Performance Analysis. (a) Portfolio Yield (Finance Charge Collections during the Due Period divided by Principal Receivables in the Trust as of the first day of the Due Period) ___________%
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Performance Analysis. We analyze the proposed solution in terms of the correctness, the security and the overall comparison with related solutions. For the security verification, we refer to [8,18–22] to evaluate session key security, mutual authentication, perfect forward security, and data integrity. Moreover, we also demonstrate that the proposed solution is safe when suffering replay attacks, impersonation attacks, privileged insider attacks, and stolen-verifier attacks.
Performance Analysis. In this section we analyze the characteristics of the key generated by EKA in terms of our design goals of random- ness, time-variance and distinctiveness. The analysis utilizes actual EKG data from 31 subjects obtained from the MIT PhysioBank database (xxxx://xxx.xxxxxxxxx.xxx/physiobank/) for our validation. Each data value has a time-stamp associated with it, as the data was sampled at 125Hz, there is one EKG value every 8 msec. The EKA implementation and analysis was done using Matlab. In this section section, the notations KeyA and KeyB are used to denote keys generated by arbitrary sensors s1 and s2 (located in the same BSN) which are in the process of exchanging keys, respectively.
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Performance Analysis. This section provides performance analysis of the proposed protocol in terms of the computation complexity and the communication complexity focused on the login phase and the authenticated key agreement phase only. Performance evaluation is provided by comparing the proposed protocol with Xxxxxxx et al.’s [11] protocol. The computational costs are measured by checking the execution time. They are generally conducted by focusing on operations performed by each party within the protocol. Therefore, for analysis of the computational costs, we concentrated on the operations that are conducted by the parties in the network: namely a patient, a server and doctor/nurse. In order to facilitate the analysis of the computational costs, we define the following three notations. Th: time to execute a one-way hash operation Ts: time to execute a symmetric key encryption or decryption Te: for the time to execute an ECC-160 encryption or decryption. We performed an experiment using Crypto++ Library on a system using the 64-bits Windows 7, 3.2 GHz processor, 4 GB memory, Visual C++ 2013 Software, SHA-1 hash function, AES symmetric encryption/decryption and ECC-160 operation [2]. According to the experiment, Th is nearly 0.0002 seconds on average, Ts is nearly 0.0087 seconds and Te is nearly 0.6 seconds, respectively. Table 3 shows a comparison of the computational cost between the related protocols. Xxxxxxx et al.'s [11] protocol takes about 3.725 sec and the proposed protocol takes about 3.672 sec. As a result, the proposed protocol has lower computational overhead than Xxxxxxx et al.’s [11] protocol. Table 3. Computation cost comparisons. EntityProtocol Patient TS Doctor/Nurse Total Xxxxxxx et al. [11] 5Th+3Ts+2Te 6Th+7Ts+2Te 5Th+4Ts+2Te 16Th+14Ts+6Te The proposed 4Th+2Ts+3Te 4Th+4Ts+1Te 4Th+2Ts+2Te 12Th+8Ts+6Te Th: a one-way hash operation time, Ts: a symmetric key operation time, Te: an ECC operation time. The communication cost represents the number of communications, and the size of messages to be transmitted during the protocol run. The proposed protocol requires less number of communications and of bits compared to Xxxxxxx et al.’s [11] protocol. The communication costs are presented in Table 4. The number of communication bits is based on various length of binary sequences such as: hash function-160 bits, identity-160 bits, symmetric encryption-128 bits and ECC element-160 bits. The number of communication bits required in the proposed protocol is given as: ...
