devices presented in Chaps. 2 and 3, respectively. Micro-Thick TiO2 Devices

As presented in Chap. 2, the micro-thick TiO2memristor (Al/Cu–D2) was initially in the OFF state. To condition the device for fully switching operation, it was necessary to electroform the device by applying −5 V for approximately 30 s until the device reaches compliance (0.1 A). This step is reported to facilitate switching in TiO2 by creating conductive filaments within the TiO2 [53]. Once the device was electroformed, ±1 V sweep was applied to switch the device OFF and ON (Fig. 5.3). To examine the memristor for security applications, it is found more efficient to operate the device without prior electroforming for two main reasons, closely related to power consumption and to fingerprint uniqueness. Firstly, the maximum current passing through the device before creating conducting filaments is in the micro-ampere range (Fig. 5.4) which reduces the power consumption of the device to ~1.5 µW compared to 0.1 W for the electroformed state. Secondly, the gradual increase in the current makes the IV curve for the un-electroformed device much richer for the keys to be extracted, as inferred from comparing data presented in both Figs. 5.3 and 5.4. The IVcharacteristics of different memristor devices fabricated through the same process, using similar starting material and processing conditions, as seen in Fig. 5.4, demonstrate a high degree of electrical IV individuality (overall low cross over between the IV fingerprints), which could be useful in generating distinctive keys. For example, if Device 1 and 2 are distributed to hosts 1 and 2, respectively, each host can generate unique key even if the same electrical test is applied to both devices. The idea of extracting key from memristor IV characteristics is explained here. As shown in Fig. 5.5 if certain voltage sweep is applied across a memristor device this will result in unique current values. The key can be generated by digitizing the IV curve based on the required key size which will depend on the used encryption mechanism.
Fig. 5.3

Electrical characteristics of the fabricated micro-thick TiO2 memristor (Al/Cu-D2) memristor after electroforming

Fig. 5.4

Electrical characteristics of the fabricated micro-thick TiO2 memristor (Al/Cu-D2) without prior electroforming

Fig. 5.5

Key generation example from fabricated memristor device Nano-Thick HfO2 Device

The unipolar switching behavior presented in Chap. 3for the fabricated HfO2memristive crossbar follows the well-known filamentary-based switching mechanism. In such behavior, the creation and rupturing of the conductive filaments are considered probabilistic (rather than deterministic) processes. This can be mainly explained due to (i) (i) fabrication process variations [41] and (ii) the randomness in the number and the strength of the created filaments [42, 54]. As mentioned in Chap. 3, the thickness of the oxide layer is too small (10 nm) which leads to significant fabrication process variations due to the increased challenge in ions deposition. Moreover, the ions move randomly under the application of electric field. Thus, the number and the position of the created filaments vary within the same device and between the identical devices as well, under applying the same sweep voltages. This affects the strength of the formed conducting paths and consequently different ions profiles are obtained during reset operation.

Figure 5.6a and b show the IV curves obtained from identical 900 × 900 µm2 and 200 × 200 µm2memristor devices, respectively. As shown, each device has its own characteristic under the application of the same sweep voltage. This means that unique keys can be generated from the memristive devices that are supposed to be identical.
Fig. 5.6

IV characteristics obtained from identical devices of same dimensions (a) 900 × 900 µm2 (b) 200 × 200 µm2

Figure 5.7 presents the consecutive set events within one memristive device. After each set operation, the device is reset by applying 5 V sweep voltage and 0.1 A compliance current. The reset curves are not included in Fig. 5.7 to achieve more clear presentation. It can be observed that during each switching event a new IV characteristic is obtained with missing the ability to retrieve the preceding states. This powerful feature is utilized in the security system presented in the following section to generate session keys in the different devices.
Fig. 5.7

IV characteristics obtained from one memristor device with consecutive set/reset operations

Figure 5.8 shows the system block diagram of the proposed memristive-based key generation scheme. It is clear that a capacitor (that is initially reset) is connected to the memristive device to be fed gradually and accumulatively during the application of each voltage pulse. The resultant voltage on the capacitor is fed to an analog to digital convertor (ADC) with the desired sampling rate to generate the key. The importance of using the capacitor is mainly raised from its accumulating property. For instance, if two memristor devices have the same current state under the application of a certain pulse, this will still lead to different output voltages at the capacitor that was initially fed with different preceding states.
Fig. 5.8

System block diagram of the proposed memristive-based key generation

5.3.2 Proposed IoT Conference Communication System

In this section, a memristor-based system that provides secure IoT conference communication among different devices is proposed. The provided system utilizes the advantage of the uniqueness property of the memristor devices presented in the preceding section to generate session keys. The proposed IoT conference communication system assumes that each of the different devices and TTP owns memristor devices with unique IVcharacteristics as shown in Fig. 5.9. Moreover, each IoT device is supposed to have an initial key that is secret and used to communicate with TTP. Table 5.1 provides the acronyms and definitions used for the proposed security system. For illustration, if for instance device A wants to share messages secretly with devices B and C, the below steps should be followed. Details of communication messages are presented in Fig. 5.9.
Fig. 5.9

Proposed Memristor-based security approach. Devices A and B can initiate communication through TTP. All keys are generated using unique memristor devices

Table 5.1

Proposed system acronyms and definitions




Unique secret key generated by TTP to share information among IoT device A, B, C


Unique secret key generated by A to share information among IoT device A, B, C


Secret Key between TTP and device A


Secret Key between TTP and device B


Secret Key between TTP and device C


Voltage applied across the device memristor


The width of the applied voltage pulse across the device memristor


Timestamp generated at device i


Nonce generated at device i


Encrypted with key K


Address of device I

  1. Step 1

    To start the process, host A will contact the TTP informing it with the address of the nodes it wants to initiate a communication with. A sends TTP the addresses of B and C along with a nonce RA. The Message M1 is as follows:

$$M_{1} = (R_{A} \left| {\left| B \right|} \right|C)$$

After TTP receives the message from A and checks its content, TTP generates a session key KABC using its memristor and a timestamp TTP. TTP creates three messages encrypted with KAT, KBT, and KCT. These messages are sent back to A which is responsible for sharing the session key KABC with B and C. The message sent back to A is as follows:

$$M_{2} = \, eK_{AT} \left( {R_{A} \left| {\left| {K_{ABC} } \right|} \right|B||C} \right)_{ } \left| {\left| { \, eK_{BT} ( \, T_{TP} } \right|} \right| \, K_{ABC} \left| {\left| A \right|} \right|B\left| {\left| {C)} \right|} \right| eK_{CT} \left( {T_{TP} \left| {\left| { \, K_{ABC} } \right|} \right|A\left| {\left| B \right|} \right|C} \right)$$
  1. Step 2

    key KABC. A generates tABC and VABC and uses its memristor to generate a new secure session key KABCnew and timestamp TA then forwards the messages from TTP. A also sends B and C another message to verify the used session key and share the newly generated KABCnew. A sends B the following:

$$M_{3} = eK_{ABC} \left( {K_{ABCnew} \left| {\left| {T_{A} } \right|} \right|B} \right)_{{}} \left| {\left| { \, eK_{BT} (T_{TP} } \right|} \right| \, K_{ABC} \left| {\left| A \right|} \right|B||C)$$

And A sends C the following:

$$M_{5} = eK_{ABC} \left( {K_{ABCnew} \left| {\left| {T_{A} } \right|} \right|C} \right)_{{}} \left| {\left| { \, eK_{CT} (T_{TP} } \right|} \right| \, eK_{ABC} \left| {\left| A \right|} \right|B||C)$$
  1. Step 3