Performance Analysis. We use the FlexRay network found in BMW 7 series vehi- cles [29] as an industrial use case to analyze the performance of the proposed FlexRay key agreement mechanism and to illustrate the impact of its introduction on the communication cycle. The communication parameters of the FlexRay network designed for BMW 7 series vehicles are presented in Table IV. For the purpose of our analysis we consider that a portion of TABLE V Execution time of elliptic curve operations on the TriCore platform. Algorithm ECDH ECDSA ECDH ECDSA Curve XXXX000X0 SECP256R1 Key size 192 256 Operation Generate Extract Sign Verify Generate Extract Sign Verify Duration 84 ms 82 ms 84 ms 164 ms 136 ms 134 ms 142 ms 284 ms TABLE VI Duration of physical layer and ECDH key exchange on the TriCore platform. ECDH Our approach XXXX000X0 SECP256R1 128 bit key 128 bit key 192 bit key 256 bit key MAPO = 31 SWAPO = 63 414.24 ms 696.25 ms 5.107 ms 10.091 ms 10.123 ms MAPO = 31 SWAPO = 31 414.24 ms 696.25 ms 5.047 ms 5.079 ms 10.047 ms MAPO = 20 SWAPO = 20 414.21 ms 696.22 ms 0.095 ms 5.058 ms 5.090 ms MAPO = 10 SWAPO = 10 414.18 ms 696.19 ms 0.081 ms 5.039 ms 5.071 ms MAPO = 5 SWAPO = 5 414.16 ms 696.18 ms 0.073 ms 5.030 ms 5.062 ms MAPO - gdMinislotActionPointOffset SWAPO - gdSymbolWindowActionPointOffset the communication cycle allocated to minislots in the dynamic segment is reallocated to provide space for a maximum sized symbol window. According to the parameters listed in Table III, for a 10 Mbit/s network, this would require reallocating a time space corresponding to approximately 33 minislots. This roughly corresponds to reducing the transmission capacity of the dynamic segment by three 20 byte frames or two frames with a payload of 56 bytes. The same assumption of the max- imum APO (i.e. offset between the start of a transmission slot and the actual transmission time discussed in section IV-E) was considered for the symbol window and the dynamic segment to provide an upper bound on protocol-related transmission overhead and a lower bound on transmission performance. A smaller APO reduces transmission overhead and enables higher transmission throughput in all communication cycle segments including the symbol window. We now compare the performance of our approach to a classical key-exchange based on the widely used Xxxxxx- Xxxxxxx protocol [30] implemented on a FlexRay network. We opt for an implementation based on elliptic curves to minimize the communication overhead. Table V shows the ti...
Performance Analysis. In the following, we show the performance of our proposed scheme. The performance evaluation of the proposed scheme mainly concerns the time complex- ity. For convenience, we suppose some notations are used to analyze the computational complexity as fol- lows: HUB VSAT (Xv , Yv Whv = (Xh)Rv = (Xv)Rh = gRh·Rv mod N ) Xh, Yh Xv = gRv mod N Yv = h(Xv, h(Sv ⊕ t)) mod N Xh = gRh mod N Sv = IDv−d mod N Yh = h(Xh, h(Sv ⊕ t)) mod N
Performance Analysis. Our proposed mechanism takes the GTK as a substitute for the original GAK so that the primary GAK can be protected whereas the SN can be fully authorized to authenticate the roaming MS group with exactly one key instead of several distinct authentication data for individual MSs. For HN, the signaling overhead between SN is reduced. For SN, not only the communication bandwidth between HN is saved but also the storage cost for user database is diminished. As for MS, except the first member in group, au- thentication key is pre-distributed without extra message exchange. Furthermore, one MS can belong to more than one group and hold multiple GAKs. Thus the MS is able to decide different group identity for group authentication when roaming to different SNs. One of the most important performance evaluations of AKA protocols are the secure level. In our proposed mechanism, HN authenticates the legitimacy of MS before pro- viding the group authentication data to SN so that SN cannot obtain MS’s authentication data without a request message from MS. The freshness of messages for mutual authen- tication between SN and MS can be assured by the random number generated by both side. If a malicious MS tries to impersonate other members in the same group with the identical GAK, SN is able to identify the vicious member by comparing the IV in Index Table provided by HN. With the unique MKs for different pairs of MS and SN, the secure channel between MS and SN is established.
Performance Analysis. A. Security Analysis There are four major security apprehensions regarding group communication: group key secrecy, backward secrecy, forward secrecy and key independence [3,6]. SGRS addresses all of these security concerns.