    After B and C receive message from A, they verify the received messages and key and then send back another message containing their address and a fresh timestamp TB and TC at B and C, respectively; informing A that they are now aware of the communication session key that is used in future communications. B and C send messages M4 and M6, respectively. The messages are summarized as follows:

$$M_{4} = \, eK_{ABCnew} \left( {T_{B} ||A} \right)$$
$$M_{6} = \, eK_{ABCnew} \left( {T_{C} ||A} \right)$$
  1. Step 4

    C sends B a message to inform it that it is aware of the new session key KABCnew and achieve authentication. C sends a message containing the address of B and its timestamp TC. The message is as follows:

$$M_{7} = eK_{ABCnew} (T_{C} ||B)$$
  1. Step 5

    Finally, B receives the message and replies with a message containing its timestamp TB and the address of C. The message is as follows:

$$M_{8} = eK_{ABCnew} (T_{B} ||C)$$

5.3.3 Security Analysis

A formal verification method called Scyther [55], [56] is used to verify the security of the proposed system. Scyther is a free formal analysis tool that provides a set of claims to test secrecy of information, synchronization, and authentication between communication parties. Synchronization indicates that messages sent are sent and received by the intended communication partners. It also means that exchanged messages are in order and their content is not modified. Scyther also tests the aliveness of a communication party, which basically means that the party is active and executing some events [289], [290]. A set of claims (tests) were set up in the tool to test the secrecy of information (i.e. the session keys, timestamps and nonces) and synchronization. Figure 5.10 shows the output of the verification test for the defined claims at devices A, B, C, and TTP. The test verifies the secrecy of the exchanged timestamps, nonces, and session keys. The synchronization between them is also verified. A detailed security analysis and the mapping between the Scyther test results and the fundamental security requirements are provided as follows.
Fig. 5.10

Output of Scyther for tested claims at aTTP, b device A, c device B, and d device C Mutual Authentication

Synchronization between A, B, C, and TTP was verified through claims (MEM,1A), (MEM,1B), (MEM,1C), and (MEM,1TTP). Passing synchronization test between the devices indicates that messages are sent and received by the intended parties in the right order and no manipulation has taken place. This ensures that the communicating entities can verify each other’s identity. Taking the communication between A device and TTP as an example, both platforms are sure of who sent the message because of the use of the secret key. Messages sent are fresh due to the existence of timestamps and both platforms can verify that the exchanged messages are actually intended to them, due to the concatenation of the address of the destination in the message. Confidentiality

The timestamps, nonce, and session keys exchange are verified for secrecy throughout the interaction by claims (MEM,2A to MEM,8A), (MEM,2B to MEM,7B), (MEM,12TTP to MEM,14TTP), and (MEM,2C to MEM,8C). The data remain confidential throughout the communication at A, B, C and TTP. At any time, only the owner platform can access the output of the request because of the encryption. In addition, the user request and timestamps are also encrypted and remain confidential. The essential information for decryption requires the knowledge of the secret keys. Integrity

Synchronization ensures that the exchanged information is not modified without being detected, claims (MEM,1A), (MEM,1B), (MEM,1C), and (MEM,1TTP) protect data integrity. The integrity of request, the output of the request, and all the timestamps are guaranteed at all times. Thus, any change or manipulation in messages is detected. Authorization

Claims proved that the exchanged information is kept secret from non-authorized parties. Only parties with proper decryption information are able to access the data. These keys remain confidential as proven by claims (MEM,7A, MEM,6B, and MEM,7C), therefore providing protection from unauthorized access attacks. When the user accesses the application and provides his/her credentials, this information is verified to decide whether to grant the user access to the application services or not. Moreover, by providing mutual authentication, platforms are able to verify each other, and any communication request or message sent by a non-trusted platform is ignored. The request, timestamps, and the output of the request are all confidential and can only be decrypted by authorized platforms. Replay Attacks

The proposed system uses nonces and timestamps to provide a proof of freshness of messages. The timestamps and nonces remain secret and cannot be modified, and therefore, protection from replay attack is achieved.


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Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  1. 1.Khalifa University of Science and TechnologyAbu DhabiUnited Arab Emirates

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